1 files changed, 0 insertions, 11874 deletions
diff --git a/scraper/reports/stats/unknown_papers.csv b/scraper/reports/stats/unknown_papers.csv
index b3090c78..9b9cce02 100644
--- a/scraper/reports/stats/unknown_papers.csv
+++ b/scraper/reports/stats/unknown_papers.csv
@@ -22,10 +22,6 @@ Department of Electrical Engineering and Robotics, Shahrood University of Techno
 Milad Lankarany and Alireza Ahmadyfard
 Keywords:
 Ear Biometrics, Ear Segmentation, Topographic Features."
-adf1b20cffb0ab12d20f878d07373efc4c1bc6c4,Image Retagging Using Collaborative Tag Propagation,"Image Retagging Using Collaborative
-Tag Propagation
-Dong Liu, Shuicheng Yan, Senior Member, IEEE, Xian-Sheng Hua, Member, IEEE, and
-Hong-Jiang Zhang, Fellow, IEEE"
 ad7a7f70e460d4067d7170bcc0f1ea62eedd7234,CBinfer: Exploiting Frame-to-Frame Locality for Faster Convolutional Network Inference on Video Streams,"CBinfer: Exploiting Frame-to-Frame Locality for Faster
 Convolutional Network Inference on Video Streams
 Lukas Cavigelli, Luca Benini"
@@ -45,14 +41,6 @@ Department of Computer Science, The University of Georgia, Athens, Georgia 30602
 Karan Sharma Arun CS Kumar
 Emails:
 Suchendra M. Bhandarkar"
-ada4901e0022b4fdeb9ec3ae26b986199f7ae3be,Human Face Recognition based on Improved PCA Algorithm,"Human Face Recognition based on Improved
-PCA Algorithm
-Xu Yue
-College of art and design, LanZhou JiaoTong University, Lanzhou, China
-Email:
-Linhao Li
-AT&T Labs, 200 South Laurel Ave, #D4-3C05, NJ, USA
-Email:"
 ade32e04dceeaed72c3e99a9f3698b2fe01c9863,Learning confidence measures in the wild,"F. TOSI ET AL.: LEARNING CONFIDENCE MEASURES IN THE WILD
 Learning conﬁdence measures in the wild
 University of Bologna
@@ -140,18 +128,6 @@ Sumazly Ulaiman and 2R.U. Gobithaasan
 Center for Artificial Intelligent Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia
 School of Informatics and App. Maths, Universiti Malaysia Terengganu, Terengganu, Malaysia
 Received 2014-02-20; Revised 2014-04-29; Accepted 2014-08-04"
-adaff7ff015b4be77e8c0bdb9d002b614d6e2851,A Hybrid Method for Face Recognition using LLS CLAHE Method,"International Journal of Computer Applications (0975 – 8887)
-Volume 152 – No.7, October 2016
-A Hybrid Method for Face Recognition using LLS
-CLAHE Method
-Mohandas College of Engineering and
-A. Thamizharasi
-Assistant Professor,
-Department of Computer
-Science & Engineering,
-Technology,
-Anad, Nedumangad P.O.,
-Trivandrum, Kerala, India"
 ad88fcfd12b62d607259db8d98e2a1a0a9642ca0,Real-time tracking-with-detection for coping with viewpoint change,"Real-Time Tracking-with-Detection for Coping With Viewpoint Change
 Shaul Oron · Aharon Bar-Hillel · Shai Avidan
 Received: 11 May 2014 / Revised: 02 Nov 2014 / Accepted: 09 Mar 2015"
@@ -161,21 +137,9 @@ Alex M. Bronstein
 Michael M. Bronstein
 Pablo Sprechmann
 Guillermo Sapiro"
-ad9937ff6c5bff4dae72ca90eddc4dd77751b3fa,FusionNet and AugmentedFlowNet: Selective Proxy Ground Truth for Training on Unlabeled Images,"FusionNet and AugmentedFlowNet:
-Selective Proxy Ground Truth
-for Training on Unlabeled Images
-Osama Makansi*, Eddy Ilg*, and Thomas Brox
-University of Freiburg, Germany"
 ad6bcf4384a7604b6252a6eeefade4c486b01240,Cluster-Based Distributed Face Tracking in Camera Networks,"Cluster-Based Distributed Face Tracking in Camera
 Networks
 Josiah Yoder, Henry Medeiros, Johnny Park, and Avinash C. Kak"
-adb2d1e241933ef363bcf03d865a9219d2911780,Classification of Age from Facial Features of Humans,"International Journal of Science and Research (IJSR)
-ISSN (Online): 2319-7064
-Index Copernicus Value (2013): 6.14 | Impact Factor (2014): 5.611
-Classification of Age from Facial Features of
-Poonam Shirode1, S. M. Handore2
-, 2Department of E&TC, K.J’s Educational Institute’s TCOER, Pune, Maharashtra, India
-Humans"
 ad8642e186c5c81d06934d4e6fc249b7cbca40e8,Learning Transferable Architectures for Scalable Image Recognition,"Learning Transferable Architectures for Scalable Image Recognition
 Barret Zoph
 Google Brain
@@ -233,20 +197,6 @@ psychophysical paradigm for investigating motor contributions to expression perc
 some of the limitations inherent in simple labeling and rating tasks. Observers were asked to judge
 whether smiles drawn from a morph continuum were sincere or insincere, in the presence or absence of
 motor load induced by the concurrent production of vowel sounds. Having confirmed that smile"
-040601d28b683c3c8b48b29e93b6aa3c26dbdf5f,"Facial Expression Recognition for Color Images using Gabor , Log Gabor Filters and PCA","International Journal of Computer Applications (0975 – 8887)
-Volume 113 – No. 4, March 2015
-Facial Expression Recognition for Color Images using
-Gabor, Log Gabor Filters and PCA
-Shail Kumari Shah
-PG Scholar,
-Computer Engg. Dept.
-Vineet Khanna
-Assistant Professor,
-Computer Engg. Dept.
-Rajasthan College of Engineering for Women
-Rajasthan Technical University, Jaipur, India
-Rajasthan College of Engineering for Women
-Rajasthan Technical University, Jaipur, India"
 04cb43806ca57040100b33af0781e4331f8daa56,Long-term Multi-granularity Deep Framework for Driver Drowsiness Detection,"Long-term Multi-granularity Deep Framework
 for Driver Drowsiness Detection
 Jie Lyu
@@ -258,15 +208,6 @@ Xi’an Jiaotong University
 Email:
 Email:
 Email:"
-0410659b6a311b281d10e0e44abce9b1c06be462,"A Gift from Knowledge Distillation: Fast Optimization, Network Minimization and Transfer Learning","A Gift from Knowledge Distillation:
-Fast Optimization, Network Minimization and Transfer Learning
-Junho Yim1
-Donggyu Joo1
-Jihoon Bae2
-Junmo Kim1
-School of Electrical Engineering, KAIST, South Korea
-Electronics and Telecommunications Research Institute
-{junho.yim, jdg105,"
 047d7cf4301cae3d318468fe03a1c4ce43b086ed,Co-Localization of Audio Sources Using Binaural Features and Locally-Linear Regression,"Co-Localization of Audio Sources in Images Using
 Binaural Features and Locally-Linear Regression
 Antoine Deleforge, Radu Horaud, Yoav Y. Schechner, Laurent Girin
@@ -374,26 +315,6 @@ August 2002
 04e5d374c10b70a74d79070103cab1f362b113ba,"DeepHash: Getting Regularization, Depth and Fine-Tuning Right","DeepHash: Getting Regularization, Depth and Fine-Tuning Right
 Jie Lin∗,1,3, Olivier Mor`ere∗,1,2,3, Vijay Chandrasekhar1,3, Antoine Veillard2,3, Hanlin Goh1,3
 I2R1, UPMC2, IPAL3"
-0422a9bc1bde71d3b4fc4f52b4a62b15f2fb101f,A Customized Vision System for Tracking Humans Wearing Reflective Safety Clothing from Industrial Vehicles and Machinery,"Sensors 2014, 14, 17952-17980; doi:10.3390/s141017952
-OPEN ACCESS
-sensors
-ISSN 1424-8220
-www.mdpi.com/journal/sensors
-Article
-A Customized Vision System for Tracking Humans
-Wearing Reflective Safety Clothing from Industrial
-Vehicles and Machinery
-Rafael Mosberger *, Henrik Andreasson and Achim J. Lilienthal
-AASS Research Centre, Örebro University, 70182 Örebro, Sweden;
-E-Mails: (H.A.); (A.J.L.)
-* Author to whom correspondence should be addressed; E-Mail:
-Tel.: +46-1930-1113; Fax: +46-1930-3463.
-External Editor: Vittorio M.N. Passaro
-Received: 8 July 2014; in revised form: 5 September 2014 / Accepted: 9 September 2014 /
-Published: 26 September 2014"
-04741341e26bdcd9ed1de18e5a95c31d7b64fa36,Adversarial Action Prediction Networks,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, FEBRUARY 2018
-Adversarial Action Prediction Networks
-Yu Kong, Member, IEEE, Zhiqiang Tao, Student Member, IEEE and Yun Fu, Senior Member, IEEE"
 0485e96bb0c1276fe2a27271b939b6e67997acfc,Active Learning for Structured Probabilistic Models,"Active Learning for Structured Probabilistic Models
 Qing Sun
 Virginia Tech
@@ -445,15 +366,6 @@ Using DCT for Face Detection
 Radovan Fusek, Eduard Sojka, Karel Mozdˇreˇn, and Milan ˇSurkala
 Technical University of Ostrava, FEECS, Department of Computer Science,
 7. listopadu 15, 708 33 Ostrava-Poruba, Czech Republic"
-04d9abdae728f09e1d1f78e36a5de551c3a690f5,Color Local Texture Features Based Face Recognition,"International Journal of Innovations in Engineering and Technology (IJIET)
-Color Local Texture Features Based Face
-Recognition
-Priyanka V. Bankar
-Department of Electronics and Communication Engineering
-SKN Sinhgad College of Engineering, Korti, Pandharpur, Maharashtra, India
-Department of Electronics and Communication Engineering
-SKN Singhgad College of Engineering, Korti, Pandharpur, Maharashtra, India
-Anjali C. Pise"
 044600cc4b93bb0504e8d72a5476d16f1a61a107,Discriminant Analysis of Principal Components for Face Recognition,"DiscriminantAnalysisofPrincipalComponentsforFace
 Recognition(cid:3)
 W.Zhao
@@ -479,26 +391,6 @@ Socio-affective touch expression database
 Haemy Lee Masson*, Hans Op de Beeck*
 Department of Brain and Cognition, KU Leuven, Leuven, Belgium
 * (HLM); (HOB)"
-0435a34e93b8dda459de49b499dd71dbb478dc18,"VEGAC: Visual Saliency-based Age, Gender, and Facial Expression Classification Using Convolutional Neural Networks","VEGAC: Visual Saliency-based Age, Gender, and Facial Expression Classification
-Using Convolutional Neural Networks
-Ayesha Gurnani£1, Vandit Gajjar£1, Viraj Mavani£1, Yash Khandhediya£1
-Department of Electronics and Communication Engineering and
-Computer Vision Group, L. D. College of Engineering, Ahmedabad, India
-{gurnani.ayesha.52, gajjar.vandit.381, mavani.viraj.604,
-the  need  for  handcrafted  facial  descriptors  and  data
-preprocessing.  D-CNN  models  have  been  not  only
-successfully  applied  to  human  face  analysis,  but  also  for
-the visual saliency detection [21, 22, 23]. Visual Saliency
-is  fundamentally  an  intensity  map  where  higher  intensity
-signifies  regions,  where  a  general  human  being  would
-look, and lower intensities mean decreasing level of visual
-ttention.  It’s  a  measure  of  visual  attention  of  humans
-ased  on  the  content  of  the  image.  It  has  numerous
-pplications  in  computer  vision  and  image  processing
-tasks. It is still an open problem when considering the MIT
-Saliency Benchmark [24].
-In  previous  five  years,  considering  age  estimation,
-gender  classification  and  facial  expression  classification"
 0447bdb71490c24dd9c865e187824dee5813a676,Manifold Estimation in View-based Feature Space for Face Synthesis Across Pose Paper 27,"Manifold Estimation in View-based Feature
 Space for Face Synthesis Across Pose
 Paper 27"
@@ -582,9 +474,6 @@ descriptor
 Walid AYEDI1,2, Hichem SNOUSSI1, Fethi SMACH2 and Mohamed ABID2
 Charles Delaunay Institute (FRE CNRS 2848), University of Technology of Troyes, 10010 Troyes, France
 Sfax University, National Engineering School of Sfax, 3052 Sfax, Tunisia"
-04adf2e51df06a03b6decf520b0952a54a538a18,Randomized Robust Subspace Recovery and Outlier Detection for High Dimensional Data Matrices,"Randomized Robust Subspace Recovery for High Dimensional
-Data Matrices
-Mostafa Rahmani, Student Member, IEEE and George K. Atia, Member, IEEE"
 047f8d5d5134dd12c67038623417f05ab9885056,Motion Synthesis In : Static Scan + Expression Out : Best Fitting Sequence + Angry Out : Animated Sequence Statistical Analysis Expression Recognition,"D Faces in Motion: Fully Automatic Registration and Statistical Analysis
 Timo Bolkarta,∗, Stefanie Wuhrera
 Saarland University, Saarbr¨ucken, Germany"
@@ -594,27 +483,12 @@ Marc-Andr´e Carbonneau∗
 Veronika Cheplygina†
 Eric Granger∗
 Ghyslain Gagnon‡"
-04afb510e11e963fb18e3271ac966164db806120,Harvesting Social Images for Bi-Concept Search,"Harvesting Social Images for Bi-Concept Search
-Xirong Li, Cees G. M. Snoek, Senior Member, IEEE, Marcel Worring, Member, IEEE, and
-Arnold W. M. Smeulders, Member, IEEE"
 0480b458439069687ec41c90178ba7e9a056bcca,Gender Classification Using Gradient Direction Pattern,"Sci.Int(Lahore),25(4),797-799,2013
 ISSN 1013-5316;  CODEN: SINTE 8
 GENDER CLASSIFICATION USING GRADIENT DIRECTION PATTERN
 Department of Computer Science, School of Applied Statistics,
 National Institute of Development Administration, Bangkok, Thailand.
 Mohammad Shahidul Islam"
-04f55f81bbd879773e2b8df9c6b7c1d324bc72d8,Multi-view Face Analysis Based on Gabor Features,"Multi-view Face Analysis Based on Gabor Features
-Hongli Liu，  Weifeng Liu，  Yanjiang Wang
-College of Information and Control Engineering in China University of Petroleum,
-Qingdao 266580, China"
-04b4c779b43b830220bf938223f685d1057368e9,Video retrieval based on deep convolutional neural network,"Video retrieval based on deep convolutional
-neural network
-Yajiao Dong
-School of Information and Electronics,
-Beijing Institution of Technology, Beijing, China
-Jianguo Li
-School of Information and Electronics,
-Beijing Institution of Technology, Beijing, China"
 041ac91c85276f61bec3f0f3c42782e4f9a31f88,Detailed Dense Inference with Convolutional Neural Networks via Discrete Wavelet Transform,"Detailed Dense Inference with Convolutional Neural Networks
 via Discrete Wavelet Transform
 Lingni Ma1, J¨org St¨uckler2, Tao Wu1 and Daniel Cremers1"
@@ -652,15 +526,6 @@ Zeeshan Hayder1,2, Xuming He2,1
 Australian National University & 2Data61/CSIRO ∗
 Mathieu Salzmann2,3
 CVLab, EPFL, Switzerland"
-9d757c0fede931b1c6ac344f67767533043cba14,Search Based Face Annotation Using PCA and Unsupervised Label Refinement Algorithms,"Search Based Face Annotation Using PCA and
-Unsupervised Label Refinement Algorithms
-Shital Shinde1, Archana Chaugule2
-Computer Department, Savitribai Phule Pune University
-D.Y.Patil Institute of Engineering and Technology, Pimpri, Pune-18
-Mahatma Phulenagar, 120/2 Mahaganpati soc, Chinchwad, Pune-19, MH, India
-D.Y.Patil Institute of Engineering and Technology, Pimpri, Pune-18
-Computer Department, D.Y.PIET, Pimpri, Pune-18, MH, India
-presents"
 9da2b79c6942852e8076cdaa4d4c93eb1ae363f1,Constraint-Based Visual Generation,"Constraint-Based Visual Generation
 Giuseppe Marra
 Francesco Giannini
@@ -718,10 +583,6 @@ Using 3D Thermal Sensing
 Ariel Kapusta and Patrick Beeson
 IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN)
 August, 30, 2016"
-9d9d496565c68a2d0ba5026aa527215ac5f82e23,Generating Discriminating Cartoon Faces Using Interacting Snakes,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 25, NO. 11, NOVEMBER 2003
-Generating Discriminating Cartoon Faces
-Using Interacting Snakes
-Rein-Lien Hsu, Member, IEEE, and Anil K. Jain, Fellow, IEEE"
 9d0ceae3747467488ba914cb2ca5b30ac3032286,Modèles graphiques probabilistes pour la reconnaissance de formes. (Probabilistic graphical models for shape recognition),"Modèles graphiques probabilistes pour la reconnaissance
 de formes
 Sabine Barrat
@@ -816,9 +677,6 @@ Cheng-Yang Fu Mykhailo Shvets Alexander C. Berg
 Computer Science Department of
 UNC at Chapel Hill
 {cyfu, mshvets,"
-9d4c05c7c9284c8e303641b95e997f11df2dd1a7,Misalignment-robust Face Recognition via Efficient Locality-constrained Representation,"Misalignment-robust Face Recognition via Effi-
-ient Locality-constrained Representation
-Yandong Wen, Weiyang Liu, Meng Yang, Member, IEEE, Yuli Fu, Zhifeng Li, Senior Member, IEEE"
 9d8fd639a7aeab0dd1bc6eef9d11540199fd6fe2,EARNING TO C LUSTER,"Workshop track - ICLR 2018
 LEARNING TO CLUSTER
 Benjamin B. Meier, Thilo Stadelmann & Oliver D¨urr
@@ -855,10 +713,6 @@ Luc van Gool1,3
 ETH Z¨urich
 Kooaba AG
 K.U. Leuven"
-9da9ee38d5845d39497b10b0ab442580e75ee4d3,Dynamic Video Segmentation Network,"Dynamic Video Segmentation Network
-Yu-Syuan Xu, Tsu-Jui Fu∗, Hsuan-Kung Yang∗, Student Member, IEEE and Chun-Yi Lee, Member, IEEE
-Elsa Lab, Department of Computer Science, National Tsing Hua Uiversity
-{yusean0118, rayfu1996ozig,"
 9d518344d5c7d889f9c90c6193be4757fa584770,3 D registration based on a multi-references local parametrisation : Application to 3 D faces,"D registration based on a multi-references local parametrisation:
 Application to 3D faces
 Wieme Gadacha1, Faouzi Ghorbel1
@@ -945,11 +799,6 @@ P. Sumathi
 R. Manickachezian
 Associate Professor, Research Department of Computer Science,
 NGM College, Pollachi, Coimbatore, Tamil Nadu, India."
-c22aa66b2fad7ed31252b5e6276a0df371c57b4c,The neural network image captioning model based on adversarial training,"The neural network image captioning model based on
-dversarial training
-K P Korshunova1
-The Branch of  National Research University ""Moscow Power Engineering Institute"" in
-Smolensk, Russia"
 c231d8638e8b5292c479d20f7dd387c53e581a1a,Multi-View Data Generation Without View Supervision,"MULTI-VIEW DATA GENERATION WITHOUT VIEW
 SUPERVISION
 Micka¨el Chen, Ludovic Denoyer
@@ -983,26 +832,6 @@ Subscriptions:
 http://jcn.sagepub.com/subscriptions
 Reprints:
 http://www.sagepub.com/journalsReprints.nav"
-c2d065bc8067384c40b3e8146cadc9a0c4c1d633,SLC25A12 expression is associated with neurite outgrowth and is upregulated in the prefrontal cortex of autistic subjects,"& 2008 Nature Publishing Group All rights reserved 1359-4184/08 $30.00
-www.nature.com/mp
-ORIGINAL ARTICLE
-SLC25A12 expression is associated with neurite
-outgrowth and is upregulated in the prefrontal cortex
-of autistic subjects
-A-M Lepagnol-Bestel1, G Maussion1, B Boda2, A Cardona3, Y Iwayama4, A-L Delezoide5, J-M Moalic1,
-D Muller2, B Dean6, T Yoshikawa4,7, P Gorwood1, JD Buxbaum8,9, N Ramoz1 and M Simonneau1
-INSERM U675, IFR2, Faculte´ de Me´ decine Xavier Bichat, Paris, France; 2Department of Basic Neuroscience, Centre Medical
-Universitaire, Geneva, Switzerland; 3Histotechnology and Pathology Unit, Institut Pasteur, Paris, France; 4Laboratory for
-AP-HP, Paris, France; 6The Rebecca L Cooper Research Laboratories, Mental Health Research Institute of Victoria, Parkville,
-VIC, Australia; 7CREST, Japan Science and Technology Agency, Saitama, Japan; 8Department of Psychiatry, Mount Sinai
-School of Medicine, New York, NY, USA and 9Department of Neuroscience, Mount Sinai School of Medicine, New York,
-NY, USA
-in the BA46 prefrontal cortex but not
-Autism is a neurodevelopmental disorder with a strong genetic component, probably involving
-several genes. Genome screens have provided evidence of linkage to chromosome 2q31–q33,
-which includes the SLC25A12 gene. Association between autism and single-nucleotide
-polymorphisms in SLC25A12 has been reported in various studies. SLC25A12 encodes the
-mitochondrial aspartate/glutamate carrier functionally important"
 c2fb2cb5487ad404b8e66daf74198496c40bef32,Learning to Transfer Privileged Information,"Learning to Transfer Privileged Information
 Viktoriia Sharmanska1∗, Novi Quadrianto2, and Christoph Lampert1,
 Institute of Science and Technology Austria, Austria
@@ -1027,12 +856,6 @@ in the joint-trajectories space. Our view-invariant recognition system has the f
 (1) Given a labeled Mocap sequences with M markers in 3D, which is a 3M -dimensional sequential
 data, the low dimensional manifold structure (i.e., geodesics distance, intrinsic dimensionality, etc)
 is learnt by using Tensor Voting. This is an offline process, as shown in Fig. 1."
-c220f457ad0b28886f8b3ef41f012dd0236cd91a,Crystal Loss and Quality Pooling for Unconstrained Face Verification and Recognition.,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015
-Crystal Loss and Quality Pooling for
-Unconstrained Face Veriﬁcation and Recognition
-Rajeev Ranjan, Member, IEEE, Ankan Bansal, Hongyu Xu, Member, IEEE,
-Swami Sankaranarayanan, Member, IEEE, Jun-Cheng Chen, Member, IEEE,
-Carlos D Castillo, Member, IEEE, and Rama Chellappa, Fellow, IEEE"
 c2f2c89d7615df07b540748d6c53485c4cbfa9c0,An Experience Report on Requirements-Driven Model-Based Synthetic Vision Testing,"An Experience Report on Requirements-Driven
 Model-Based Synthetic Vision Testing
 Markus Murschitz and Oliver Zendel and Martin Humenberger
@@ -1061,10 +884,6 @@ c2cb38fc68b877a96be99b814e8ee437e585f5b2,Mining on Manifolds: Metric Learning wi
 Ahmet Iscen1 Giorgos Tolias1 Yannis Avrithis2 Ondˇrej Chum1
 VRG, FEE, CTU in Prague
 Inria Rennes"
-c238f871c029d8c33949f8410f8cf3bf79ffc102,No Blind Spots: Full-Surround Multi-Object Tracking for Autonomous Vehicles using Cameras & LiDARs,"No Blind Spots: Full-Surround Multi-Object
-Tracking for Autonomous Vehicles using
-Cameras & LiDARs
-Akshay Rangesh, Member, IEEE, and Mohan M. Trivedi, Fellow, IEEE"
 c2e9300b0e72dca0b95ccd4181fc2a7a5178dea7,Improving Bilayer Product Quantization for Billion-Scale Approximate Nearest Neighbors in High Dimensions.,"Improving Bilayer Product Quantization
 for Billion-Scale Approximate Nearest Neighbors in High
 Dimensions
@@ -1129,9 +948,6 @@ EM LCT
 Universit`a degli Studi di Trento
 Raffaella Bernardi
 CIMeC, DISI"
-3f14b504c2b37a0e8119fbda0eff52efb2eb2461,Joint Facial Action Unit Detection and Feature Fusion: A Multi-Conditional Learning Approach,"Joint Facial Action Unit Detection and Feature
-Fusion: A Multi-Conditional Learning Approach
-Stefanos Eleftheriadis, Ognjen Rudovic, Member, IEEE, and Maja Pantic, Fellow, IEEE"
 3fd90098551bf88c7509521adf1c0ba9b5dfeb57,Attribute-Based Classification for Zero-Shot Visual Object Categorization,"Page 1 of 21
 *****For Peer Review Only*****
 Attribute-Based Classiﬁcation for Zero-Shot
@@ -1287,10 +1103,6 @@ lthough some heterogeneous conﬁgurations yield better throughput and per-progr
 homogeneous designs, some homogeneous conﬁgurations are optimal for particular throughput versus per-
 program performance trade-offs. Two core types provide most of the beneﬁts from heterogeneity and a larger
 number of core types does not contribute much; job-to-core mapping is both important and challenging for"
-3fb689c0f1db224d53d9fdaee578d3ff8522f807,"Integrating Motion, Illumination, and Structure in Video Sequences with Applications in Illumination-Invariant Tracking","Integrating Motion, Illumination, and Structure
-in Video Sequences with Applications in
-Illumination-Invariant Tracking
-Yilei Xu, Student Member, IEEE, and Amit K. Roy-Chowdhury, Member, IEEE"
 3f44352b857f2fc18c18c5ebb2cbf994ee22f44c,Humanist computing for knowledge discovery from ordered datasets,"HumanistComputingforKnowledgeDiscovery
 fromOrderedDatasets
 JonathanMichaelRossiter
@@ -1322,10 +1134,6 @@ Evan Racah1, Christopher Beckham2, Tegan Maharaj2
 Prabhat1, Christopher Pal2
 Lawrence Berkeley National Lab, Berkeley, CA,
 ´Ecole Polytechnique de Montr´eal,"
-3fbd68d1268922ee50c92b28bd23ca6669ff87e5,A shape- and texture-based enhanced Fisher classifier for face recognition,"IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 10, NO. 4, APRIL 2001
-A Shape- and Texture-Based Enhanced Fisher
-Classifier for Face Recognition
-Chengjun Liu, Member, IEEE, and Harry Wechsler, Fellow, IEEE"
 3faff93758fe7fc58b3832055cb15c6ca3f306a7,Evaluation of multi feature fusion at score-level for appearance-based person re-identification,"Evaluation of Multi Feature Fusion at Score-Level
 for Appearance-based Person Re-Identiﬁcation
 Markus Eisenbach
@@ -1349,12 +1157,6 @@ degree of Doctor of Philosophy
 Faculty of Science and Engineering
 The Department of Computing and Mathematics
 October 2010"
-3f40c1d8c2fe5d416ffca93049d3f3539fb52079,Sample-Level CNN Architectures for Music Auto-Tagging Using Raw Waveforms,"SAMPLE-LEVEL CNN ARCHITECTURES FOR MUSIC AUTO-TAGGING
-USING RAW WAVEFORMS
-Taejun Kim1, Jongpil Lee2, Juhan Nam2
-School of Electrical and Computer Engineering, University of Seoul,
-Graduate School of Culture Technology, KAIST,
-{richter,"
 e5eb7fa8c9a812d402facfe8e4672670541ed108,Performance of PCA Based Semi-supervised Learning in Face Recognition Using MPEG-7 Edge Histogram Descriptor,"Performance of PCA Based Semi-supervised
 Learning in Face Recognition Using MPEG-7
 Edge Histogram Descriptor
@@ -1385,18 +1187,6 @@ Interested in publishing with us?
 Contact"
 e5320955580401d5a5b2ae8b507e8f0b47e08118,Deep Supervision with Intermediate Concepts,"Deep Supervision with Intermediate Concepts
 Chi Li, M. Zeeshan Zia, Quoc-Huy Tran, Xiang Yu, Gregory D. Hager, and Manmohan Chandraker"
-e5c4b75cb79aa5155ffd9498b3fcc790eb794e72,Object Recognition using Discriminative Robust Local Binary Pattern,"WWW.IJITECH.ORG
-ISSN 2321-8665
-Vol.03,Issue.05,
-July-2015,
-Pages:0700-0706
-Object Recognition using Discriminative Robust Local Binary Pattern
-T. LAVANYA
-, A. SUJATHA
-PG Scholar, Dept of DE & CS, Dr.K.V.Subba Reddy Engineering College for Women, AP, India,
-Associate Professor, Dept of DE & CS, Dr.K.V.Subba Reddy Engineering College for Women, AP, India,
-E-mail:
-E-mail:"
 e58f08ad6e0edd567f217ef08de1701a8c29fcc8,Pseudo-task Augmentation: From Deep Multitask Learning to Intratask Sharing - and Back,"Pseudo-task Augmentation: From Deep Multitask
 Learning to Intratask Sharing—and Back
 Elliot Meyerson 1 2 Risto Miikkulainen 1 2"
@@ -1474,12 +1264,6 @@ AJE= ==Fœ EJ=L	JAA	I =H?FAI
 6	=LAAJﬁ 5=JHO
 BH=JE= 2D, D=C=J
 -6- 66 1BH?EI 6=I	"
-e545f1c06799bfd2bd5f7eaed085fd60a388202f,A top-down manner-based DCNN architecture for semantic image segmentation,"RESEARCH ARTICLE
-A top-down manner-based DCNN
-rchitecture for semantic image
-segmentation
-Kai Qiao, Jian Chen, Linyuan Wang, Lei Zeng, Bin Yan*
-National Digital Switching System Engineering and Technological Research Centre, Zhengzhou, China"
 e525ba29497bab9b530ea7b056dd0128be22c48a,Tencent ML-Images: A Large-Scale Multi-Label Image Database for Visual Representation Learning.,"Tencent ML-Images: A Large-Scale Multi-Label
 Image Database for Visual Representation
 Learning
@@ -1503,21 +1287,6 @@ Radu Timofte
 ETH Zurich, Merantix
 Luc Van Gool
 ETH Zurich, KU Leuven"
-e510f2412999399149d8635a83eca89c338a99a1,Face Recognition using Block-Based DCT Feature Extraction,"Journal of Advanced Computer Science and Technology, 1 (4) (2012) 266-283
-(cid:13)Science Publishing Corporation
-www.sciencepubco.com/index.php/JACST
-Face Recognition using Block-Based
-DCT Feature Extraction
-K Manikantan1, Vaishnavi Govindarajan1,
-V V S Sasi Kiran1, S Ramachandran2
-Department of Electronics and Communication Engineering,
-M S Ramaiah Institute of Technology, Bangalore, Karnataka, India 560054
-E-mail:
-E-mail:
-E-mail:
-Department of Electronics and Communication Engineering,
-S J B Institute of Technology, Bangalore, Karnataka, India 560060
-E-mail:"
 e56c4c41bfa5ec2d86c7c9dd631a9a69cdc05e69,Human Activity Recognition Based on Wearable Sensor Data: A Standardization of the State-of-the-Art,"Human Activity Recognition Based on Wearable
 Sensor Data: A Standardization of the
 State-of-the-Art
@@ -1525,15 +1294,6 @@ Artur Jord˜ao, Antonio C. Nazare Jr., Jessica Sena and William Robson Schwartz
 Smart Surveillance Interest Group, Computer Science Department
 Universidade Federal de Minas Gerais, Brazil
 Email: {arturjordao, antonio.nazare, jessicasena,"
-e5346a581ade62e1ac4b272d26d340fe78b58faa,Weakly Supervised Semantic Segmentation Using Web-Crawled Videos,"Weakly Supervised Semantic Segmentation using Web-Crawled Videos
-Seunghoon Hong† Donghun Yeo† Suha Kwak‡ Honglak Lee§ Bohyung Han†
-POSTECH
-Pohang, Korea
-{maga33, hanulbog,
-DGIST
-Daegu, Korea
-§University of Michigan
-Ann Arbor, MI, USA"
 e564268a03b21fa092390db0c11ba1c33d2323f9,Multi-view Stereo with Single-View Semantic Mesh Refinement,"Multi-View Stereo with Single-View Semantic Mesh Reﬁnement
 Andrea Romanoni Marco Ciccone
 Francesco Visin Matteo Matteucci
@@ -1634,26 +1394,6 @@ Julien Meynet · Vlad Popovici ·
 Jean-Philippe Thiran
 Received: 12 October 2006 / Revised: 12 January 2007 / Accepted: 12 January 2007 / Published online: 3 March 2007
 © Springer-Verlag London Limited 2007"
-a48c71153265d6da7fbc4b16327320a5cbfa6cba,Unite the People : Closing the loop between 3 D and 2 D Human Representations Supplementary Material,"Unite the People: Closing the loop between 3D and 2D Human Representations
-Supplementary Material
-Christoph Lassner1,2
-Javier Romero2
-Martin Kiefel2
-Federica Bogo2,3
-Michael J. Black2
-Peter V. Gehler1,2
-Bernstein Center for Comp. Neuroscience1
-Max-Planck Institute for Intelligent Systems2
-Microsoft3
-Otfried-M¨uller-Str. 25, T¨ubingen
-Spemannstr. 41, T¨ubingen
-1 Station Rd., Cambridge
-. Introduction
-We have obtained human segmentation labels to inte-
-grate shape information into the SMPLify 3D ﬁtting pro-
-edure and for the evaluation of methods introduced in the
-main paper. The labels consist of foreground segmentation
-for multiple human pose datasets and six body part segmen-"
 a4f345a8a7b3d5933282cb7fa641b2957ca89113,Comparison of focus measures in face detection environments,"+2)415 . .+75 -)574-5 1 .)+- ,-6-+61
 -814-65
  HA  ,AE  +=IJHE + /KAHH=
@@ -1819,18 +1559,6 @@ a4ce0f8cfa7d9aa343cb30b0792bb379e20ef41b,Facial Landmark Machines: A Backbone-Br
 Architecture with Progressive Representation
 Learning
 Lingbo Liu, Guanbin Li, Yuan Xie, Yizhou Yu, Qing Wang and Liang Lin"
-a41581276c5d6206ce79c1c7b319556de0d15234,Couch potato or gym addict ? Semantic lifestyle profiling with wearables and fuzzy knowledge graphs,"Couch potato or gym addict? Semantic lifestyle
-proﬁling with wearables and fuzzy knowledge graphs
-Natalia Díaz-Rodríguez∗
-U2IS, ENSTA ParisTech, France
-Aki Härmä and Rim Helaoui
-Philips Research, Eindhoven, Netherlands
-{aki.harma,
-Ignacio Huitzil and Fernando Bobillo
-I3A, University of Zaragoza, Spain
-{ihuitzil,
-Umberto Straccia
-ISTI-CNR, Pisa, Italy"
 a45450824c6e8e6b42fd9bbf52871104b6c6ce8b,Optimizing the Latent Space of Generative Networks,"Optimizing the Latent Space of Generative Networks
 Piotr Bojanowski, Armand Joulin, David Lopez-Paz, Arthur Szlam
 {bojanowski, ajoulin, dlp,
@@ -1884,15 +1612,6 @@ The Netherlands
 P.O. Box 513
 5600 MB Eindhoven
 The Netherlands"
-a4bfe4ac91b295ced04f06d3b8f986b0dc5172c0,A NEW RECOGNITION TECHNIQUE NAMED SOMP BASED ON PALMPRINT USING NEURAL NETWORK BASED SELF ORGANIZING MAPS,"A S RAJA AND V JOSEPH RAJ: A NEW RECOGNITION TECHNIQUE NAMED SOMP BASED ON PALMPRINT USING NEURAL NETWORK BASED SELF ORGANIZING MAPS
-DOI: 10.21917/ijivp.2012.0064
-A NEW RECOGNITION TECHNIQUE NAMED SOMP BASED ON PALMPRINT
-USING NEURAL NETWORK BASED SELF ORGANIZING MAPS
-A. S. Raja1 and V. Joseph Raj2
-Sathyabama University, India
-E-mail:
-Department of Computer Science, Kamaraj College, India
-E-mail:"
 a481de6e9a7303784a7492ede7a7f055be7bc831,Egocentric Audio-Visual Scene Analysis. A Machine Learning and Signal Processing Approach. (Analyse Égocentrique de Scènes Audio-Visuelles. Une approche par Apprentissage Automatique et Traitement du Signal),"Egocentric Audio-Visual Scene Analysis : a machine
 learning and signal processing approach
 Xavier Alameda-Pineda
@@ -1933,32 +1652,6 @@ Anonymous CVPR submission
 Paper ID 1387"
 bc995457cf5f4b2b5ef62106856571588d7d70f2,Comparison of Maximum Likelihood and GAN-based training of Real NVPs,"Comparison of Maximum Likelihood and GAN-based training of Real NVPs
 Ivo Danihelka 1 2 Balaji Lakshminarayanan 1 Benigno Uria 1 Daan Wierstra 1 Peter Dayan 3"
-bc047bdf33c12682837fb0b2aa1ebdae99329968,The Development of an Interaction Support System for International Distance Education,"The Development of an Interaction
-Support System for International
-Distance Education
-Hsiu-Ping Yueh, Member, IEEE,
-Weijane Lin, Member, IEEE, Yi-Lin Liu,
-Tetsuo Shoji, and Michihiko Minoh, Member, IEEE"
-bcf19b964e7d1134d00332cf1acf1ee6184aff00,Trajectory-Set Feature for Action Recognition,"IEICE TRANS. INF. & SYST., VOL.E100–D, NO.8 AUGUST 2017
-LETTER
-Trajectory-Set Feature for Action Recognition
-Kenji MATSUI†, Nonmember, Toru TAMAKI†a), Member, Bisser RAYTCHEV†, Nonmember,
-nd Kazufumi KANEDA†, Member
-SUMMARY We propose a feature for action recognition called
-Trajectory-Set (TS), on top of the improved Dense Trajectory (iDT).
-The TS feature encodes only trajectories around densely sampled inter-
-est points, without any appearance features. Experimental results on the
-UCF50 action dataset demonstrates that TS is comparable to state-of-the-
-rts, and outperforms iDT; the accuracy of 95.0%, compared to 91.7% by
-key words: action recognition, trajectory, improved Dense Trajectory
-the two-stream CNN [2] that uses a single frame and a opti-
-al flow stack. In their paper stacking trajectories was also
-reported but did not perform well, probably the sparseness
-of trajectories does not ﬁt to CNN architectures. In contrast,
-we take a hand-crafted approach that can be fused later with
-CNN outputs.
-Introduction
-Action recognition has been well studied in the computer"
 bcaa5fab589d95890d539a3119657fa253176f0d,"THE PROBLEM : MID-RANGE FR AT NIGHT No Active Illumination Night Time 120 meters Evaluating the Efficiency of a Night-Time , Middle-Range Infrared Sensor for Applications in Human Detection and Recognition","THE PROBLEM: MID-RANGE FR AT NIGHT
 No Active Illumination
 NIR Led Illuminator
@@ -2063,13 +1756,6 @@ Categorisation. In Proceedings International Conference on Biometrics
 This is the author-manuscript version of this work - accessed from
 http://eprints.qut.edu.au
 Copyright 2007 Springer"
-bc6de183cd8b2baeebafeefcf40be88468b04b74,Age Group Recognition using Human Facial Images,"Age Group Recognition using Human Facial Images
-International Journal of Computer Applications (0975 – 8887)
-Volume 126 – No.13, September 2015
-Shailesh S. Kulkarni
-Dept. of Electronics and Telecommunication
-Government College of Engineering,
-Aurangabad, Maharashtra, India"
 bc15e0ebe7ff84e090aa2d74d753d87906d497f7,The Impact of Preprocessing on Deep Representations for Iris Recognition on Unconstrained Environments,"The Impact of Preprocessing on Deep
 Representations for Iris Recognition on
 Unconstrained Environments
@@ -2096,16 +1782,6 @@ Caegie e
 ib	gh A 15213
 ib	gh A 15260
 ib	gh A 15213"
-bc9c4b5379469a03415b5b35f8b627b2fbdbe967,Face Illumination Processing Using Wavelet Transform and Gradientfaces,"016 Joint International Conference on Artificial Intelligence and Computer Engineering (AICE 2016) and
-International Conference on Network and Communication Security (NCS 2016)
-ISBN: 978-1-60595-362-5
-Face Illumination Processing Using Wavelet
-Transform and Gradientfaces
-Xue HE1,a, Zhi-jun YANG1,b, Xiang-fei NIE1,c,*
-College of Electronic and Information Engineering,
-Chongqing Three Gorges University, Chongqing, China
-*Corresponding author
-Keywords: Face Illumination Processing, Wavelet Transform, Gradientfaces, Face Recognition."
 bc8bd3f5653165809af3d4525f266219add4d132,Symbolic principal component for interval-valued observations,
 bc40057335e589c30e0b6c7b71685ef0433b5af5,"Recounting ( MER ) , Surveillance Event Detection ( SED ) , and Semantic Indexing ( SIN ) Systems","IBM Research and Columbia University TRECVID-2013 Multimedia Event Detection (MED),
 Multimedia Event Recounting (MER), Surveillance Event Detection (SED), and Semantic
@@ -2140,26 +1816,6 @@ Department of Electrical Engineering, Universidad de Chile"
 8a866bc0d925dfd8bb10769b8b87d7d0ff01774d,WikiArt Emotions: An Annotated Dataset of Emotions Evoked by Art,"WikiArt Emotions: An Annotated Dataset of Emotions Evoked by Art
 Saif M. Mohammad and Svetlana Kiritchenko
 National Research Council Canada"
-8a92d17cff2096336796232e4e42bb11c590629d,Color Face Recognition Based on Curvelet Transform Ayşegül UÇAR,"Color Face Recognition Based on Curvelet Transform
-Department Mechatronics Engineering, University Firat, Elazığ, Turkey, e-mail:
-Ayşegül UÇAR
-denoising,
-ompression and texture classification [4, 7-9].
-image  enhancement,
-image
-fusion,
-image
-for  color
-Color  information provides  useful  information in  image
-processing  applications.  Some  recent  researches  have  been
-shown that face color information has considerably enhanced
-the  performance  with  respect  to  gray-scale  face  recognition
-[10-12]. In [10], it was interrogated what kind of color space is
-suitable
-recognition  and  presented  a
-discriminant  color  space  method.  In  [11],  it  was  applied  the
-Principal Component Analysis (PCA) at various color spaces
-such as HSV, RGB, YCbCr, YCgCr, and YUV and analyzed"
 8a12ee3c98b76d99531d5965f15bb77a10ec2569,Holistic Face Recognition through Multivariate Analysis and Genetic Algorithms,"Holistic Face Recognition through Multivariate Analysis and Genetic
 Algorithms"
 8acb55a72c4d6eae528a99e571b4a24d51f57fe6,Toward Crowd-Sensitive Path Planning,"Toward Crowd-Sensitive Path Planning
@@ -2170,9 +1826,6 @@ New York, NY 10065"
 Benjamin Eysenbach
 Carl Vondrick
 Antonio Torralba"
-8a0538eb80b5d41c0e5991aceeef47db01603033,Proposal Flow: Semantic Correspondences from Object Proposals,"Proposal Flow: Semantic Correspondences from
-Object Proposals
-Bumsub Ham, Member, IEEE, Minsu Cho, Cordelia Schmid, Fellow, IEEE and Jean Ponce, Fellow, IEEE"
 8a02a0517b841b53fba478a851948b86869a0582,Fast Neural Networks with Circulant Projections,"Fast Neural Networks with Circulant Projections
 Yu Cheng∗, Felix X. Yu∗, Rogerio S. Feris,
 Sanjiv Kumar, Alok Choudhary, Shih-Fu Chang"
@@ -2229,12 +1882,6 @@ State Key Lab. of Intelligent Technology and Systems
 Tsinghua National Laboratory for Information Science and Technology (TNList)
 Department of Computer Science and Technology, Tsinghua University 2Intel Labs China
 {anbang.yao,"
-8a2ed61448d9e41295753f5bd0a662ac28373e6f,Domain-Specific Face Synthesis for Video Face Recognition From a Single Sample Per Person,"Domain-Speciﬁc Face Synthesis for Video Face
-Recognition From a Single Sample Per Person
-Fania Mokhayeri
-, Student Member, IEEE, Eric Granger
-, Member, IEEE,
-nd Guillaume-Alexandre Bilodeau , Member, IEEE"
 8aae23847e1beb4a6d51881750ce36822ca7ed0b,Comparison between geometry-based and Gabor-wavelets-based facial expression recognition using multi-layer perceptron,"Comparison Between Geometry-Based and Gabor-Wavelets-Based
 Facial Expression Recognition Using Multi-Layer Perceptron
 Zhengyou Zhang
@@ -2252,9 +1899,6 @@ MTA SZTAKI, Institute for Computer Science and Control
 {varga.domonkos,
 Budapest University of Technology and Economics, Department of Networked Systems and Services
 Budapest University of Technology and Economics, Department of Material Handling and Logistics Systems"
-8a91ad8c46ca8f4310a442d99b98c80fb8f7625f,2D Segmentation Using a Robust Active Shape Model With the EM Algorithm,"D Segmentation Using a Robust Active
-Shape Model With the EM Algorithm
-Carlos Santiago, Jacinto C. Nascimento, Member, IEEE, and Jorge S. Marques"
 8a91cb96dd520ba3e1f883aa6d57d4d716c5d1c8,Low Cost Eye Tracking: The Current Panorama,"Hindawi Publishing Corporation
 Computational Intelligence and Neuroscience
 Volume 2016, Article ID 8680541, 14 pages
@@ -2275,15 +1919,6 @@ tracking constitutes an interesting alternative by allowing scalability and remo
 field has seen examples of research showing performance comparable to the IR alternatives. In this work, we survey the previous
 work on remote, visible light gaze trackers and analyze the explored techniques from various perspectives such as calibration
 strategies, head pose invariance, and gaze estimation techniques. We also provide information on related aspects of research such"
-8a77025bde5479a1366bb93c6f2366b5a6293720,Sharp Attention Network via Adaptive Sampling for Person Re-identification,"IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, VOL. XX, NO. XX, XX 2018
-Sharp Attention Network via Adaptive Sampling
-for Person Re-identiﬁcation
-Chen Shen, Guo-Jun Qi, Member, IEEE, Rongxin Jiang, Zhongming Jin, Hongwei Yong, Yaowu Chen,
-nd Xian-Sheng Hua, Fellow, IEEE"
-8ab183883acba0501c3315a914aee755b5e517d8,Synthesis-based Robust Low Resolution Face Recognition,"IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. X, NO. X, MONTH 20XX
-Synthesis-based Robust Low Resolution Face
-Recognition
-Sumit Shekhar, Student Member, IEEE, Vishal M. Patel, Member, IEEE, and Rama Chellappa, Fellow, IEEE"
 8ab16c26678245ef009cbbf87d750cfd18e21572,A Wearable Ultrasonic Obstacle Sensor for Aiding Visually Impaired and Blind Individuals,"A Wearable Ultrasonic Obstacle Sensor for Aiding Visually Impaired and Blind Individuals
 {tag}                                                                                   {/tag}
 IJCA Proceedings on National Conference on
@@ -2385,11 +2020,6 @@ January 2006
 Thème COG
 p p o r t  (cid:13)
 (cid:13) d e  r e c h e r c h e (cid:13)"
-8a2bd5dbcf0ab0130dfb97e2a035e5722aa9319e,NLP EAC Recognition by Component Separation in the Eye Region,"NLP EAC Recognition by Component
-Separation in the Eye Region
-Ruxandra Vrˆanceanu, Corneliu Florea, Laura Florea and Constantin Vertan
-The Image Processing and Analysis Laboratory (LAPI), Politehnica University of
-Bucharest, Romania"
 8a158fb9380a6666b922bc7a00121b6bf4a5ab0b,UnDEMoN 2.0: Improved Depth and Ego Motion Estimation through Deep Image Sampling,"UnDEMoN 2.0: Improved Depth and Ego Motion Estimation through Deep
 Image Sampling
 Madhu Babu V, Swagat Kumar, Anima Majumder and Kaushik Das
@@ -2526,10 +2156,6 @@ the primary visual cortex of higher mammals and the resulting features are fed i
 network for the recognition task. Next, we damage the network by reducing self-connections below a certain threshold
 in order to create dynamic attractors and hence hinder the networks ability to recognize familiar faces (faces already
 learned). Results obtained from simulations show that the resulting network responses are very similar to those of"
-6d66c98009018ac1512047e6bdfb525c35683b16,Face Recognition Based on Fitting a 3D Morphable Model,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 25, NO. 9, SEPTEMBER 2003
-Face Recognition Based on
-Fitting a 3D Morphable Model
-Volker Blanz and Thomas Vetter, Member, IEEE"
 6db59b031406546682a773baed2caed529aaf37c,Inferring the semantics of direction signs in public places,"Inferring the Semantics of Direction Signs in Public Places
 J´erˆome Maye∗, Luciano Spinello∗†, Rudolph Triebel∗, and Roland Siegwart∗
 Autonomous Systems Lab, ETH Zurich, Switzerland
@@ -2615,18 +2241,6 @@ pspb.sagepub.com"
 6d8057ce549db311b7ddaeed8dfd934b58c1c281,A RELIEF Based Feature Extraction Algorithm,"A RELIEF Based Feature Extraction Algorithm
 Yijun Sun∗
 Dapeng Wu†"
-6d5b0f6e5258d370f9af8a2cebf035fe61905db1,Gazefinder as a clinical supplementary tool for discriminating between autism spectrum disorder and typical development in male adolescents and adults,"Fujioka et al. Molecular Autism  (2016) 7:19
-DOI 10.1186/s13229-016-0083-y
-Open Access
-R ES EAR CH
-Gazefinder as a clinical supplementary tool
-for discriminating between autism
-spectrum disorder and typical development
-in male adolescents and adults
-Toru Fujioka1,2,3, Keisuke Inohara1,4, Yuko Okamoto2,3, Yasuhiro Masuya1, Makoto Ishitobi1,5, Daisuke N. Saito2,3,6,
-Minyoung Jung2,3, Sumiyoshi Arai2,3, Yukiko Matsumura1, Takashi X. Fujisawa2,3, Kosuke Narita7, Katsuaki Suzuki3,8,9,
-Kenji J. Tsuchiya3,8,9, Norio Mori3,8,9, Taiichi Katayama3, Makoto Sato2,3,10,11, Toshio Munesue3,12,
-Hidehiko Okazawa2,3,6, Akemi Tomoda2,3, Yuji Wada1,2,3 and Hirotaka Kosaka1,2,3*"
 6dd007b6e518a3aa96111028c4664f2647e5e81a,3D Face Synthesis Driven by Personality Impression,"D Face Synthesis Driven by Personality Impression
 Yining Lang1 Wei Liang1 Yujia Wang1 Lap-Fai Yu2
 Beijing Institute of Technology
@@ -2644,17 +2258,6 @@ Serena Li†, Gao Huang†, Bharath Hariharan†, Kilian Q. Weinberger†"
 6d88fb85fe5c61bd65e0a373cd39fac81a19596a,DC-Image for Real Time Compressed Video Matching,"DC-Image for Real Time Compressed
 Video Matching
 Saddam Bekhet, Amr Ahmed and Andrew Hunter"
-6d4b5444c45880517213a2fdcdb6f17064b3fa91,Harvesting Image Databases from The Web,"Journal of Information Engineering and Applications
-ISSN 2224-5782 (print) ISSN 2225-0506 (online)
-Vol 2, No.3, 2012
-www.iiste.org
-Harvesting Image Databases from The Web
-Snehal M. Gaikwad
-G.H.Raisoni College of Engg. & Mgmt.,Pune,India
-Snehal S. Pathare
-G.H.Raisoni College of Engg. & Mgmt.,Pune,India
-Trupti A. Jachak
-G.H.Raisoni College of Engg. & Mgmt.,Pune,India"
 6d7dabc58f53c0233d6d593a8fee76d1c7f44033,Robust Observation Detection for Single Object Tracking: Deterministic and Probabilistic Patch-Based Approaches,"Sensors 2012, 12, 15638-15670; doi:10.3390/s121115638
 OPEN ACCESS
 sensors
@@ -2739,10 +2342,6 @@ Gabriel Baglietto1,2*, Guido Gigante3,4, Paolo Del Giudice1,3
 INFN-Roma1, Italian National Institute for Nuclear Research (INFN), Rome, Italy, 2 IFLYSIB Instituto de
 Fı´sica de Lı´quidos y Sistemas Biolo´gicos (UNLP-CONICET), La Plata, Argentina, 3 Italian Institute of Health
 (ISS), Rome, Italy, 4 Mperience srl, Rome, Italy"
-6dddf1440617bf7acda40d4d75c7fb4bf9517dbb,"Beyond Counting: Comparisons of Density Maps for Crowd Analysis Tasks - Counting, Detection, and Tracking","JOURNAL OF LATEX CLASS FILES, VOL. XX, NO. X, MM YY
-Beyond Counting: Comparisons of Density Maps for Crowd
-Analysis Tasks - Counting, Detection, and Tracking
-Di Kang, Zheng Ma, Member, IEEE, Antoni B. Chan Senior Member, IEEE,"
 6d84d92d9ed6c226f0cc6401bc425a23432c9f96,Autism spectrum disorders: clinical and research frontiers.,"Downloaded from
 dc.bmj.com
 on 22 May 2008
@@ -2763,15 +2362,6 @@ You can respond to this article at:
 http://adc.bmj.com/cgi/eletter-submit/93/6/518
 Email alerting
 service"
-6d071848a3fd4e6c3184db0a68a41559ec9a47c8,An approach to Enhance Automatic Diagnosis of Diabetic Retinopathy and Classification by Hybrid Multilayer Feed forward Neural Networks by Genetic Algorithm,"International Journal of Science, Engineering and Technology Research (IJSETR), Volume 4, Issue 4, April 2015
-An approach to Enhance Automatic Diagnosis of
-Diabetic Retinopathy and Classification by Hybrid
-Multilayer Feed forward Neural Networks by
-Genetic Algorithm
-Rupa V. Lichode
-M. Tech ( Computer Science and Engineering )
-Department of Computer Technology
-R.C.E.R.T. Chandrapur, Maharastra, India"
 6d432962055a8c521e6b388d5a0a2140a0019a5e,Sensor network reconfiguration and big multimedia data fusion for situational awareness in smart environments,"Sensor network reconfiguration and big multimedia data fusion for situational
 wareness in smart environments
 Z. Akhtar, C. Drioli, M. Farinosi, G. Ferrin, G.L. Foresti, N. Martinel, C. Micheloni, C. Piciarelli, D.
@@ -2798,21 +2388,9 @@ Vishnu Naresh Boddeti†, Myung-Cheol Roh†, Jongju Shin, Takaharu Oguri, Takeo
 6dead19a89cbcbb71350a19925cb2c6f71261dfc,Fair k-Center Clustering for Data Summarization,"Fair k-Center Clustering for Data Summarization
 Matth¨aus Kleindessner 1 Pranjal Awasthi 1 Jamie Morgenstern 2"
 6d10beb027fd7213dd4bccf2427e223662e20b7d,User Adaptive and Context-Aware Smart Home Using Pervasive and Semantic Technologies,"Publishing CorporationJournal of Electrical and Computer EngineeringVolume 2016, Article ID 4789803, 20 pageshttp://dx.doi.org/10.1155/2016/4789803"
-6d973fb5f682c491be94aa40a184a1707a8dc24a,Combining Multiple Image Segmentations by Maximizing Expert Agreement,"Combining Multiple Image Segmentations by
-Maximizing Expert Agreement
-Joni-Kristian Kamarainen, Lasse Lensu, and Tomi Kauppi
-Machine Vision and Pattern Recognition Laboratory
-Department of Information Technology
-Lappeenranta University of Technology
-P.O. Box 20, FI-53851 Lappeenranta, Finland
-http://www2.it.lut.fi/mvpr/"
 6d77b214a39b8592cd6ce48c9945e8a2466b22ba,Videana: A Software Toolkit for Scientific Film Studies,"Ralph Ewerth, Markus Mühling, Thilo Stadelmann,
 Julinda Gllavata, Manfred Grauer, Bernd Freisleben
 Videana: A Software Toolkit for Scientific Film Studies"
-6dd0597f8513dc100cd0bc1b493768cde45098a9,Learning to parse images of articulated bodies,"Learning to parse images of articulated bodies
-Deva Ramanan
-Toyota Technological Institute at Chicago
-Chicago, IL 60637"
 309e17e6223e13b1f76b5b0eaa123b96ef22f51b,Face recognition based on a 3D morphable model,"Face Recognition based on a 3D Morphable Model
 Volker Blanz
 University of Siegen
@@ -2874,9 +2452,6 @@ Montréal, Canada
 Christopher Pal
 École Polytechnique de
 Montréal, Canada"
-30c96cc041bafa4f480b7b1eb5c45999701fe066,Discrete Cosine Transform Locality-Sensitive Hashes for Face Retrieval,"Discrete Cosine Transform Locality-Sensitive
-Hashes for Face Retrieval
-Mehran Kafai, Member, IEEE, Kave Eshghi, and Bir Bhanu, Fellow, IEEE"
 30f78071ac2bc965ffbf452a7b315d6dfddae30e,Lingusitic Analysis of Multi-Modal Recurrent Neural Networks,"Proceedings of the 2015 Workshop on Vision and Language (VL’15), pages 8–9,
 Lisbon, Portugal, 18 September 2015. c(cid:13)2015 Association for Computational Linguistics."
 30ad88ca5b834ca78619f3938b5f8ee534fd3ea8,Random Forest with Learned Representations for Semantic Segmentation,"Random Forest with Learned Representations
@@ -2952,23 +2527,6 @@ Zhijun Chen Tao Zhang Bo Zhang Kong-kat Wong
 {wanshaohua, chenzhijun, tao.zhang, zhangbo,
 Xiaomi Inc.
 August 9, 2016"
-302c2293e36e0704ccfe9af759a8505df588eb07,Face recognition with Multilevel B-Splines and Support Vector Machines,"Face Recognition with Multilevel B-Splines and Support
-Vector Machines
-Manuele Bicego
-Dipartimento di Informatica
-University of Verona
-Strada Le Grazie 15
-7134 Verona - Italia
-Gianluca Iacono
-Dipartimento di Informatica
-University of Verona
-Strada Le Grazie 15
-7134 Verona - Italia
-Vittorio Murino
-Dipartimento di Informatica
-University of Verona
-Strada Le Grazie 15
-7134 Verona - Italia"
 30962cf6f47396df88bf1c8827ebda8f0a6ff516,A Convolutional Neural Network Approach for Assisting Avalanche Search and Rescue Operations with UAV Imagery,"Article
 A Convolutional Neural Network Approach for
 Assisting Avalanche Search and Rescue Operations
@@ -3026,11 +2584,6 @@ Items deposited in White Rose Research Online are protected by copyright, with a
 indicated otherwise. They may be downloaded and/or printed for private study, or other acts as permitted by
 national copyright laws. The publisher or other rights holders may allow further reproduction and re-use of
 the full text version. This is indicated by the licence information on the White Rose Research Online record"
-306957285fea4ce11a14641c3497d01b46095989,Face recognition under varying lighting based on derivates of log image,"FACE RECOGNITION UNDER VARYING LIGHTING BASED ON
-DERIVATES OF LOG IMAGE
-Laiyun Qing1,2, Shiguang Shan2,  Wen Gao1,2
-ICT-ISVISION Joint R&D Laboratory for Face Recognition, CAS, Beijing 100080, China
-Graduate School, CAS, Beijing, 100039, China"
 30a319d6e1472c81a1987133afb01f524df459dc,Pedestrian Detection Based on Adaptive Selection of Visible Light or Far-Infrared Light Camera Image by Fuzzy Inference System and Convolutional Neural Network-Based Verification,"Article
 Pedestrian Detection Based on Adaptive Selection of
 Visible Light or Far-Infrared Light Camera Image by
@@ -3041,17 +2594,6 @@ Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildo
 Seoul 100-715, Korea; (J.K.K.); (H.G.H.)
 * Correspondence: Tel.: +82-10-3111-7022; Fax: +82-2-2277-8735
 Received: 16 June 2017; Accepted: 5 July 2017; Published: 8 July 2017"
-30f7609d111bb3bc006e3dd38678291528aa14d3,A new approach for extracting and summarizing abnormal activities in surveillance videos,"014 IEEE International
-Conference on Multimedia and
-Expo Workshops
-(ICMEW 2014)
-Chengdu, China
-4-18 July 2014
-Pages 516-1030
-IEEE Catalog Number:
-ISBN:
-CFP14IEW-POD
-978-1-4799-4716-4"
 30256c10cb7ec139b4245855850998c39b297975,Functional magnetic resonance imaging of autism spectrum disorders,"C l i n i c a l   r e s e a r c h
 Functional magnetic resonance imaging of
 utism spectrum disorders
@@ -3079,17 +2621,8 @@ Ricardo TOLEDO b
 Artiﬁcial Intelligence Research Institute (IIIA-CSIC), Campus UAB, 08193 Bellaterra,
 Computer Vision Center (CVC), Campus UAB, 08193 Bellaterra, Spain
 Spain"
-30b32f4a6341b5809428df1271bdb707f2418362,A Sequential Neural Encoder With Latent Structured Description for Modeling Sentences,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015
-A Sequential Neural Encoder with Latent Structured
-Description for Modeling Sentences
-Yu-Ping Ruan, Qian Chen, and Zhen-Hua Ling, Member, IEEE"
 30870ef75aa57e41f54310283c0057451c8c822b,Overcoming catastrophic forgetting with hard attention to the task,"Overcoming Catastrophic Forgetting with Hard Attention to the Task
 Joan Serr`a 1 D´ıdac Sur´ıs 1 2 Marius Miron 1 3 Alexandros Karatzoglou 1"
-3005a4afddab849d9070788ac0e4e95e0fff2216,"Transfer Metric Learning: Algorithms, Applications and Outlooks","JOURNAL OF LATEX CLASS FILES, VOL. XX, NO. X, XXXX XXXX
-Transfer Metric Learning: Algorithms,
-Applications and Outlooks
-Yong Luo, Yonggang Wen, Senior Member, IEEE, Ling-Yu Duan, Member, IEEE,
-nd Dacheng Tao, Fellow, IEEE"
 3099615de73bb1d6442ce29dc9959ddb91cfc282,Detecting and Tracking Sports Players with Random Forests and Context-Conditioned Motion Models,"Detecting and Tracking Sports Players with
 Random Forests and Context-Conditioned
 Motion Models
@@ -3121,15 +2654,6 @@ Vallabh Vidyanagar-388120, Gujarat, India."
 30c8a2b6a505645b9f93dcc4d365eee6f46c4c37,Using Curvilinear Features in Focus for Registering a Single Image to a 3D Object,"Using Curvilinear Features in Focus for Registering
 Single Image to a 3D Object
 Hatem A. Rashwan, Sylvie Chambon, Pierre Gurdjos, G´eraldine Morin and Vincent Charvillat"
-30b15cdb72760f20f80e04157b57be9029d8a1ab,Face Aging with Identity-Preserved Conditional Generative Adversarial Networks,"Face Aging with Identity-Preserved
-Conditional Generative Adversarial Networks
-Zongwei Wang
-Shanghaitech University
-Xu Tang
-Baidu
-Weixin Luo, Shenghua Gao∗
-Shanghaitech University
-{luowx,"
 307a810d1bf6f747b1bd697a8a642afbd649613d,An affordable contactless security system access for restricted area,"An affordable contactless security system access
 for restricted area
 Pierre Bonazza1, Johel Mitéran1, Barthélémy Heyrman1, Dominique Ginhac1,
@@ -3159,16 +2683,6 @@ Chen Sun
 Univ. of Southern California
 Ram Nevatia
 Univ. of Southern California"
-30aff559ad25dd3490712749793547bc89b0f103,Image Latent Semantic Analysis for Face Recognition,"Image Latent Semantic Analysis for Face Recognition
-Jucheng Yang 1,2,3 , Yanbin Jiao2, Jinfeng Yang4,Zhijun Fang2 , Congcong Xiong1,
-Lei Shu2
-College of Computer Science and Information Engineering, Tianjin University of Science
-nd Technology, Tianjin, China.
-School of Information Technology, Jiangxi University of Finance and Economics,
-Nanchang, China. {ybjiao, zjfang, lshu
-Ahead Software Company Limited, Nanchang, 330041, China
-Tianjin Key Lab for Advanced Signal Processing, Civil Aviation University of China,
-Tianjin, China"
 308647f22e3f1c80b7416b3c53fd56f9abfa904f,Robust Real-Time Tracking with Diverse Ensembles and Random Projections,"Robust Real-Time Tracking with Diverse Ensembles and Random Projections
 Center for Informatics Science,
 Center for Informatics Science,
@@ -3259,24 +2773,11 @@ ooperation in a sequential Prisoner’s
 Dilemma game
 Raoul Bell*, Laura Mieth, Axel Buchner
 Department of Experimental Psychology, Heinrich Heine University Du¨sseldorf, Du¨sseldorf, Germany"
-3b311a1ce30f9c0f3dc1d9c0cf25f13127a5e48c,A Coarse-to-fine Pyramidal Model for Person Re-identification via Multi-Loss Dynamic Training,"A Coarse-to-ﬁne Pyramidal Model for Person Re-identiﬁcation via Multi-Loss
-Dynamic Training
-Feng Zheng, Xing Sun, Xinyang Jiang, Xiaowei Guo, Zongqiao Yu, Feiyue Huang
-{winfredsun, sevjiang, scorpioguo, quentinyu,
-YouTu Lab, Tencent
-Shanghai, China"
-3bfa75238e15e869b902ceb62b31ffddbe8ccb0d,Describing Images using Inferred Visual Dependency Representations,"Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics
-nd the 7th International Joint Conference on Natural Language Processing, pages 42–52,
-Beijing, China, July 26-31, 2015. c(cid:13)2015 Association for Computational Linguistics"
 3b4177556f1c9f5a8f8e1b2e8d824dee20e388e4,Spatial Weighting for Bag-of-Features,"Spatial Weighting for Bag-of-Features
 Marcin Marsza(cid:7)ek
 Cordelia Schmid
 INRIA Rh(cid:136)one-Alpes, LEAR - GRAVIR
 665 av de l’Europe, 38330 Montbonnot, France"
-3ba8f8b6bfb36465018430ffaef10d2caf3cfa7e,Local Directional Number Pattern for Face Analysis: Face and Expression Recognition,"Local Directional Number Pattern for Face
-Analysis: Face and Expression Recognition
-Adin Ramirez Rivera, Student Member, IEEE, Jorge Rojas Castillo, Student Member, IEEE,
-nd Oksam Chae, Member, IEEE"
 3b08ef7aa0cf9528da42b2b594b66e4a6f7fdb7f,Active Learning for Delineation of Curvilinear Structures,"Active Learning for Delineation of Curvilinear Structures
 Agata Mosinska
 Raphael Sznitman
@@ -3305,14 +2806,6 @@ information about you. In many nonhuman species,
 direct gaze functions as an aversive stimulus, likely
 ecause of the threat value associated with eye con-"
 3bc776eb1f4e2776f98189e17f0d5a78bb755ef4,View Synthesis from Image and Video for Object Recognition Applications,
-3b570499c39cfdadc306039e58ef460f139f59d0,Part-based Visual Tracking via Structural Support Correlation Filter,"Part-based Visual Tracking via Structural Support
-Zhangjian Jia,b,c, Kai Fenga,b, Yuhua Qiana,b,c
-School of Computer & Information Technology, Shanxi University, Taiyuan, China
-Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry
-of Education, Shanxi University, Taiyuan, China
-Institute of Big Data Science and Industry, Shanxi University, Taiyuan, China"
-3bbdfa097a4c39012cb322b23051e360c2f7f023,Learning Race from Face: A Survey,"Learning Race from Face: A Survey
-Siyao Fu, Member, IEEE, Haibo He, Senior Member, IEEE, and Zeng-Guang Hou, Senior Member, IEEE"
 3b14bdb0b1a7353d94973ef4c1578e1bd4a4e35e,Three dimensional binary edge feature representation for pain expression analysis,"Three Dimensional Binary Edge
 Feature Representation for Pain
 Expression Analysis
@@ -3333,9 +2826,6 @@ Phone: +65 6408 2071; Fax: +65 6776 1378;
 E-mail:"
 3b8ad690f8d43d189ea2f2559c41b6eebac8dcc8,Mobile 3D object detection in clutter,"Mobile 3D Object Detection in Clutter
 David Meger and James J. Little"
-3b2df7d70ecbe3d0d65d27801d159ddaa150bf42,Doubly Sparse Relevance Vector Machine for Continuous Facial Behavior Estimation,"Doubly Sparse Relevance Vector Machine for
-Continuous Facial Behavior Estimation
-Sebastian Kaltwang, Sinisa Todorovic, Member, IEEE and Maja Pantic, Fellow, IEEE"
 3b8ad1f2335fc755e5cd75ee5922b8a0d432018a,A Fast and Compact Saliency Score Regression Network Based on Fully Convolutional Network,"A Fast and Compact Saliency Score Regression
 Network Based on Fully Convolutional Network
 Xuanyang Xi, Yongkang Luo, Fengfu Li, Peng Wang and Hong Qiao"
@@ -3374,14 +2864,6 @@ Olga Russakovsky* · Jia Deng* · Hao Su · Jonathan Krause ·
 Sanjeev Satheesh · Sean Ma · Zhiheng Huang · Andrej Karpathy ·
 Aditya Khosla · Michael Bernstein · Alexander C. Berg · Li Fei-Fei
 Received: date / Accepted: date"
-3bcca85ad84806be6d38d3882f7a6aac0ad90253,Video captioning with recurrent networks based on frame- and video-level features and visual content classification,"A pre-workshop version of a paper set to be presented in the ICCV 2015 Large Scale Movie Description Challenge workshop
-Video captioning with recurrent networks based on
-frame- and video-level features and visual content classiﬁcation
-Rakshith Shetty and Jorma Laaksonen
-Department of Computer Science
-Aalto University School of Science
-P.O.BOX 15400, FI-00076 AALTO
-Espoo, Finland"
 3b1ba9818e2ee6a54e7ec033c5b2ec8bdbe2935f,Social Signaling Descriptor for Group Behaviour Analysis,"Social Signaling Descriptor for Group
 Behaviour Analysis
 Eduardo M. Pereira1,2(B), Lucian Ciobanu1, and Jaime S. Cardoso1,2
@@ -3405,9 +2887,6 @@ Zhongxian Chen
 Dept. Computer Science
 Thomas Zimmie
 Dept. Civil Engineering"
-3b47e618c5ceb1c16db7f709dd1cfe53d7417b54,Discrimination on the Grassmann Manifold: Fundamental Limits of Subspace Classifiers,"Discrimination on the Grassmann Manifold:
-Fundamental Limits of Subspace Classiﬁers
-Matthew Nokleby, Member, IEEE, Miguel Rodrigues, Member, IEEE, and Robert Calderbank, Fellow,"
 3b9d94752f8488106b2c007e11c193f35d941e92,"Appearance , Visual and Social Ensembles for Face Recognition in Personal Photo Collections","#2052
 CVPR 2013 Submission #2052. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE.
 #2052
@@ -3435,13 +2914,6 @@ teaching and research institutions in France or
 broad, or from public or private research centers.
 L’archive ouverte pluridisciplinaire HAL, est
 destinée au dépôt et à la diffusion de documents"
-3b374fd726c8cd2c79c1092d76e3583265866362,Superpixel Convolutional Networks using Bilateral Inceptions,"Superpixel Convolutional Networks using
-Bilateral Inceptions
-Raghudeep Gadde1(cid:63), Varun Jampani2(cid:63), Martin Kiefel2,3, Daniel Kappler2, and
-Peter V. Gehler2,3
-Universit´e Paris-Est, LIGM (UMR 8049), CNRS, ENPC, ESIEE, UPEM, France
-Max Planck Institute for Intelligent Systems, T¨ubingen, Germany
-Bernstein Center for Computational Neuroscience, T¨ubingen, Germany"
 3bb80697a28b9876e668de2228003dbbdcb84a25,Face Recognition with semi-supervised learning and Multiple Classifiers,"Face Recognition with semi-supervised learning and Multiple
 Classifiers
 NEAMAT EL GAYAR*, SHABAN A. SHABAN† SAYED HAMDY†
@@ -3519,35 +2991,6 @@ Marzuki1, Egi Muhamad Hidayat2, Rinaldi Munir3, Ary Setijadi P4 ,Carmadi Machbub
 School of Electrical Engineering and Informatics, Institut Teknologi Bandung
 Bandung, Indonesia
 lskk.ee.itb.ac.id"
-470dbd3238b857f349ebf0efab0d2d6e9779073a,Unsupervised Simultaneous Orthogonal basis Clustering Feature Selection,"Unsupervised Simultaneous Orthogonal Basis Clustering Feature Selection
-Dongyoon Han and Junmo Kim
-School of Electrical Engineering, KAIST, South Korea
-In this paper, we propose a novel unsupervised feature selection method: Si-
-multaneous Orthogonal basis Clustering Feature Selection (SOCFS). To per-
-form feature selection on unlabeled data effectively, a regularized regression-
-ased formulation with a new type of target matrix is designed. The target
-matrix captures latent cluster centers of the projected data points by per-
-forming the orthogonal basis clustering, and then guides the projection ma-
-trix to select discriminative features. Unlike the recent unsupervised feature
-selection methods, SOCFS does not explicitly use the pre-computed local
-structure information for data points represented as additional terms of their
-objective functions, but directly computes latent cluster information by the
-target matrix conducting orthogonal basis clustering in a single uniﬁed term
-of the proposed objective function.
-Since the target matrix is put in a single uniﬁed term for regression of
-the proposed objective function, feature selection and clustering are simul-
-taneously performed. In this way, the projection matrix for feature selection
-is more properly computed by the estimated latent cluster centers of the
-projected data points. To the best of our knowledge, this is the ﬁrst valid"
-47d4838087a7ac2b995f3c5eba02ecdd2c28ba14,Automatic Recognition of Deceptive Facial Expressions of Emotion,"JOURNAL OF IEEE TRANSACTIONS ON AFFECTIVE COMPUTING, VOL. XX, NO. X, XXX 2017
-Automatic Recognition of Facial Displays of
-Unfelt Emotions
-Kaustubh Kulkarni*, Ciprian Adrian Corneanu*, Ikechukwu Ofodile*, Student Member, IEEE, Sergio
-Escalera, Xavier Bar´o, Sylwia Hyniewska, Member, IEEE, J¨uri Allik,
-nd Gholamreza Anbarjafari, Senior Member, IEEE"
-47bd6c1d7da596d3cf79f06ec0de816d10f11beb,Coupled Discriminant Analysis for Heterogeneous Face Recognition,"Coupled Discriminant Analysis for Heterogeneous
-Face Recognition
-Zhen Leiy, Member, IEEE, Shengcai Liaoz, Anil K. Jainz, Fellow, IEEE, and Stan Z. Liy, Fellow, IEEE"
 47719d391417a237701c5e275ebb1034418e20f2,Human Face Processing with 1.5D Models,"Human Face Processing with 1.5D Models
 Gin´es Garc´ıa-Mateos1, Alberto Ruiz1, and Pedro E. L´opez-de-Teruel2
 Dept. de Inform´atica y Sistemas
@@ -3578,27 +3021,13 @@ Unsupervised Deep Learning
 for Optical Flow Estimation
 Zhe Ren,1 Junchi Yan,2,3∗ Bingbing Ni,1 Bin Liu,4 Xiaokang Yang,1 Hongyuan Zha5
 Shanghai Jiao Tong University 2East China Normal University 3IBM Research 4Moshanghua Tech 5Georgia Tech"
-475e16577be1bfc0dd1f74f67bb651abd6d63524,DAiSEE: Towards User Engagement Recognition in the Wild,"DAiSEE: Towards User Engagement Recognition in the Wild
-Abhay Gupta
-Microsoft
-Vineeth N Balasubramanian
-Indian Institution of Technology Hyderabad"
 4753a125469da7649e9f58fb0db781622dff41f8,Single-View Semantic Mesh Refinement,"Multi-View Stereo with Single-View Semantic Mesh Reﬁnement
 Andrea Romanoni Marco Ciccone
 Francesco Visin Matteo Matteucci
 {andrea.romanoni, marco.ciccone, francesco.visin,
 Politecnico di Milano, Italy"
-47022785c35735a242dbacd4f1f1bb73628493ea,Person Retrieval Based on Viewpoint Saliency Prior,"Journal of Computational Information Systems 9: 20 (2013) 8235–8242
-Available at http://www.Jofcis.com
-Person Retrieval Based on Viewpoint Saliency Prior
-Qingming LENG, Ruimin HU∗, Cuina JIAO, Chao LIANG, Zheng WANG
-National Engineering Research Center for Multimedia Software, School of Computer, Wuhan
-University, Wuhan 430079, China"
 47fc921add1421ff8adb730df7aa9e7f865bfdeb,Toward Practical Smile Detection,"Towards Practical Smile Detection
 Jacob Whitehill, Gwen Littlewort, Ian Fasel, Marian Bartlett, and Javier Movellan"
-47a2727bd60e43f3253247b6d6f63faf2b67c54b,Semi-supervised Vocabulary-Informed Learning,"Semi-supervised Vocabulary-informed Learning
-Yanwei Fu and Leonid Sigal
-Disney Research"
 47e8db3d9adb79a87c8c02b88f432f911eb45dc5,MAGMA: Multilevel Accelerated Gradient Mirror Descent Algorithm for Large-Scale Convex Composite Minimization,"MAGMA: Multi-level accelerated gradient mirror descent algorithm for
 large-scale convex composite minimization
 Vahan Hovhannisyan
@@ -3646,20 +3075,9 @@ School of Computer Science and Engineering, Kyungpook National University,
 Laboratoire MIA (Mathematiques, Image et Applications)- Universit´e de La
 Rochelle, 17000, France, {andrews.sobral,"
 47980c6e42f1a3381e6c5f3db7230e6a64c40218,Finding People in Images and Videos,"INSTITUTNATIONALPOLYTECHNIQUEDEGRENOBLENum´eroattribu´eparlabiblioth`equeTH`ESEpourobtenirlegradedeDOCTEURDEL’INSTITUTNATIONALPOLYTECHNIQUEDEGRENOBLESp´ecialit´e:Imagerie,VisionetRobotiquedanslecardedel’´EcoleDoctoraleMath´ematiques,SciencesetTechnologiedel’Informationpr´esent´eeetsoutenuepubliquementparNavneetDALALle17Juillet,2006FindingPeopleinImagesandVideosJURYM.JamesL.CROWLEYPr´esidentM.MartialHEBERTRapporteurM.LucVanGOOLRapporteurM.ShaiAVIDANExaminateurMme.CordeliaSCHMIDDirecteurdeth`eseM.WilliamJ.TRIGGSDirecteurdeth`eseTh`esepr´epar´eedanslelaboratoireGRAVIR–IMAGauseinduProjetLEAR,INRIARhˆone-Alpes655avenuedel’Europe,38334SaintIsmier,France."
-47d3b923730746bfaabaab29a35634c5f72c3f04,Real-Time Facial Expression Recognition App Development on Smart Phones,"Humaid Alshamsi.et.al. Int. Journal of Engineering Research and Application              www.ijera.com
-ISSN : 2248-9622, Vol. 7, Issue 7, ( Part -3) July 2017, pp.30-38
-RESEARCH ARTICLE
-OPEN ACCESS
-Real-Time Facial Expression Recognition App Development on
-Smart Phones
-Humaid Alshamsi, Veton Kupuska
-Electrical And Computer Engineering Department, Florida Institute Of Technology, Melbourne Fl,"
 47f2088afb616bde5468818e23d79e1ae5a562cd,Multi-view gender classification based on local Gabor binary mapping pattern and support vector machines,"Multi-view Gender Classiﬁcation based on Local Gabor Binary
 Mapping Pattern and Support Vector Machines
 Bin Xia, He Sun and Bao-Liang Lu∗ Senior Member, IEEE"
-47caa516511a111b9dfd04f0eae55c6568bddb6c,Joint Tensor Feature Analysis For Visual Object Recognition,"Joint Tensor Feature Analysis For Visual
-Object Recognition
-Wai Keung Wong, Zhihui Lai, Yong Xu, Member, IEEE, Jiajun Wen, and Chu Po Ho"
 470b89e2c5248eb58e09129aa9b4d8bc77497e7e,Cortical folding abnormalities in autism revealed by surface-based morphometry.,"The Journal of Neuroscience, October 24, 2007 • 27(43):11725–11735 • 11725
 Neurobiology of Disease
 Cortical Folding Abnormalities in Autism Revealed by
@@ -3779,10 +3197,6 @@ Appearance Models. A comparison approach.
 Drago(cid:1) Datcu
 Léon Rothkrantz"
 478261574ddc6cf297611000735aa9808f8f0030,ScanNet: Richly-Annotated 3D Reconstructions of Indoor Scenes,
-471befc1b5167fcfbf5280aa7f908eff0489c72b,Class-Specific Kernel-Discriminant Analysis for Face Verification,"Class-Speciﬁc Kernel-Discriminant
-Analysis for Face Veriﬁcation
-Georgios Goudelis, Stefanos Zafeiriou, Anastasios Tefas, Member, IEEE, and Ioannis Pitas, Fellow, IEEE
-lass problems ("
 47541d04ec24662c0be438531527323d983e958e,Affective Information Processing,Affective Information Processing
 47b34a8ad5100582aa7cbfd85df3ca7659adc392,Is this a wampimuk? Cross-modal mapping between distributional semantics and the visual world,"Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, pages 1403–1414,
 Baltimore, Maryland, USA, June 23-25 2014. c(cid:13)2014 Association for Computational Linguistics"
@@ -3820,9 +3234,6 @@ November 28, 2017"
 Xiaohan Fei
 Alex Wong
 Stefano Soatto"
-99b7ff97ad54308b816e47d9bbf6704b787b8f52,Causal flow,"IEEE TRANSACTIONS ON MULTIMEDIA, VOL. 14, NO. 3, JUNE 2012
-Causal Flow
-Yuya Yamashita, Tatsuya Harada, Member, IEEE, and Yasuo Kuniyoshi, Member, IEEE"
 998e829cc72080c88a780f322d6bf7ab78dbd743,Towards Real-Time Multiresolution Face/Head Detection,"´AAAAAAAAAAAAAAAAAAAAAAAA
 ´AAAAAAAAAAAAAAAAAAAAAAAA
 ART´ICULO
@@ -3835,9 +3246,6 @@ y Aplicaciones Num´ericas en Ingenier´ıa
 Ediﬁcio Central del Parque Cient´ıﬁco-Tecnol´ogico
 Campus Universitario de Taﬁra
 5017 Las Palmas - Espa˜na"
-99d3bc6d62675297693e5e57ff0770e7017f9637,Hierarchical Invariant Feature Learning with Marginalization for Person Re-Identification,"Hierarchical Invariant Feature Learning with
-Marginalization for Person Re-Identiﬁcation
-Rahul Rama Varior, Student Member, IEEE, Gang Wang, Member, IEEE"
 9974a806bb69ed26fb8cf49ebdd53d7756336eec,Object Recognition Using Multiresolution Trees,"Object recognition using Multiresolution trees
 Monica Bianchini, Marco Maggini, and Lorenzo Sarti
 DII - Universit`a degli Studi di Siena
@@ -3903,32 +3311,6 @@ Amira E. Youssef, Sherin F. Aly, Ahmed S. Ibrahim, and A. Lynn Abbott
 regarding
 emotion
 recognize"
-99cb716cd7687db8ef3d0403c85b1ab90869800f,FACE RECOGNITION UNDER POSE AND EXPRESIVITY VARIATION USING THERMAL AND VISIBLE IMAGES,"FACE RECOGNITION UNDER POSE AND EXPRESIVITY
-VARIATION USING THERMAL AND VISIBLE IMAGES
-Florin Marius Pop, Mihaela Gordan, Camelia Florea, Aurel Vlaicu
-Centre for Multimedia Technologies and Distance Education
-Technical University of Cluj-Napoca, Romania
-{Mihaela.Gordan, Camelia.Florea,"
-99c57ec53f2598d63c010f791adbca386b276919,Landmark-Guided Local Deep Neural Networks for Age and Gender Classification,"Hindawi
-Journal of Sensors
-Volume 2018, Article ID 5034684, 10 pages
-https://doi.org/10.1155/2018/5034684
-Research Article
-Landmark-Guided Local Deep Neural Networks for Age and
-Gender Classification
-Yungang Zhang 1 and Tianwei Xu2
-Department of Computer Science, Yunnan Normal University, Kunming, Yunnan 650500, China
-Graduate School, Yunnan Normal University, Kunming, Yunnan 650500, China
-Correspondence should be addressed to Yungang Zhang;
-Received 22 February 2018; Accepted 30 April 2018; Published 9 July 2018
-Academic Editor: Mucheol Kim
-Copyright © 2018 Yungang Zhang and Tianwei Xu. This is an open access article distributed under the Creative Commons
-Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work
-is properly cited.
-Many types of deep neural networks have been proposed to address the problem of human biometric identiﬁcation, especially in the
-reas of face detection and recognition. Local deep neural networks have been recently used in face-based age and gender
-lassiﬁcation, despite their improvement in performance, their costs on model training is rather expensive. In this paper, we
-propose to construct a local deep neural network for age and gender classiﬁcation. In our proposed model, local image patches"
 99e1ab1fb08af137cad6efbc0454c6e1e68dca51,3D human action recognition and motion analysis using selective representations,"D HUMAN ACTION RECOGNITION
 AND MOTION ANALYSIS USING
 SELECTIVE REPRESENTATIONS
@@ -3983,18 +3365,6 @@ Ronny Hug∗, Stefan Becker∗, Wolfgang H¨ubner∗ and Michael Arens∗"
 99227909e5733d76b0d50fc3fab975ab7a43fce3,A Cascaded Inception of Inception Network With Attention Modulated Feature Fusion for Human Pose Estimation,"A Cascaded Inception of Inception Network with Attention Modulated Feature
 Fusion for Human Pose Estimation
 Submission ID: 2065"
-99726ad232cef837f37914b63de70d8c5101f4e2,Facial Expression Recognition Using PCA & Distance Classifier,"International Journal of Scientific & Engineering Research, Volume 5, Issue 5, May-2014                                                                                                      570
-ISSN 2229-5518
-Facial Expression Recognition Using PCA & Distance Classifier
-AlpeshKumar Dauda*
-Dept. of Electronics & Telecomm. Engg.
-Ph.D Scholar,VSSUT
-BURLA, ODISHA, INDIA
-Nilamani Bhoi
-Reader in Dept. of Electronics & Telecomm. Engg.
-VEER SURENDRA SAI UNIVERSITY OF
-TECHNOLOGY
-BURLA, ODISHA, INDIA"
 998b7c8608fb9f80177ce54230761d8c3d82b2da,SHEF-Multimodal: Grounding Machine Translation on Images,"Proceedings of the First Conference on Machine Translation, Volume 2: Shared Task Papers, pages 660–665,
 Berlin, Germany, August 11-12, 2016. c(cid:13)2016 Association for Computational Linguistics"
 99246f998a684879038f39583bcf75b8f218e0a3,Object Detection for Autonomous Driving Using Deep Learning,"UNIVERSITAT POLITÈCNICA DE CATALUNYA
@@ -4164,9 +3534,6 @@ BSc(Biol), MSc(Biol), MSc(CompSc)
 A thesis submitted for the degree of Doctor of Philosophy at
 The University of Queensland in 2012
 School of Information Technology and Electrical Engineering"
-299eb74b2a553c6ff1e3d756a19cfe6ac4b133a0,Face recognition by independent component analysis,"Face Recognition by Independent
-Component Analysis
-Marian Stewart Bartlett, Member, IEEE, Javier R. Movellan, Member, IEEE, and Terrence J. Sejnowski, Fellow, IEEE"
 2914a20df10f3bb55c5d4764ece85101c1a3e5a8,User interest profiling using tracking-free coarse gaze estimation,"User Interest Proﬁling Using
 Tracking-free Coarse Gaze Estimation
 Federico Bartoli, Giuseppe Lisanti, Lorenzo Seidenari, Alberto Del Bimbo
@@ -4243,42 +3610,11 @@ Dr. Harald Scharfenberg
 Professor at FHD
 Thesis Supervisor
 Accepted by . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ."
-29b1a44d1e1ffa05c2bf7f4be931c5045f427718,ON GENERIC OBJECT RECOGNITION TECHNIQUES : CHALLENGES AND OPPORTUNITIES Prof,"International Journal of Advanced Research in Engineering and Technology
-(IJARET)
-Volume 6, Issue 12, Dec 2015, pp. 104-133, Article ID: IJARET_06_12_010
-Available online at
-http://www.iaeme.com/IJARET/issues.asp?JType=IJARET&VType=6&IType=12
-ISSN Print: 0976-6480 and ISSN Online: 0976-6499
-© IAEME Publication
-REVIEW ON GENERIC OBJECT
-RECOGNITION TECHNIQUES:
-CHALLENGES AND OPPORTUNITIES
-Prof. Deepika Shukla
-Comp. Science and Engineering Department,
-Institute of Technology, Nirma University, Ahmedabad, India
-Apurva Desai
-Department of Computer Science and Information Technology,
-VNSGU, Surat India"
 2926a7b4e6f92498236817300a253e8f3a88bd49,Neural Paraphrase Generation using Transfer Learning,"Proceedings of The 10th International Natural Language Generation conference, pages 257–261,
 Santiago de Compostela, Spain, September 4-7 2017. c(cid:13)2017 Association for Computational Linguistics"
 299af7d4fe6da8ac0b390e3ce45c48f7a8b5bb37,"Attribute And-Or Grammar for Joint Parsing of Human Attributes, Part and Pose.","Attribute And-Or Grammar for Joint Parsing of
 Human Attributes, Part and Pose
 Seyoung Park, Bruce Xiaohan Nie and Song-Chun Zhu"
-29619496c688f8400a90fef79b4fa756967ed0f7,Head Gesture Recognition: A Literature Review,"International Conference on Innovative Research in Engineering, Science, Management and Humanities (ICIRESMH-2017)
-t (IETE) Institution of Electronics and Telecommunication Engineers, Lodhi Road, Delhi, India
-on 19th February 2017
-ISBN: 978-81-932712-5-4
-Head Gesture Recognition: A Literature Review
-Er. Rushikesh T. Bankar
-Ph. D Scholar,
-Department of Electronics Engineering,
-G. H. Raisoni College of Engineering,
-Nagpur, India.
-Dr. Suresh S. Salankar
-Dean SAC & Professor,
-Department of E&TC Engineering,
-G. H. Raisoni College of Engineering,
-Nagpur, India."
 29756b6b16d7b06ea211f21cdaeacad94533e8b4,Thresholding Approach based on GPU for Facial Expression Recognition,"Thresholding Approach based on GPU for Facial
 Expression Recognition
 Jesús García-Ramírez1, J. Arturo Olvera-López1, Ivan Olmos-Pineda1, Georgina
@@ -4320,11 +3656,6 @@ Department of Electrical and Electronic Engineering, Imperial College, South Ken
 {oscar.deniz, ismael.serrano,
 Keywords:
 ction recognition, violence detection, ﬁght detection"
-29c23c7d5d70aef54168ba20dccdd14f570901a3,Duplicate Discovery on 2 Billion Internet Images,"Duplicate Discovery on 2 Billion Internet Images
-Xin-Jing Wang, Lei Zhang
-Microsoft Research Asia
-5 Danling Street, Beijing, China
-fxjwang,"
 299c14458e13eb290534eb4484ad910ea0e828a7,Evaluation of the most appropriate Kernel Function for the Purpose of Feature Extraction in Face Recognition in video surveillance systems,"Evaluation of the most appropriate Kernel Function for the
 Purpose of Feature Extraction in Face Recognition in video
 surveillance systems
@@ -4421,12 +3752,6 @@ Department of Computer Science, University of California, Irvine"
 296502c6370cabd2b7e38e71cfc757d2e5fa2199,Detection of Deep Network Generated Images Using Disparities in Color Components,"Detection of Deep Network Generated Images
 Using Disparities in Color Components
 Haodong Li, Bin Li, Shunquan Tan, Jiwu Huang"
-294bd7eb5dc24052237669cdd7b4675144e22306,Automatic Face Annotation,"International Journal of Science and Research (IJSR)
-ISSN (Online): 2319-7064
-Index Copernicus Value (2013): 6.14 | Impact Factor (2013): 4.438
-Automatic Face Annotation
-Ashna Shajahan
-M.Tech Student, Dept. of Computer Science & Engineering, Mount Zion College of Engineering, Pathanamthitta, Kerala, India"
 29cf7937a1c1848c24b294569d50a2f7122de51b,MarioQA: Answering Questions by Watching Gameplay Videos,"MarioQA: Answering Questions by Watching Gameplay Videos
 Jonghwan Mun*
 Bohyung Han
@@ -4441,9 +3766,6 @@ Real-time reliability measure-driven multi-
 hypothesis tracking using 2D and 3D features
 Marcos D Zúñiga1*, François Brémond2 and Monique Thonnat2
 Open Access"
-299ca90452aa8a7dd517de3ff3c9bf224d5100c7,Dynamic Scene Classification Using Redundant Spatial Scenelets,"Dynamic Scene Classiﬁcation Using Redundant
-Spatial Scenelets
-Liang Du and Haibin Ling, Member, IEEE"
 2921719b57544cfe5d0a1614d5ae81710ba804fa,Face Recognition Enhancement Based on Image File Formats and Wavelet,"Face Recognition Enhancement Based on Image
 File Formats and Wavelet De-noising
 Isra’a Abdul-Ameer Abdul-Jabbar, Jieqing Tan, and Zhengfeng Hou"
@@ -4466,16 +3788,6 @@ work in other works.
 Contact
 https://ghassanalregib.com/
 http://cantemel.com/"
-29bcf87f48a5b4e2f06f20761cbc376d56df5f13,Face Recognition using PCA and SVM with Surf Technique,"Face Recognition using PCA and SVM with Surf
-International Journal of Computer Applications (0975 – 8887)
-Volume 129 – No.4, November2015
-Technique
-Shilpa Sharma
-Indo Global College of Engineering
-Abhipur, Mohali, India
-Kumud Sachdeva
-Asstt.Prof. Indo Global  College of Engineering
-Abhipur, Mohali, India"
 292c4bd6fa516393e9c8c5f1dae5afe0bb0ece35,IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 1 Interacting Multiview Tracker,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 38, NO. 5, MAY 2016
 Interacting Multiview Tracker
 Ju Hong Yoon, Ming-Hsuan Yang, Senior Member, IEEE, and Kuk-Jin Yoon"
@@ -4552,8 +3864,6 @@ Department of Electrical and Computer Engineering
 American University of Beirut
 Beirut, Lebanon
 Email:"
-9b95153e4d3972d59fabef0fddce9b7207836b1b,Nonlinear Discrete Hashing,"Nonlinear Discrete Hashing
-Zhixiang Chen, Jiwen Lu, Senior Member, IEEE, Jianjiang Feng, Member, IEEE, and Jie Zhou, Senior Member, IEEE"
 9bf6fbccfdf013cfd076f9357a05fb00b50735ee,JAR-Aibo: A Multi-view Dataset for Evaluation of Model-Free Action Recognition Systems,"JAR-Aibo: A Multi-View Dataset for Evaluation
 of Model-Free Action Recognition Systems
 Marco K¨orner and Joachim Denzler
@@ -4630,10 +3940,6 @@ Baidu.com, Inc"
 9bcfadd22b2c84a717c56a2725971b6d49d3a804,How to Detect a Loss of Attention in a Tutoring System using Facial Expressions and Gaze Direction,"How to Detect a Loss of Attention in a Tutoring System
 using Facial Expressions and Gaze Direction
 Mark ter Maat"
-9b693c71cc89e2d2f41b6ab5cc0f62ca59c6d128,Recognizing Unseen Attribute-Object Pair with Generative Model,"Recognizing Unseen Attribute-Object Pair with Generative Model
-Zhixiong Nan1,2∗ , Yang Liu2∗, Nanning Zheng1, and Song-Chun Zhu2
-Xi’an Jiaotong University, China
-University of California, Los Angeles, USA"
 9b678aa28facf4f90081d41c2c484c6addddb86d,Fully Convolutional Attention Networks for Fine-Grained Recognition,"Fully Convolutional Attention Networks for Fine-Grained Recognition
 Xiao Liu, Tian Xia, Jiang Wang, Yi Yang, Feng Zhou and Yuanqing Lin
 Baidu Research
@@ -4642,16 +3948,6 @@ Baidu Research
 9bac481dc4171aa2d847feac546c9f7299cc5aa0,Matrix Product State for Higher-Order Tensor Compression and Classification,"Matrix Product State for Higher-Order Tensor
 Compression and Classiﬁcation
 Johann A. Bengua1, Ho N. Phien1, Hoang D. Tuan1 and Minh N. Do2"
-9bcfa6d23ea628ccfabf6900ef05437e7cecb1c6,A Hybrid Approach for Secure Biometric Authentication Using Fusion of Iris and Ear,"Volume 5, Issue 8, August 2015                                          ISSN: 2277 128X
-International Journal of Advanced Research in
-Computer Science and Software Engineering
-Research Paper
-Available online at: www.ijarcsse.com
-A Hybrid Approach for Secure Biometric Authentication Using
-Fusion of Iris and Ear
-Pamalpreet Kaur*, Er. Nirvair Neeru
-CSE Deptt. Punjabi University,
-Patiala, India"
 9b7974d9ad19bb4ba1ea147c55e629ad7927c5d7,Faical Expression Recognition by Combining Texture and Geometrical Features,"Faical Expression Recognition by Combining
 Texture and Geometrical Features
 Renjie Liu, Ruofei Du, Bao-Liang Lu*"
@@ -4692,17 +3988,6 @@ Reasoning with shapes: proﬁting cognitive
 susceptibilities to infer linear mapping
 transformations between shapes
 Vahid Jalili"
-9b666e20f570387214926eee542965f3fbe3cfce,Side Information for Face Completion: a Robust PCA Approach,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015
-Side Information for Face Completion: a Robust
-PCA Approach
-Niannan Xue, Student Member, IEEE, Jiankang Deng, Student Member,IEEE,
-Shiyang Cheng, Student Member,IEEE, Yannis Panagakis, Member,IEEE,
-nd Stefanos Zafeiriou, Member, IEEE"
-9b4e90866c1f096a57383fb7320ac9d516a2f88d,Towards lightweight convolutional neural networks for object detection,"TOWARDS LIGHTWEIGHT CONVOLUTIONAL NEURAL
-NETWORKS FOR OBJECT DETECTION
-Dmitriy Anisimov, Tatiana Khanova
-Intel
-Nizhny Novgorod, Russia"
 9b7c6ef333c6e64f2dfa97a1a3614d0775d81a8a,A New Evaluation Protocol and Benchmarking Results for Extendable Cross-media Retrieval,"A New Evaluation Protocol and Benchmarking
 Results for Extendable Cross-media Retrieval
 Ruoyu Liu, Yao Zhao, Liang Zheng, Shikui Wei, and Yi Yang"
@@ -4728,13 +4013,6 @@ Xiaofeng Cao, Ivor W. Tsang, Jianliang Xu, Zenglin Shi, Guandong Xu"
 Sang Phan, Duy-Dinh Le, Shin’ichi Satoh
 National Institute of Informatics
 -1-2 Hitotsubashi, Chiyoda-ku, Tokyo, Japan 101-8430"
-13f07d51c073964d11f9af6463fe3ffe5475c393,"Part-Based Pedestrian Detection and Feature-Based Tracking for Driver Assistance: Real-Time, Robust Algorithms, and Evaluation","This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination.
-Part-Based Pedestrian Detection and Feature-Based
-Tracking for Driver Assistance: Real-Time,
-Robust Algorithms, and Evaluation
-Antonio Prioletti, Student Member, IEEE, Andreas Møgelmose, Student Member, IEEE, Paolo Grisleri,
-Mohan Manubhai Trivedi, Fellow, IEEE, Alberto Broggi, Senior Member, IEEE, and
-Thomas B. Moeslund, Member, IEEE"
 13b8d657f0f9a0178339570bdc153bfd10a81300,Harvesting large-scale weakly-tagged image databases from the web,"Harvesting Large-Scale Weakly-Tagged Image Databases from the Web
 Jianping Fan1, Yi Shen1, Ning Zhou1, Yuli Gao2
 Department of Computer Science, UNC-Charlotte, NC28223, USA
@@ -4759,13 +4037,6 @@ Laboratoire d’Informatique, Polytech’Tours, Universite´ Franc¸ois-Rabelais
 e-mail: {sebastien.aupetit, nicolas.monmarche,
 (Received 16 July 2005; in ﬁnal form 22 December 2005; published online 28 February 2006)
 In this work we consider the problem of Hidden Markov Models (HMM) training. This"
-130bf256f4cc3dded4fb701f74f6a34992be639b,A Robust Multiwavelet-Based Watermarking Scheme for Copyright Protection of Digital Images Using Human Visual System,"The International Arab Journal of Information Technology, Vol. 10, No. 6, November 2013                                                               527
-A Robust Multiwavelet-Based Watermarking
-Scheme for Copyright Protection of Digital
-Images using Human Visual System
-Padmanabhareddy Vundela1 and Varadarajan Sourirajan2
-Department of Information Technology, Vardhaman College of Engineering, India
-Department of Electrical and Electronic Engineering, S.V. University College of Engineering, India"
 138e3f6bc164a7b26a0ff283379a325afc0fee14,Geo-Supervised Visual Depth Prediction,"Geo-Supervised Visual Depth Prediction
 Xiaohan Fei
 Alex Wong
@@ -4785,11 +4056,6 @@ Tübingen, Germany"
 139763a0b2e78b63b245a456f2b9dbde2d1d573c,"RPRG: Toward Real-time Robotic Perception, Reasoning and Grasping with One Multi-task Convolutional Neural Network","RPRG: Toward Real-time Robotic Perception, Reasoning and Grasping
 with One Multi-task Convolutional Neural Network
 Hanbo Zhang, Xuguang Lan, Lipeng Wan, Chenjie Yang, Xinwen Zhou, and Nanning Zheng"
-134db6ca13f808a848321d3998e4fe4cdc52fbc2,Dynamics of facial expression: recognition of facial actions and their temporal segments from face profile image sequences,"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 36, NO. 2, APRIL 2006
-Dynamics of Facial Expression: Recognition of
-Facial Actions and Their Temporal Segments
-From Face Proﬁle Image Sequences
-Maja Pantic, Member, IEEE, and Ioannis Patras, Member, IEEE"
 135fcdab631ab30ae837a743040f1c8751268e41,DeepStyle: Multimodal Search Engine for Fashion and Interior Design,"SUBMITTED TO IEEE TRANSACTIONS ON MULTIMEDIA
 DeepStyle: Multimodal Search Engine
 for Fashion and Interior Design
@@ -4820,11 +4086,6 @@ is an emerging technology that addresses the automated identiﬁcation of
 individuals, based on their physiological and behavioral traits. The main advantage of
 iometric methods is the ability to recognize, which is made by means of a physical feature or
 unique pattern (Jain et al. (2008)). With these methods and individual can hardly be victim"
-13caf4d2e0a4b6fcfcd4b9e8e2341b8ebd38258d,Joint Learning of Siamese CNNs and Temporally Constrained Metrics for Tracklet Association,"Joint Learning of Siamese CNNs and Temporally
-Constrained Metrics for Tracklet Association
-Bing Wang, Student Member, IEEE, Li Wang, Member, IEEE, Bing Shuai, Student Member, IEEE,
-Zhen Zuo, Student Member, IEEE, Ting Liu, Student Member, IEEE, Kap Luk Chan, Member, IEEE, and
-Gang Wang, Member, IEEE"
 135fe2a0a0e6b726e5d81299edad4b3ce39d6614,Multichannel-Kernel Canonical Correlation Analysis for Cross-View Person Reidentification,"This is a pre-print version, the ﬁnal version of the manuscript with more experiments can be found at:
 https://doi.org/10.1145/3038916
 Multi Channel-Kernel Canonical Correlation
@@ -4850,10 +4111,6 @@ FPCEUP, Porto, Portugal.
 ESTSPIPP, Porto, Portugal.
 Institution where the study was elaborated: Faculty of Psychology and Educational Sciences, Porto University, Portugal.
 Received: 11/6/2012 – Accepted: 2/14/2013"
-133f01aec1534604d184d56de866a4bd531dac87,Effective Unconstrained Face Recognition by Combining Multiple Descriptors and Learned Background Statistics,"Effective Unconstrained Face Recognition by
-Combining Multiple Descriptors and Learned
-Background Statistics
-Lior Wolf, Member, IEEE, Tal Hassner, and Yaniv Taigman"
 13ae3c8afef5a0d6f4c9e684da9fc1fa96caaeb6,Online Anomaly Detection in Crowd Scenes via Structure Analysis,"Online Anomaly Detection in Crowd Scenes
 via Structure Analysis
 Yuan Yuan, Senior Member, IEEE, Jianwu Fang, and Qi Wang"
@@ -5020,15 +4277,6 @@ University of California, Berkeley∗ and Microsoft Research†
 yeshen, jfgao, jingjl,"
 13b2e01030ae41983003e3ae53b5bb3ed3e764f0,Detection-Tracking for Efficient Person Analysis: The DetTA Pipeline,"Detection-Tracking for Efﬁcient Person Analysis: The DetTA Pipeline
 Stefan Breuers1, Lucas Beyer1, Umer Raﬁ1, Bastian Leibe1"
-132cc530230cb869318b0a9d81a717077895db38,Emancipation of Upper Bound Greedy Algorithm in Detection of Nodes in Social Networks,"Emancipation of Upper Bound Greedy Algorithm in Detection
-© 2018 IJSRSET | Volume 4 | Issue 1 | Print ISSN: 2395-1990 | Online ISSN : 2394-4099
-Themed Section : Engineering and Technology
-of Nodes in Social Networks
-Shaik Aasha1, T. Nagini2
-M.Tech Scholar Department of CS, St.Mary’s Group of Institutions Guntur Chebrolu(V&M),Guntur(Dt),
-Andhra Pradesh, India
-Assistant Professor Department of CSE, St.Mary’s Group of Institutions Guntur Chebrolu(V&M),Guntur(Dt),
-Andhra Pradesh, India"
 13f03aab62fc29748114a0219426613cf3ba76ae,MORPH-II: Feature Vector Documentation,"MORPH-II: Feature Vector Documentation
 Troy P. Kling
 NSF-REU Site at UNC Wilmington, Summer 2017
@@ -5061,19 +4309,6 @@ Priusha Narwariya
 Dept. of CSE
 ITM Universe
 Gwalior"
-138cef9080f213f1ffc7900ade7c0e85ee8e7bf2,Bloodhound : Kinship Through Imaging,"ISSN (Online) : 2319 – 8753
-ISSN (Print)    : 2347 - 6710
-International Journal of Innovative Research in Science, Engineering and Technology
-An ISO 3297: 2007 Certified Organization,
-Volume 3, Special Issue 5, April 2014
-Two days National Conference – VISHWATECH 2014
-On 21st & 22nd February, Organized by
-Department of CIVIL, CE, ETC, MECHNICAL, MECHNICAL SAND, IT Engg. Of Vishwabharati Academy’s College of engineering,
-Ahmednagar, Maharastra, India
-Bloodhound : Kinship Through Imaging
-Chaitali Deshmukh, Prof. S.D.Jondhale
-ME student, Department of Computer Engineering, SVIT, Chincholi, Nashik, India.
-Professor, Computer Engineering Department, SVIT, Chincholi, Nashik, India."
 13f9922632ff5311046229b849615fcd2f5d0c06,On Multi-scale differential features for face recognition,"On Multi-scale differential features for face recognition
 Center for Intelligent Information Retrieval
 S. Ravela
@@ -5145,21 +4380,12 @@ Cornell Tech
 Gunnar R¨atsch
 Computational Biology Program, Sloan Kettering Institute
 275 York Avenue, New York, USA"
-60cc2e8abc20c145727e7089c55bdba5722436d0,Higher Order Matching for Consistent Multiple Target Tracking,"Higher Order Matching for Consistent Multiple Target Tracking
-Chetan Arora
-Amir Globerson
-School of Computer Science and Engineering
-The Hebrew University
-http://www.cs.huji.ac.il/˜chetan/"
 60ffc8db53b02e95d852f5a06f97686486f72195,Video matching using DC-image and local features,"Video Matching Using DC-image and Local
 Features
 Saddam Bekhet, Amr Ahmed and Andrew Hunter"
 60cdcf75e97e88638ec973f468598ae7f75c59b4,Face Annotation Using Transductive Kernel Fisher Discriminant,"Face Annotation Using Transductive
 Kernel Fisher Discriminant
 Jianke Zhu, Steven C.H. Hoi, and Michael R. Lyu"
-6047e9af00dcffbd2effbfa600735eb111f7de65,A Discriminative Representation of Convolutional Features for Indoor Scene Recognition,"A Discriminative Representation of Convolutional
-Features for Indoor Scene Recognition
-S. H. Khan, M. Hayat, M. Bennamoun, Member, IEEE, R. Togneri, and F. Sohel, Senior Member, IEEE"
 60d75d32d345c519fa5c0d8d6b6eb62e633a8d13,Person reidentification by semisupervised dictionary rectification learning with retraining module,"Downloaded From: https://www.spiedigitallibrary.org/journals/Journal-of-Electronic-Imaging on 9/13/2018
 Terms of Use: https://www.spiedigitallibrary.org/terms-of-use
 PersonreidentificationbysemisuperviseddictionaryrectificationlearningwithretrainingmoduleHongyuanWangZongyuanDingJiZhangSuolanLiuTongguangNiFuhuaChenHongyuanWang,ZongyuanDing,JiZhang,SuolanLiu,TongguangNi,FuhuaChen,“Personreidentificationbysemisuperviseddictionaryrectificationlearningwithretrainingmodule,”J.Electron.Imaging27(4),043043(2018),doi:10.1117/1.JEI.27.4.043043."
@@ -5241,13 +4467,6 @@ segmentation of medical images [17], [18]. In conventional Sparse Representation
 Experience-Based Classiﬁcation for
 Robot Perception
 Jeffrey Hawke†, Corina Gur˘au†, Chi Hay Tong and Ingmar Posner"
-601834a4150e9af028df90535ab61d812c45082c,A short review and primer on using video for psychophysiological observations in human-computer interaction applications,"A short review and primer on using video for
-psychophysiological observations in
-human-computer interaction applications
-Teppo Valtonen1
-Quantiﬁed Employee unit, Finnish Institute of Occupational Health,
-teppo. valtonen fi,
-POBox 40, 00250, Helsinki, Finland"
 6025f0761024006e0ea5782a7cea29ed69231fbf,Neural Mechanisms of Qigong Sensory Training Massage for Children With Autism Spectrum Disorder: A Feasibility Study,"Original Article
 Neural Mechanisms of Qigong Sensory
 Training Massage for Children With Autism
@@ -5293,18 +4512,6 @@ Moulay Slimane, Beni Mellal
 Arne Schumann, Eduardo Monari
 Fraunhofer Institute for Optronics, System Technologies and Image Exploitation
 {arne.schumann,"
-607850dc8e640c25f027f2eee202dee5605cf27c,A Survey on Face Detection and Recognition Techniques in Different Application Domain,"I.J. Modern Education and Computer Science, 2014, 8, 34-44
-Published Online August 2014 in MECS (http://www.mecs-press.org/)
-DOI: 10.5815/ijmecs.2014.08.05
-A Survey on Face Detection and Recognition
-Techniques in Different Application Domain
-Subrat Kumar Rath, Siddharth Swarup Rautaray
-School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India
-related
-technology
-recognition,
-to  biometric  science
-the  popularity  and"
 60bc358296ae11ac8f11286bba0a49ac7e797d26,Diverse Image-to-Image Translation via Disentangled Representations,"Diverse Image-to-Image Translation via
 Disentangled Representations
 Hsin-Ying Lee(cid:63)1, Hung-Yu Tseng(cid:63)1, Jia-Bin Huang2, Maneesh Singh3,
@@ -5322,14 +4529,6 @@ Output
 Fig. 1: Unpaired diverse image-to-image translation. (Lef t) Our model
 learns to perform diverse translation between two collections of images without
 ligned training pairs. (Right) Example-guided translation."
-60ec284f67c1012419e5dea508d1bae4bc144bb2,Curvelet Based Multiresolution Analysis of Face Images for Recognition using Robust Local Binary Pattern Descriptor,"Proc. of Int. Conf. on  Recent Trends in Signal Processing, Image Processing and VLSI, ICrtSIV
-Curvelet Based Multiresolution Analysis of Face
-Images for Recognition using Robust Local Binary
-Pattern Descriptor
-Nagaraja S. and Prabhakar C.J
-Department of P.G. Studies and Research in Computer Science,
-Kuvempu University, Karnataka, India
-Email: { nagarajas27, psajjan"
 608c5103ad8e745b98dfe92ef33b66b93f01b051,Amélioration de performance de la navigation basée vision pour la robotique autonome : une approche par couplage vision/commande. (Performance improvment of vision-based navigation for autonomous robotics : a vision and control coupling approach),"Amélioration de performance de la navigation basée
 vision pour la robotique autonome : une approche par
 ouplage vision/commande
@@ -5404,9 +4603,6 @@ Signals and systems group, Faculty of Electrical Engineering, Mathematics and Co
 G. M. Beumer, and R.N.J. Veldhuis
 Twente, Enschede, The Netherlands
 Email:"
-60e2b9b2e0db3089237d0208f57b22a3aac932c1,Frankenstein: Learning Deep Face Representations Using Small Data,"Frankenstein: Learning Deep Face Representations
-using Small Data
-Guosheng Hu, Member, IEEE, Xiaojiang Peng, Yongxin Yang, Timothy M. Hospedales, and Jakob Verbeek"
 602ff4fd0f5bd10c9fb971ecd2317e542f070883,Object Detection from the Satellite Images using Divide and Conquer Model,"SSRG International Journal of Computer Science and Engineering (SSRG-IJCSE) – volume1 issue10 Dec 2014
 Object Detection from the Satellite Images
 using Divide and Conquer Model
@@ -5527,9 +4723,6 @@ norm as a convex surrogate of the rank operator. However, all singular values ar
 thus the rank may not be well approximated in practical problems. In this paper, we propose using a log-determinant (LogDet)
 function as a smooth and closer, though nonconvex, approximation to rank for obtaining a low-rank representation in subspace
 lustering. Augmented Lagrange multipliers strategy is applied to iteratively optimize the LogDet-based nonconvex objective"
-60f7de07de4d090990120483bd5407369b29a120,ℓ₁-Norm Heteroscedastic Discriminant Analysis Under Mixture of Gaussian Distributions.,"L1-Norm Heteroscedastic Discriminant Analysis
-under Mixture of Gaussian Distributions
-Wenming Zheng, Member, IEEE, Cheng Lu, Zhouchen Lin, Fellow, IEEE, Tong Zhang, Zhen Cui, Wankou Yang"
 60efdb2e204b2be6701a8e168983fa666feac1be,Transferring Deep Object and Scene Representations for Event Recognition in Still Images,"Int J Comput Vis
 DOI 10.1007/s11263-017-1043-5
 Transferring Deep Object and Scene Representations for Event
@@ -5538,9 +4731,6 @@ Limin Wang1
 · Zhe Wang2 · Yu Qiao3 · Luc Van Gool1
 Received: 31 March 2016 / Accepted: 1 September 2017
 © Springer Science+Business Media, LLC 2017"
-60b66ec51ddadd132453f700d1781e8e7a8f78c8,Self-Validated Labeling of Markov Random Fields for Image Segmentation,"Self-Validated Labeling of Markov Random
-Fields for Image Segmentation
-Wei Feng, Jiaya Jia, Member, IEEE, and Zhi-Qiang Liu"
 77db171a523fc3d08c91cea94c9562f3edce56e1,Gauss-Laguerre wavelet textural feature fusion with geometrical information for facial expression identification,"Poursaberi et al. EURASIP Journal on Image and Video Processing 2012, 2012:17
 http://jivp.eurasipjournals.com/content/2012/1/17
 R ES EAR CH
@@ -5665,16 +4855,8 @@ Dayananda Sagar College of Engineering, Bangalore, India.
 Sai-Tektronix Pvt. Ltd., Bangalore, India.
 University Visvesvaraya College of Engineering, Bangalore, India.
 dK.S. Institute of Technology, Bangalore, India."
-7711a7404f1f1ac3a0107203936e6332f50ac30c,Action Classification and Highlighting in Videos,"Action Classiﬁcation and Highlighting in Videos
-Atousa Torabi
-Disney Research Pittsburgh
-Leonid Sigal
-Disney Research Pittsburgh"
 77c7f5c5852c189b59c34ebbbbec03e5e4060428,Talking to Robots : Learning to Ground Human Language in Perception and Execution,"(cid:13)Copyright 2014
 Cynthia Matuszek"
-7754b708d6258fb8279aa5667ce805e9f925dfd0,Facial Action Unit Recognition by Exploiting Their Dynamic and Semantic Relationships,"Facial Action Unit Recognition by Exploiting
-Their Dynamic and Semantic Relationships
-Yan Tong, Student Member, IEEE, Wenhui Liao, Member, IEEE, and Qiang Ji, Senior Member, IEEE"
 77acb8847a76bfcc925f45387fb7abd4f2bd38ac,A novel polar-based human face recognition computational model.,"Novel polar-based human face recognition computational model
 Brazilian Journal of Medical and Biological Research (2009) 42: 637-646
 ISSN 0100-879X
@@ -5776,15 +4958,6 @@ Selection of our books indexed in the Book Citation Index
 in Web of Science™ Core Collection (BKCI)
 Interested in publishing with us?
 Contact"
-778952cc94d5baa5132ffbe2cf342f80032f5f73,Comparative Analysis of Techniques for the Recognition of Stabbed Wound and Accidental Wound Patterns,"International Journal of Computer Applications (0975 – 8887)
-Volume 182 – No. 13, September 2018
-Comparative Analysis of Techniques for the Recognition
-of Stabbed Wound and Accidental Wound Patterns
-Dayanand G. Savakar
-Department of Computer Science
-Rani Channamma University, Belagavi
-INDIA
-schemas  of"
 778c9f88839eb26129427e1b8633caa4bd4d275e,Pose pooling kernels for sub-category recognition,"Pose Pooling Kernels for Sub-category Recognition
 Ning Zhang
 ICSI & UC Berkeley
@@ -5799,10 +4972,6 @@ Judy Hoffman
 Li Fei-Fei
 CS Department Stanford University
 {tgebru, jhoffman,"
-772d15efe06d741b4ab7c5524c5384406731a3f7,Random Sampling and Locality Constraint for Fast Face Sketch Synthesis,"> A SUBMISSION TO IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS<
-Random Sampling and Locality Constraint for Fast
-Face Sketch Synthesis
-Nannan Wang, Member, IEEE, and Xinbo Gao, Senior Member, IEEE, and Jie Li"
 77d0c4ed1c2d971b3e81fe7919be7a5a19309f40,Deep Generative Modeling of LiDAR Data,"Deep Generative Modeling of LiDAR Data
 Lucas Caccia1,2, Herke van Hoof1,4, Aaron Courville2,3, Joelle Pineau1,2,3"
 7789252476073a77e80fb0668eecf94a99b81d8d,Fast Landmark Localization With 3D Component Reconstruction and CNN for Cross-Pose Recognition,"Fast Landmark Localization
@@ -5866,10 +5035,6 @@ Department of Psychology, Faculty of Humanities and Social Sciences,
 University of Zagreb, Croatia
 Ana Marija Španić
 Child Protection Center of Zagreb, Zagreb, Croatia"
-7789a5d87884f8bafec8a82085292e87d4e2866f,A Unified Tensor-based Active Appearance Face Model,"A Uniﬁed Tensor-based Active Appearance Face
-Model
-Zhen-Hua Feng, Member, IEEE, Josef Kittler, Life Member, IEEE, William Christmas, and Xiao-Jun Wu,
-Member, IEEE"
 776b77306bdb852c89a22ba142fb57c8e8bb7bb5,Efficient On-Board Stereo Vision Pose Estimation,"Ef‌f‌icient On-Board Stereo Vision
 Pose Estimation(cid:2)
 Angel D. Sappa1, Fadi Dornaika2, David Ger´onimo1, and Antonio L´opez1
@@ -5887,17 +5052,6 @@ Zhiqiang Zhang2 Gang Yu
 Jian Sun
 Megvii Inc. (Face++), {chenyilun, wangzhicheng, pyx, zhangzhiqiang, yugang,
 Tsinghua University 2HuaZhong University of Science and Technology"
-9a2ed8abaa17834cb8f227a9353c8cfed3a367cd,A Method of Detecting Abnormal Crowd Behavior Events Applied in Air Patrol Robot,"A Method of Detecting Abnormal Crowd Behavior Events Applied in Air Patrol Robot
-School of Electrical and Electronic Engineering ,Shanghai Institute of Technology, Shanghai, China
-Huailin Zhao
-School of Electrical and Electronic Engineering ,Shanghai Institute of Technology, Shanghai, China
-Shunzhou Wang
-School of Electrical and Electronic Engineering ,Shanghai Institute of Technology, Shanghai, China
-Shifang Xu
-School of Computer Science and Information Engineering ,Shanghai Institute of Technology, Shanghai, China
-Yani Zhang
-Masanori Sugisaka
-Alife Robotics Corporation LTD, Oita, Japan"
 9a03b7b71a82fc2c86b3b4cbec802dfc16978486,One-Shot Observation Learning,"One-Shot Observation Learning
 Leo Pauly, Wisdom C. Agboh, Mohamed Abdellatif, David C. Hogg, Raul Fuentes"
 9a1a9dd3c471bba17e5ce80a53e52fcaaad4373e,Automatic Recognition of Spontaneous Facial Actions,"Automatic Recognition of Spontaneous Facial
@@ -5937,16 +5091,6 @@ Support Vector Machines
 Porawat Visutsak
 Department of Information Technology, Faculty of Industrial Technology and Management,
 King Mongkut’s University of Technology North Bangkok,"
-9abc9e3cadbec9139b39dfddb0de6c08b7aaf2d0,Pain Intensity Evaluation through Facial Action Units,"Pain Intensity Evaluation Through Facial Action
-Units
-Zuhair Zafar
-Dept. of Electrical Engineering, SBASSE,
-Lahore University of Management Sciences,
-Lahore, Pakistan
-Nadeem Ahmad Khan
-Dept. of Electrical Engineering, SBASSE,
-Lahore University of Management Sciences,
-Lahore, Pakistan"
 9a08459b0cb133f0f4352c58225446f9dc95ecc4,Metadata of the chapter that will be visualized in SpringerLink,"Metadata of the chapter that will be visualized in
 SpringerLink
 Book Title
@@ -6084,23 +5228,6 @@ Vergara, Diego∗1, Hern´andez, Sergio∗2, Valdenegro-Toro, Mat´ıas∗∗3 a
 Laboratorio de Procesamiento de Informaci´on Geoespacial, Universidad Cat´olica del Maule, Chile.
 German Research Centre for Artiﬁcial Intelligence, Bremen, Germany.
 Email:"
-0c2c53d71942ad3171b693f565812f1db43215e0,Descriptive visual words and visual phrases for image applications,"Descriptive Visual Words and Visual Phrases for Image
-Shiliang Zhang1, Qi Tian2, Gang Hua3, Qingming Huang4, Shipeng Li2
-Applications
-Key Lab of Intelli. Info.
-Process., Inst. of Comput.
-Tech., CAS, Beijing 100080,
-China
-Microsoft Research Asia,
-Beijing 100080, China
-Microsoft Live Labs
-Research, Redmond, WA
-78052, U.S.A.
-Graduate University of
-Chinese Academy of
-Sciences, Beijing 100049,
-China
-{slzhang, {qitian, ganghua,"
 0cd98be65a1a645f3c9618d9920be3a3dfc77574,Just-in-Time Reconstruction: Inpainting Sparse Maps Using Single View Depth Predictors as Priors,"Inpainting Sparse Maps using Single View Depth Predictors as Priors
 Just-in-Time Reconstruction:
 Chamara Saroj Weerasekera1, Thanuja Dharmasiri2, Ravi Garg1, Tom Drummond2 and Ian Reid1"
@@ -6118,41 +5245,12 @@ EURECOM Institute
 http:www.eurecom.fr~marchand
 To be presented in the
 nd Int. Conf. on Audio- and Video-based Biometric Person Authentication"
-0c1d40de56698e672d3906b96f47ae1361fc3912,Face Recognition Using Kernel PrincipalComponent Analysis,"Advances in Vision Computing: An International Journal (AVC) Vol.1, No.1, March 2014
-Face Recognition Using Kernel
-PrincipalComponent Analysis
-Jayanthi T and 2Dr. Aji S
-Assistant Professor,Department of Computer Applications,
-Mohandas College of Engineering and Technology, Anad, Nedumangad
-Thiruvananthapuram, India
-Assistant Professor,Department of Computer Science,University of Kerala
-Kariyavattom,Thiruvananthapuram, India"
 0c95ff762bdf6a20609f49f1eb5248de3f748866,Fine-Grained Walking Activity Recognition via Driving Recorder Dataset,"Fine-grained Walking Activity Recognition
 via Driving Recorder Dataset
 Hirokatsu Kataoka (AIST), Yoshimitsu Aoki (Keio Univ.), Yutaka Satoh (AIST)
 Shoko Oikawa (NTSEL), Yasuhiro Matsui (NTSEL)
 Email:
 http://hirokatsukataoka.net/"
-0c1d5801f2b86afa969524dc74708a78450300d9,2 : Conditional Random Fields,"0-708: Probabilistic Graphical Models 10-708, Spring 2014
-2 : Conditional Random Fields
-Lecturer: Eric P. Xing
-Scribes: Qin Gao, Siheng Chen
-Hidden Markov Model
-.1 General parametric form
-In hidden Markov model (HMM), we have three sets of parameters,
-t = 1|yi
-transition probability matrix A : p(yj
-initialprobabilities : p(y1) ∼ Multinomial(π1, π2, ..., πM ),
-emission probabilities : p(xt|yi
-t) ∼ Multinomial(bi,1, bi,2, ..., bi,K).
-t−1 = 1) = ai,j,
-.2 Inference
-The inference can be done with forward algorithm which computes αk
-) recursively by
-t ≡ µt−1→t(k) = P (x1, ..., xt−1, xt, yk
-nd the backward algorithm which computes βk
-t = 1) recursively by
-(cid:88)"
 0c5ddfa02982dcad47704888b271997c4de0674b,Model-driven and Data-driven Approaches for some Object Recognition Problems,
 0c3f7272a68c8e0aa6b92d132d1bf8541c062141,Kruskal-Wallis-Based Computationally Efficient Feature Selection for Face Recognition,"Hindawi Publishing Corporation
 e Scientiﬁc World Journal
@@ -6247,12 +5345,6 @@ Ecole Polytechnique Federale de Lausanne, Signal Processing Institute
 Ecole Polytechnique Federale de Lausanne, Operation Research Group
 Ecublens, 1015 Lausanne, Switzerland
 Ecublens, 1015 Lausanne, Switzerland"
-0c9d9ebecfce885f3b1e7bd82ec1b74e9f17b9de,Attribute expansion with sequential learning for object classification,"ATTRIBUTE EXPANSION WITH SEQUENTIAL LEARNING FOR OBJECT
-CLASSIFICATION
-Biao Niuy, Bin Liz, Peng Liy, Xi Zhangy, Jian Chengy, Hanqing Luy
-National Laboratory of Pattern Recognition, CASIA, Beijing, China 100190
-ShiJiaZhuang Vocational Technology Institute, Hebei, China 050000
-{bniu, pli, xi.zhang, jcheng,"
 0c8d675bcd4489e886f35bee2a347c948ffee270,Semantic bottleneck for computer vision tasks,"Semantic bottleneck for computer vision tasks
 Maxime Bucher1,2, St´ephane Herbin1, and Fr´ed´eric Jurie2
 ONERA, Universit´e Paris-Saclay, FR-91123 Palaiseau, France
@@ -6301,14 +5393,6 @@ Philipps-Universit¨at Marburg
 Technicolor
 MPI for Informatics"
 0cb2dd5f178e3a297a0c33068961018659d0f443,IARPA Janus Benchmark-B Face Dataset,"© 2017 Noblis, Inc.  IARPA Janus Benchmark-B Face Dataset Cameron Whitelam, Emma Taborsky*, Austin Blanton, Brianna Maze*, Jocelyn Adams*, Tim Miller*, Nathan Kalka*, Anil K. Jain**, James A. Duncan*, Kristen Allen, Jordan Cheney*, Patrick Grother***  Noblis* Michigan State University** NIST*** 21 July 2017"
-0c922f8be9f0368c1abd53b8d9554f06b73a56cf,High-Level Fusion of Depth and Intensity for Pedestrian Classification,"High-Level Fusion of Depth and
-Intensity for Pedestrian Classiﬁcation
-Marcus Rohrbach1,3,(cid:2), Markus Enzweiler2,(cid:2), and Dariu M. Gavrila1,4
-Environment Perception, Group Research, Daimler AG, Ulm, Germany
-Image & Pattern Analysis Group, Dept. of Math.
-nd Computer Science, Univ. of Heidelberg, Germany
-Dept. of Computer Science, TU Darmstadt, Germany
-Intelligent Systems Lab, Fac. of Science, Univ. of Amsterdam, The Netherlands"
 0ca475433d74abb3c0f38fbe9d212058dc771570,Learning pairwise feature dissimilarities for person re-identification,"Learning Pairwise Feature Dissimilarities
 for Person Re-Identiﬁcation
 Niki Martinel
@@ -6345,10 +5429,6 @@ Eng. Jiangsu Univ. Xuefu Road
 01 Jingkou District Zhenjiang
 Prov. 212003
 supported  by"
-0cf333cab1a9ccf671cebf31b78180f863c1caa7,Automated Evaluation of Semantic Segmentation Robustness for Autonomous Driving,"Automated Evaluation of Semantic Segmentation
-Robustness for Autonomous Driving
-Wei Zhou, Member, IEEE, Julie Stephany Berrio, Member, IEEE,
-Stewart Worrall, Member, IEEE, and Eduardo Nebot, Member, IEEE"
 0cf7da0df64557a4774100f6fde898bc4a3c4840,Shape matching and object recognition using low distortion correspondences,"Shape Matching and Object Recognition using Low Distortion Correspondences
 Alexander C. Berg Tamara L. Berg
 Jitendra Malik
@@ -6382,22 +5462,9 @@ Department of Computer Science,Universidade Federal de Minas Gerais, Belo Horizo
 0c03bb741972c99b71d8d733b92e5fa9430cbede,Learning rank reduced interpolation with principal component analysis,"Learning Rank Reduced Interpolation
 with Principal Component Analysis
 Matthias Ochs1, Henry Bradler1 and Rudolf Mester1,2"
-0c4659b35ec2518914da924e692deb37e96d6206,Registering a MultiSensor Ensemble of Images,"Registering a MultiSensor Ensemble of Images
-Jeff Orchard, Member, IEEE, and Richard Mann"
 0c25a4636ebde18e229f7e459f1adaab1e9a2db9,Multi-class Classification and Clustering based Multi-object Tracking,"Multi-class Classification and Clustering based
 Multi-object Tracking
 Nii Longdon Sowah, Qingbo Wu, Fanman Meng"
-0cd8fabfc8e22be8275c317e7ccd37e640711c62,Experiments on an RGB-D Wearable Vision System for Egocentric Activity Recognition,"Experiments on an RGB-D Wearable Vision System
-for Egocentric Activity Recognition
-Mohammad Moghimi1, Pablo Azagra2, Luis Montesano2, Ana C. Murillo1,2 and Serge Belongie3
-UC San Diego
-La Jolla, CA
-DIIS - I3A
-University of Zaragoza, Spain
-{montesano,
-Cornell Tech
-New York, NY
-tech.cornell.edu"
 0c5f9f5083b9fca4dcdbc4b122099ac1f630728b,Visual Semantic Role Labeling,"Visual Semantic Role Labeling
 Saurabh Gupta
 UC Berkeley
@@ -6415,9 +5482,6 @@ IBM Research - Haifa, Israel
 Photometric Calibration, Motion Bias and
 Rolling Shutter Effect
 Nan Yang1,2,∗, Rui Wang1,2,∗, Xiang Gao1 and Daniel Cremers1,2"
-0c5afb209b647456e99ce42a6d9d177764f9a0dd,Recognizing action units for facial expression analysis,"Recognizing Action Units for
-Facial Expression Analysis
-Ying-li Tian, Member, IEEE, Takeo Kanade, Fellow, IEEE, and Jeffrey F. Cohn, Member, IEEE"
 0c53ef79bb8e5ba4e6a8ebad6d453ecf3672926d,Weakly Supervised PatchNets: Describing and Aggregating Local Patches for Scene Recognition,"SUBMITTED TO JOURNAL
 Weakly Supervised PatchNets: Describing and
 Aggregating Local Patches for Scene Recognition
@@ -6429,30 +5493,6 @@ Humayra Binte Ali1 and David M W Powers2
 Computer Science, Engineering and Mathematics School, Flinders University, Australia
 Computer Science, Engineering and Mathematics School, Flinders University, Australia"
 0c069a870367b54dd06d0da63b1e3a900a257298,Weakly Supervised Learning of Foreground-Background Segmentation using Masked RBMs,"Author manuscript, published in ""ICANN 2011 - International Conference on Artificial Neural Networks (2011)"""
-0c75c7c54eec85e962b1720755381cdca3f57dfb,Face Landmark Fitting via Optimized Part Mixtures and Cascaded Deformable Model,"Face Landmark Fitting via Optimized Part
-Mixtures and Cascaded Deformable Model
-Xiang Yu, Member, IEEE, Junzhou Huang, Member, IEEE,
-Shaoting Zhang, Senior Member, IEEE, and Dimitris N. Metaxas, Fellow, IEEE"
-0c3c83b7f030fe661548d362ddf33f37bb44043d,Crowd Motion Analysis Based on Social Force Graph with Streak Flow Attribute,"Hindawi Publishing Corporation
-Journal of Electrical and Computer Engineering
-Volume 2015, Article ID 492051, 12 pages
-http://dx.doi.org/10.1155/2015/492051
-Research Article
-Crowd Motion Analysis Based on Social Force Graph with
-Streak Flow Attribute
-Shaonian Huang,1,2 Dongjun Huang,1 and Mansoor Ahmed Khuhro1
-School of Information Science and Engineering, Central South University, Changsha 410083, China
-School of Computer and Information Engineering, Hunan University of Commerce, Changsha 420005, China
-Correspondence should be addressed to Shaonian Huang;
-Received 28 July 2015; Accepted 27 September 2015
-Academic Editor: Stefano Basagni
-Copyright © 2015 Shaonian Huang et al. This is an open access article distributed under the Creative Commons Attribution
-License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly
-ited.
-Over the past decades, crowd management has attracted a great deal of attention in the area of video surveillance. Among various
-tasks of video surveillance analysis, crowd motion analysis is the basis of numerous subsequent applications of surveillance video.
-In this paper, a novel social force graph with streak flow attribute is proposed to capture the global spatiotemporal changes and
-the local motion of crowd video. Crowd motion analysis is hereby implemented based on the characteristics of social force graph."
 0cca85ee872ae6f6a4d305880b4461f152b1d808,Automatic framework for tracking honeybee's antennae and mouthparts from low framerate video,"AUTOMATIC FRAMEWORK FOR TRACKING HONEYBEE’S ANTENNAE AND
 MOUTHPARTS FROM LOW FRAMERATE VIDEO
 Minmin Shen⋆
@@ -6493,11 +5533,6 @@ UNSUPERVISED ROBOTIC SORTING: TOWARDS
 AUTONOMOUS DECISION MAKING ROBOTS
 Joris Gu´Erin, St´Ephane Thiery, Eric Nyiri And Olivier Gibaru
 Arts et M´etiers ParisTech, Lille, FRANCE"
-0c36c988acc9ec239953ff1b3931799af388ef70,Face Detection Using Improved Faster RCNN,"Face Detection Using Improved Faster RCNN
-Changzheng Zhang, Xiang Xu, Dandan Tu*
-Huawei Cloud BU, China
-{zhangzhangzheng, xuxiang12,
-Figure1.Face detection results of FDNet1.0"
 0cdac46ec42be2d81f64ec4ee53d88be43290d52,Temporal Poselets for Collective Activity Detection and Recognition,"Temporal Poselets for Collective Activity Detection and Recognition
 Moin Nabi
 Alessio Del Bue
@@ -6521,36 +5556,12 @@ Switzerland
 Markus Gross
 ETH Zurich
 Switzerland"
-0c377fcbc3bbd35386b6ed4768beda7b5111eec6,A Unified Probabilistic Framework for Spontaneous Facial Action Modeling and Understanding,"A Unified Probabilistic Framework
-for Spontaneous Facial Action Modeling
-nd Understanding
-Yan Tong, Member, IEEE, Jixu Chen, Student Member, IEEE, and Qiang Ji, Senior Member, IEEE"
 71766bf224d5c74a0be6996b38d8885c2eed5a2c,Fooling Vision and Language Models Despite Localization and Attention Mechanism,
 7135bed472d9a307d0612634d690c6306f5bce26,A Unified Framework for Concurrent Pedestrian and Cyclist Detection,"This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination.
 A Uniﬁed Framework for Concurrent Pedestrian
 nd Cyclist Detection
 Xiaofei Li, Lingxi Li, Fabian Flohr, Jianqiang Wang, Hui Xiong, Morys Bernhard, Shuyue Pan,
 Dariu M. Gavrila, and Keqiang Li"
-71c549df77b0fc2ebe0dc20d39d0a629a563bd7a,Texture Classification based on Local Features Using Dual Neighborhood Approach,"I.J. Image, Graphics and Signal Processing, 2017, 9, 59-67
-Published Online September 2017 in MECS (http://www.mecs-press.org/)
-DOI: 10.5815/ijigsp.2017.09.07
-Texture Classification based on Local Features
-Using Dual Neighborhood Approach
-Associate Professor, Dept. of C.S.E, Sri Vasavi Institute of Engineering & Technology, pedana, Andhrapradesh, India
-M. Srinivasa Rao
-Email:
-V.Vijaya Kumar
-Professor, Anurag Group of Institutions (Autonomous), Hyderabad,Telanagana, India
-Email:
-MHM KrishnaPrasad
-Professor of the Department of Computer Science and Engineering, University College of  Engineering, Kakinada
-(Autonomous), JNTUK, Andhra Pradesh, India
-Email:
-Received: 11 March 2017; Accepted: 05 July 2017; Published: 08 September 2017"
-715216a92c338a3c35319026d38ed0da0c57d013,Integrated Pedestrian and Direction Classification Using a Random Decision Forest,"Integrated Pedestrian and Direction Classiﬁcation
-using a Random Decision Forest
-Junli Tao and Reinhard Klette
-University of Auckland, Auckland, New Zealand"
 71529e3e51f2967e338124652e93a3d34eb6c5e1,Deep triplet-group network by exploiting symmetric and asymmetric information for person reidentification,"Downloaded From: https://www.spiedigitallibrary.org/journals/Journal-of-Electronic-Imaging on 9/6/2018
 Terms of Use: https://www.spiedigitallibrary.org/terms-of-use
 Deeptriplet-groupnetworkbyexploitingsymmetricandasymmetricinformationforpersonreidentificationBenzhiYuNingXuBenzhiYu,NingXu,“Deeptriplet-groupnetworkbyexploitingsymmetricandasymmetricinformationforpersonreidentification,”J.Electron.Imaging27(3),033033(2018),doi:10.1117/1.JEI.27.3.033033."
@@ -6618,16 +5629,6 @@ Combinatorial Resampling Particle Filter: an Effective and Efﬁcient
 Method for Articulated Object Tracking
 Christophe Gonzales · S´everine Dubuisson
 Received: date / Accepted: date"
-71d3ed17c0642234a921bb45fcadd86520794941,Learning by Tracking: Siamese CNN for Robust Target Association,"Learning by tracking: Siamese CNN for robust target association
-Laura Leal-Taix´e
-TU M¨unchen
-Munich, Germany
-Cristian Canton-Ferrer
-Microsoft
-Redmond (WA), USA
-Konrad Schindler
-ETH Zurich
-Zurich, Switzerland"
 710ce8cf25f31df8547b888519b414187e989257,Amygdala activation predicts gaze toward fearful eyes.,"The Journal of Neuroscience, July 15, 2009 • 29(28):9123–9126 • 9123
 Brief Communications
 Amygdala Activation Predicts Gaze toward Fearful Eyes
@@ -6807,12 +5808,6 @@ Rana el Kaliouby
 MIT Media Lab
 Cambridge
 02139, USA"
-706600aa77ffb165097e4aeccb2b214dabdb8092,Combining Graph-based Dependency Features with Convolutional Neural Network for Answer Triggering,"Combining Graph-based Dependency Features with
-Convolutional Neural Network for Answer Triggering
-Deepak Gupta∗, Sarah Kohail†, Pushpak Bhattacharyya∗
-Indian Institute of Technology Patna, India
-Universit¨at Hamburg, Germany
-{deepak.pcs16,"
 70ce1a17f257320fc718d61964b21e7aeabd8cd5,Person re-identification with fusion of hand-crafted and deep pose-based body region features,"Person re-identiﬁcation with fusion of hand-crafted and deep pose-based body
 region features
 Jubin Johnson1
@@ -6882,12 +5877,6 @@ Christina Katsimerou, Judith A. Redi, Ingrid Heynderickx
 Department of Intelligent Systems
 TU Delft
 Delft, The Netherlands"
-70eb48e06d9d5edf84246b772673b6d44af4b3c6,ROBUST LDP BASED FACE DESCRIPTOR,"International Journal of Advances in Engineering & Technology, Mar. 2013.
-©IJAET                                                                                                          ISSN: 2231-1963
-ROBUST LDP BASED FACE DESCRIPTOR
-Mahadeo D. Narlawar and Jaideep G. Rana
-Department of Electronics Engineering, Jawaharlal Nehru College of Engineering,
-Aurangabad-431004, Maharashtra, India"
 70c38203d9bf5ff3a6f4639a1fb13dcaab233a61,Occlusion-robust Detector Trained with Occluded Pedestrians,
 708355d319a88485fdbbea3524104982b8cf37c2,2D/3D Sensor Exploitation and Fusion for Enhanced Object Detection,"D/3D Sensor Exploitation and Fusion for Enhanced Object Detection
 Jiejun Xu
@@ -7054,21 +6043,6 @@ Higher Order Tensors
 Shuo Zhou1, Nguyen Xuan Vinh1, James Bailey1, Yunzhe Jia1, Ian Davidson2
 Dept. of Computing and Information Systems, The University of Melbourne, Australia
 Dept. of Computer Science, University of California, Davis, USA"
-7003d903d5e88351d649b90d378f3fc5f211282b,Facial Expression Recognition using Gabor Wavelet,"International Journal of Computer Applications (0975 – 8887)
-Volume 68– No.23, April 2013
-Facial Expression Recognition using Gabor Wavelet
-Mahesh Kumbhar
-ENTC SVERI’S COE (Poly),
-Pandharpur,
-Solapur, India
-Manasi Patil
-ENTC SVERI’S COE,
-Pandharpur,
-Solapur, India
-Ashish Jadhav
-ENTC SVERI’S COE (Poly),
-Pandharpur,
-Solapur, India"
 708a55d65568faf8158417ddfb79e728b2b28f86,3D Body Model Construction and Matching for Real Time People Re-Identification,"Eurographics Italian Chapter Conference (2010)
 E. Puppo, A. Brogni, and L. De Floriani (Editors)
 D Body Model Construction and Matching for Real Time
@@ -7107,18 +6081,6 @@ L’archive ouverte pluridisciplinaire HAL, est
 destinée au dépôt et à la diffusion de documents
 scientifiques de niveau recherche, publiés ou non,
 émanant des établissements d’enseignement et de"
-ff3a9545e73adea5275a1c7c71c5e3fe2e35a9a1,An Enhanced Feature Extraction Technique for Diagnosis of Pathological Problems in Mango Crop,"I.J. Image, Graphics and Signal Processing, 2017, 9, 28-39
-Published Online September 2017 in MECS (http://www.mecs-press.org/)
-DOI: 10.5815/ijigsp.2017.09.04
-An Enhanced Feature Extraction Technique for
-Diagnosis of Pathological Problems in Mango
-S. B. Ullagaddi
-Department of CSE VTU, Belagavi, Karnataka,India
-Email:
-Dr. S.Viswanadha Raju
-Department of CSE JNTUHCEJ, Nachepally, Jagtail,Telangana,India
-Email:
-Received: 19 April 2017; Accepted: 13 May 2017; Published: 08 September 2017"
 ff01bc3f49130d436fca24b987b7e3beedfa404d,Fuzzy System-Based Face Detection Robust to In-Plane Rotation Based on Symmetrical Characteristics of a Face,"Article
 Fuzzy System-Based Face Detection Robust to
 In-Plane Rotation Based on Symmetrical
@@ -7204,25 +6166,6 @@ Dissemination Level"
 ff1b253636c878f5b464a7623f36242327e6b485,Visual Place Recognition with Probabilistic Vertex Voting,"Visual Place Recognition with Probabilistic Vertex Voting
 Mathias Gehrig, Elena Stumm, Timo Hinzmann and Roland Siegwart
 Autonomous Systems Lab, ETH Zurich"
-ff8315c1a0587563510195356c9153729b533c5b,Zapping Index:Using Smile to Measure Advertisement Zapping Likelihood,"Zapping Index:Using Smile to Measure
-Advertisement Zapping Likelihood
-Songfan Yang, Member, IEEE, Mehran Kafai, Member, IEEE,
-Le An, Student Member, IEEE, and Bir Bhanu, Fellow, IEEE"
-ffc06713436afc4e08bf4afa401ac52db674c5da,Neural Adaptive Content-aware Internet Video Delivery,"Neural Adaptive Content-aware
-Internet Video Delivery
-Hyunho Yeo, Youngmok Jung, Jaehong Kim, Jinwoo Shin, and Dongsu Han, KAIST
-https://www.usenix.org/conference/osdi18/presentation/yeo
-This paper is included in the Proceedings of the 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI ’18).October 8–10, 2018 • Carlsbad, CA, USAISBN 978-1-931971-47-8Open access to the Proceedings of the 13th USENIX Symposium on Operating Systems Design and Implementation is sponsored by USENIX."
-ff4e8a8333e4ef506318160248c068250963806d,Gender recognition from face images using texture descriptors for human computer interaction,"www.jchps.com                                                                    Journal of Chemical and Pharmaceutical Sciences
-Gender recognition from face images using texture descriptors
-ISSN: 0974-2115
-for human computer interaction
-M.Annalakshmi1*, S.M.M.Roomi2, and S.S.Priya1
-&3Department of Electronics and Communication Engineering, Sethu Institute of Technology, Pulloor, Kariapatti
-Department of Electronics and Communication Engineering, Thiagarajar College of Engineering, Madurai 625
-– 626 115, Virudhunagar – District, Tamilnadu, India.
-*Corresponding author: E-Mail:
-015, Tamilnadu, India"
 ffeff854e7fcf5af663497be00c86537f7d9ed11,Face recognition in JPEG compressed domain: a novel coefficient selection approach,"SIViP (2015) 9:651–663
 DOI 10.1007/s11760-013-0492-8
 ORIGINAL PAPER
@@ -7307,12 +6250,6 @@ Universitat Aut`onoma de Barcelona
 C. Alejandro Parraga
 Centre de Visi´o per Computador
 Universitat Aut`onoma de Barcelona"
-ff7bc7a6d493e01ec8fa2b889bcaf6349101676e,Facial expression recognition with spatiotemporal local descriptors,"Facial expression recognition with spatiotemporal local
-descriptors
-Guoying Zhao, Matti Pietikäinen
-Machine  Vision  Group,  Infotech  Oulu  and  Department  of  Electrical  and
-Information Engineering, P. O. Box 4500 FI-90014 University of Oulu, Finland
-{gyzhao,"
 ffae2fe85d3c93610ac6270db2ddf1f2f6779ea8,Learning pullback HMM distances for action recognition,"#****
 ICCV 2011 Submission #****. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE.
 Learning pullback HMM distances for action recognition
@@ -7336,10 +6273,6 @@ May 29, 2017"
 fff12919cf912347776b70aa76af7635280dc401,Are object detection assessment criteria ready for maritime computer vision?,"Are object detection assessment criteria ready
 for maritime computer vision?
 Dilip K. Prasad1,∗, Deepu Rajan2, and Chai Quek2"
-fffefc1fb840da63e17428fd5de6e79feb726894,Fine-Grained Age Estimation in the wild with Attention LSTM Networks,"Fine-Grained Age Estimation in the wild with
-Attention LSTM Networks
-Ke Zhang, Member, IEEE, Na Liu, Xingfang Yuan, Student Member, IEEE, Xinyao Guo, Ce Gao,
-nd Zhenbing Zhao Member, IEEE,"
 ffcb92719dcd993dda292ca82d4585950ea22ac9,Handwritten Digit Recognition Using Convolutional Neural Networks,"ISSN(Online): 2320-9801
 ISSN (Print):  2320-9798
 International Journal of Innovative Research in Computer
@@ -7395,10 +6328,6 @@ College of Computer Science at Chongqing University, Chongqing, 400044, P.R.C
 Eller College of Management at University of Arizona, Tucson, AZ, 85712, USA
 School of Software Engineering at Chongqing University, Chongqing, 400044, P.R.C
 dMinistry of Education Key Laboratory of Dependable Service Computing in Cyber Physical Society, Chongqing, 400044, P.R.C"
-ab87dfccb1818bdf0b41d732da1f9335b43b74ae,Structured Dictionary Learning for Classification,"SUBMITTED TO IEEE TRANSACTIONS ON SIGNAL PROCESSING
-Structured Dictionary Learning for Classiﬁcation
-Yuanming Suo, Student Member, IEEE, Minh Dao, Student Member, IEEE, Umamahesh Srinivas, Student
-Member, IEEE, Vishal Monga, Senior Member, IEEE, and Trac D. Tran, Fellow, IEEE"
 abeda55a7be0bbe25a25139fb9a3d823215d7536,Understanding Human-Centric Images: From Geometry to Fashion,"UNIVERSITATPOLITÈCNICADECATALUNYAProgramadeDoctorat:AUTOMÀTICA,ROBÒTICAIVISIÓTesiDoctoralUnderstandingHuman-CentricImages:FromGeometrytoFashionEdgarSimoSerraDirectors:FrancescMorenoNoguerCarmeTorrasMay2015"
 ab969cfae95f62d68c61830128b35786eb6c84a9,Contents 1 Introduction 2,"Contents1Introduction22Tracking:FundamentalNotions22.1Trackingbydetection........................................22.2TrackingusingFlow........................................22.3Flowmodelsfromkinematicmodels................................22.4TrackingwithProbability......................................23Tracking:Relationsbetween3Dand2D23.1KinematicInferencewithMultipleViews.............................23.2Liftingto3D............................................33.3MultipleModes,RandomizedSearchandHumanTracking....................34Tracking:DataAssociationforHumanTracking54.1DetectingHumans.........................................54.2TrackingbyMatchingRevisited..................................64.3Evaluation..............................................75MotionSynthesisandAnimation95.1Motioncapture...........................................95.2Footskate..............................................95.3ResolvingKinematicAmbiguitieswithExamples.........................95.4MotionSignalProcessing......................................95.5MotionGraphs...........................................95.6MotionPrimitives..........................................105.7EnrichingaMotionCollection...................................105.8MotionfromPhysicalConsiderations...............................105.8.1SimpliﬁedCharacters....................................105.8.2ModiﬁedPhysics......................................115.8.3ReducedDimensions....................................115.8.4ModifyingExistingMotions................................116DescribingActivities126.1WhatshouldanActivityRepresentationdo?............................126.1.1NecessaryPropertiesofanActivityRepresentation....................136.1.2WhatDataisAvailable?..................................136.2MiscellaneousMethods.......................................146.2.1ActivityRepresentationMethodsbasedaroundTemporalLogics.............146.2.2ActivityRepresentationMethodsbasedonTemplates...................146.3ActivityRepresentationusingHiddenMarkovModelsandFiniteStateRepresentations.....146.4TheSpeechAnalogy........................................146.4.1FiniteStateTransducers..................................156.4.2WhyshouldweCare?...................................156.5ActivityRecognitionMethodsbasedaroundHMM’s.......................166.6SignLanguageRecognition.....................................176.7Morerecentmaterial........................................171"
 abba22ed4713a5ee5fa91fcf7b8dde58a9b621db,Acquisition of a 3D Audio-Visual Corpus of Affective Speech,"BIWI Technical Report n. 270
@@ -7439,8 +6368,6 @@ of Saarland University
 Marcus Rohrbach, M.Sc.
 Saarbrücken
 March 2014"
-ab41364a58b34844b281046c3d8678f7d537a97e,Learning Deep Hierarchical Visual Feature Coding,"Learning Deep Hierarchical Visual Feature Coding
-Hanlin Goh, Nicolas Thome, Member, IEEE, Matthieu Cord, Member, IEEE, and Joo-Hwee Lim, Member, IEEE"
 ab450a7968555532d9ea79f81189c0d52f9c5f11,RGB-D Face Recognition in Surveillance Videos,"RGB-D Face Recognition in Surveillance Videos
 Anurag Chowdhury
 IIIT-D-MTech-CS-GEN-14-002
@@ -7581,11 +6508,6 @@ A Convex Max-Flow Approach to Distribution-Based Figure-Ground Separation
 , Shuo Li
 , and Yuri Boykov
 Kumaradevan Punithakumar"
-ab302d79e419348499acbda4a627b67dec89936f,Robust Correlated and Individual Component Analysis,"JOURNAL OF LATEX CLASS FILES, VOL. 6, NO. 1, JANUARY 2014
-Robust Correlated and Individual Component
-Analysis
-Yannis Panagakis, Member, IEEE, Mihalis A. Nicolaou, Member, IEEE,
-Stefanos Zafeiriou, Member, IEEE, and Maja Pantic, Fellow, IEEE"
 abc66504927075c5878dc6b0d70f2d4b009a9c9a,Damaged Building Detection in the crisis areas using Image Processing Tools,
 ab8af4cb5243544e38852bb670aafe5a2fd9b3ec,Real-Time Human Detection Using Relational Depth Similarity Features,"Real-Time Human Detection using Relational
 Depth Similarity Features
@@ -7593,9 +6515,6 @@ Sho Ikemura, Hironobu Fujiyoshi
 Dept. of Computer Science, Chubu University.
 Matsumoto 1200, Kasugai, Aichi, 487-8501 Japan.
 http://www.vision.cs.chubu.ac.jp"
-ab0dd486ff270c3a5ec877aecad7f20b2ce3f670,A Two Phase Approach for Pedestrian Detection,"A Two Phase Approach for Pedestrian Detection
-Soonmin Hwang, Tae-Hyun Oh, In So Kweon
-Robotics and Computer Vision Lab., KAIST, Korea"
 ab6776f500ed1ab23b7789599f3a6153cdac84f7,A Survey on Various Facial Expression Techniques,"International Journal of Scientific & Engineering Research, Volume 6, Issue 4, April-2015                                                                                                   1212
 ISSN 2229-5518
 A Survey on Various Facial Expression
@@ -7635,9 +6554,6 @@ d’explications possibles d’une image donnée lorsque les connaissances, expr
 logique de description, comportent des concepts décrivant les objets mais aussi les relations
 spatiales entre ces objets. La meilleure explication est sélectionnée en exploitant les domaines
 oncrets pour évaluer le degré de satisfaction des relations spatiales entre les objets."
-ab43c43d5eb2c5bee6de1b25c8bcb8068ab8bcd2,Deep Class-Wise Hashing: Semantics-Preserving Hashing via Class-wise Loss,"Deep Class-Wise Hashing:
-Semantics-Preserving Hashing via Class-wise Loss
-Xuefei Zhe, Shifeng Chen, Member, IEEE, and Hong Yan, Fellow, IEEE"
 abb4b8f9df14f7b15aa43920d0329eccada33b97,LBP Yardımıyla Görüntüdeki Kişinin Yaşının Bulunması,"C¸ ankaya University Journal of Science and Engineering
 Volume 8 (2011), No. 1, 27–41
 LBP Yardımıyla G¨or¨unt¨udeki Ki¸sinin Ya¸sının
@@ -7658,16 +6574,6 @@ larının birle¸stirilmesiyle, y¨uz i¸cin verimli bir vekt¨orel g¨osterim �
 teme sunulan her yeni y¨uz i¸cin b¨olgesel LBP histogramı ¨uretilmekte ve ya¸s sınıflarına
 it LBP histogramlarıyla kar¸sıla¸stırılarak sınıflandırılmaktadır. Sınıflandırmada minimum
 uzaklık (minimum distance), en yakın kom¸suluk (nearest neighbor) ve k-en yakın kom¸suluk"
-abf659847660763c94b44c0baaf9198046a11845,Video Image Object Tracking Algorithm based on Improved Principal Component Analysis,"Video Image Object Tracking Algorithm based
-on Improved Principal Component Analysis
-. Engineering Technology Research Center of Optoelectronic Technology Appliance, AnHui Tongling Anhui 244000,
-. Hefei University of Technology, Hefei Anhui 230009, China
-China
-Wang Liping 1, 2
-dopts
-DPCA
-lgorithm
-to  reduce  dimension  of  object"
 abb1289cfdc4c23d72d0680c3ec100eae74d4fdb,PatchMatch : A Fast Randomized Matching Algorithm with Application to Image and Video,"PatchMatch: A Fast Randomized Matching
 Algorithm with Application to Image and Video
 Connelly Barnes
@@ -7756,20 +6662,10 @@ Merantix GmbH
 Luc Van Gool
 D-ITET, ETH Zurich
 ESAT, KU Leuven"
-ae5983048e59a339c77fee89e9279a4a787ba985,Part-Based Deep Hashing for Large-Scale Person Re-Identification,"Part-based Deep Hashing for Large-scale
-Person Re-identiﬁcation∗
-Fuqing Zhu, Xiangwei Kong, Member, IEEE, Liang Zheng, Member, IEEE, Haiyan Fu, Member, IEEE,
-Qi Tian, Fellow, IEEE,"
 aeff403079022683b233decda556a6aee3225065,DeepFace: Face Generation using Deep Learning,"DeepFace: Face Generation using Deep Learning
 Hardie Cate
 Fahim Dalvi
 Zeshan Hussain"
-ae33dc04adcb83a486517c48078cdd4af7dcc7c7,The adaptative local Hausdorff-distance map as a new dissimilarity measure,"The adaptative local Hausdorff-distance map
-s a new dissimilarity measure
-´Etienne Baudrier∗, Gilles Millon, Fr´ed´eric Nicolier, Su Ruan
-Centre de Recherche en STIC (CReSTIC)
-IUT de Troyes, 9, rue de Qu´ebec, 10026 TROYES CEDEX, FRANCE
-{e.baudrier, g.millon, f.nicolier,"
 ae2cf545565c157813798910401e1da5dc8a6199,Cascade of Boolean detector combinations,"Mahkonen et al. EURASIP Journal on Image and Video
 Processing  (2018) 2018:61
 https://doi.org/10.1186/s13640-018-0303-9
@@ -7952,18 +6848,6 @@ Butler, Joseph G., ""Automated Fingertip Detection"" (2012). All Theses and Diss
 https://scholarsarchive.byu.edu/etd/3164
 This Thesis is brought to you for free and open access by BYU ScholarsArchive. It has been accepted for inclusion in All Theses and Dissertations by an
 uthorized administrator of BYU ScholarsArchive. For more information, please contact"
-ae85c822c6aec8b0f67762c625a73a5d08f5060d,Retrieving Similar Styles to Parse Clothing,"This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication.
-The final version of record is available at http://dx.doi.org/10.1109/TPAMI.2014.2353624
-IEEE TRANSACTION ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. M, NO. N, MONTH YEAR
-Retrieving Similar Styles to Parse Clothing
-Kota Yamaguchi, Member, IEEE, M. Hadi Kiapour, Student Member, IEEE,
-Luis E. Ortiz, and Tamara L. Berg, Member, IEEE"
-aee90db1f66b77113b0a62701deb01ca96b6d9e6,"Discriminant Saliency, the Detection of Suspicious Coincidences, and Applications to Visual Recognition","JUNE 2009
-Discriminant Saliency, the Detection
-of Suspicious Coincidences,
-nd Applications to Visual Recognition
-Dashan Gao, Member, IEEE, Sunhyoung Han, Student Member, IEEE, and
-Nuno Vasconcelos, Senior Member, IEEE"
 ae89b7748d25878c4dc17bdaa39dd63e9d442a0d,On evaluating face tracks in movies,"On evaluating face tracks in movies
 Alexey Ozerov, Jean-Ronan Vigouroux, Louis Chevallier, Patrick Pérez
 To cite this version:
@@ -7984,9 +6868,6 @@ destinée au dépôt et à la diffusion de documents
 scientifiques de niveau recherche, publiés ou non,
 émanant des établissements d’enseignement et de
 recherche français ou étrangers, des laboratoires"
-ae299fad29ba650fbf1e14c7c95ba8ae32e095f0,Person Re-Identification by Robust Canonical Correlation Analysis,"Person Re-Identiﬁcation by Robust
-Canonical Correlation Analysis
-Le An, Songfan Yang, Member, IEEE, and Bir Bhanu, Fellow, IEEE"
 ae0322119c8d70ba98f32aeb205393dad8dd287b,OxIOD: The Dataset for Deep Inertial Odometry,"OxIOD: The Dataset for Deep Inertial Odometry
 Changhao Chen∗, Peijun Zhao∗, Chris Xiaoxuan Lu, Wei Wang, Andrew Markham, Niki Trigoni"
 ae8d5be3caea59a21221f02ef04d49a86cb80191,Skip RNN: Learning to Skip State Updates in Recurrent Neural Networks,"Published as a conference paper at ICLR 2018
@@ -8039,10 +6920,6 @@ Prof Frédéric Jurie, rapporteur"
 07c6744e25ed01967e448a397f5d7e9d540345c3,Effective Multi-Query Expansions: Collaborative Deep Networks for Robust Landmark Retrieval,"Effective Multi-Query Expansions: Collaborative Deep Networks for Robust
 Landmark Retrieval
 Yang Wang, Xuemin Lin, Lin Wu, Wenjie Zhang"
-073bcb3b1aed5cdf7bff4e9fe46a21175f42c877,"Zero-Shot Learning - A Comprehensive Evaluation of the Good, the Bad and the Ugly","Zero-Shot Learning - A Comprehensive
-Evaluation of the Good, the Bad and the Ugly
-Yongqin Xian, Student Member, IEEE, Christoph H. Lampert,
-Bernt Schiele, Fellow, IEEE, and Zeynep Akata, Member, IEEE"
 074061bc12af98e3c9fd7650452d896b2c03b3ac,A FPGA Implementation of Neural / Wavelet Face Detection System,"Australian  Journal  of  Basic  and  Applied  Sciences,  4(3):  379-388,  2010
 ISSN  1991-8178
 ©  2010,  INSInet  Publication
@@ -8217,26 +7094,6 @@ Facebook AI Research"
 Nathan Jones
 Formerly: Texas A&M University
 Currently: The Software Group"
-07a7484a9cc566619ff9a01eb71bfa30ea9e4a06,Measurement of exceptional motion in VR video contents for VR sickness assessment using deep convolutional autoencoder,"Measurement of exceptional motion in VR video contents for
-VR sickness assessment using deep convolutional autoencoder
-Hak Gu Kim
-Image and Video System Lab.,
-Electrical Engineering, KAIST,
-South Korea,
-Wissam J. Baddar
-Image and Video System Lab.,
-Electrical Engineering, KAIST,
-South Korea,
-Heoun-taek Lim
-Image and Video System Lab.,
-Electrical Engineering, KAIST,
-South Korea,
-Hyunwook Jeong
-Image and Video System Lab.,
-Electrical Engineering, KAIST,
-South Korea,
-Yong Man Ro*
-Image and Video System Lab.,"
 0726152a1c1a5723ac34d54abec0dc8d4659598e,Realtime Image Matching for Vision Based Car Navigation with Built-in Sensory Data,"ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume II-3/W2, 2013
 ISA13 - The ISPRS Workshop on Image Sequence Analysis 2013, 11 November 2013, Antalya, Turkey"
 073c5c27f26c9d174e2ee060b27a090457e3f774,Backprop KF: Learning Discriminative Deterministic State Estimators,"Backprop KF: Learning Discriminative Deterministic
@@ -8312,12 +7169,6 @@ L’archive ouverte pluridisciplinaire HAL, est
 destinée au dépôt et à la diffusion de documents
 scientifiques de niveau recherche, publiés ou non,
 émanant des établissements d’enseignement et de"
-0730d5f4408ab3c3bcc316ecbbfdc61cdbf7d813,Object-centric Auto-encoders and Dummy Anomalies for Abnormal Event Detection in Video,"Object-centric Auto-encoders and Dummy Anomalies
-for Abnormal Event Detection in Video
-Radu Tudor Ionescu1,2,3, Fahad Shahbaz Khan1, Mariana-Iuliana Georgescu2,3, Ling Shao1
-Inception Institute of Artiﬁcial Intelligence (IIAI), Abu Dhabi, UAE
-University of Bucharest, 14 Academiei, Bucharest, Romania
-SecurifAI, 21 Mircea Vod˘a, Bucharest, Romania"
 07ca470ed3be3a476b6fc1917bbbf4182846d1db,Transforming sensor data to the image domain for deep learning — An application to footstep detection,"Transforming Sensor Data to the Image Domain for
 Deep Learning - an Application to Footstep
 Detection
@@ -8329,9 +7180,6 @@ TU Kaiserslautern, Germany
 DFKI, Kaiserslautern, Germany
 M onit ki.de, r.ch
 ki.de, P ki.de,"
-07625af8d73142e239b5cdccb1dd226648e4b0d4,Learning Scene-Independent Group Descriptors for Crowd Understanding,"Learning Scene-Independent Group Descriptors for
-Crowd Understanding
-Jing Shao, Chen Change Loy, Member, IEEE, and Xiaogang Wang, Member, IEEE"
 072fd0b8d471f183da0ca9880379b3bb29031b6a,Image-to-Image Translation with Conditional Adversarial Networks,"Image-to-Image Translation with Conditional Adversarial Networks
 Phillip Isola
 Jun-Yan Zhu
@@ -8381,26 +7229,6 @@ Anonymous Author(s)
 Afﬁliation
 Address
 email"
-f0304ea9943e96e645b8702c2810cca517439465,Automatic Diagnosis of Diabetic Retinopathy by Hybrid Multilayer Feed Forward Neural Network Ms,"ISSN: 2278 – 7798
-International Journal of Science, Engineering and Technology Research (IJSETR)
-Volume 2, Issue 9, September 2013
-Automatic Diagnosis of Diabetic Retinopathy by
-Hybrid Multilayer Feed Forward Neural Network
-Ms. Rupa V. Lichode
-M. Tech ( Computer Science and Engineering )
-IVth    Semester
-R.C.E.R.T. Chandrapur
-Abtract--  For  a  particularly  long  time,  Automatic  diagnosis  of
-diabetic  retinopathy  from  digital  fundus  images  has  been  an  active
-research  topic  in  the  medical  image  processing  community.  This
-paper  describes  what  is  the  diagnosis  of  Diabetic  Retinopathy  by
-various image processing techniques and how proposed work can be
-help  to  enhace  it  further.  In  the  beginning  section  introduction
-provides  the  terminology  related  to  DR  like  fundus  images  with
-different  types  of  stages  in  Diabetic  Retinopathy  as  NPDR(  Non
-Proliferative  DR)  and  PDR(  Proliferative  DR)    levels.  Further
-sections describes different features extraction of  Fundus images like
-exudates, microaneurysms, optic Disc, macula, blood vessels, texture"
 f05358fb80283f0f242215d459367bddce810cd0,An Efficient Video to Video Face Recognition using Neural Networks,"An Efficient Video to Video Face Recognition using Neural Networks
 {tag}                                                 {/tag}
 International Journal of Computer Applications
@@ -8434,17 +7262,6 @@ Clayton Mellina: and David A. Shamma§‹
 f07956d0031ff046c5c719296f7916d7897fdd21,A Flexible Real-Time Control System for Autonomous Vehicles,"A Flexible Real-Time Control System for Autonomous Vehicles.
 Johannes Meyer, Armin Strobel
 Institute of Flight Systems and Automatic Control, Technische Universität Darmstadt, Germany 1"
-f0a0f341fa1f91ee58a5020297bea02f8863cb26,Learning Deep Semantic Embeddings for Cross-Modal Retrieval,"Proceedings of Machine Learning Research 77:471–486, 2017
-ACML 2017
-Learning Deep Semantic Embeddings for Cross-Modal
-Retrieval
-Cuicui Kang
-No.89A Minzhuang Road, Beijing, China
-Shengcai Liao∗
-No.95 Zhuangguancun East Road, Beijing, China
-Zhen Li, Zigang Cao, Gang Xiong
-No.89A Minzhuang Road, Beijing, China
-Editors: Yung-Kyun Noh and Min-Ling Zhang"
 f040e4fcedca0c07788ecb6e92ad246b9c1697a9,REAL-TIME MULTIPLE HEAD TRACKING USING TEXTURE AND COLOUR CUES,"REAL-TIME MULTIPLE HEAD TRACKING
 USING TEXTURE AND COLOUR CUES
 Vasil Khalidov        Jean-Marc Odobez
@@ -8485,9 +7302,6 @@ Masaki Saito∗
 Eiichi Matsumoto∗
 Preferred Networks inc., Japan
 {msaito,"
-f08266cea120e8aa091983da5269ee5e35febe75,Semantic Diversity versus Visual Diversity in Visual Dictionaries,"Semantic Diversity versus Visual Diversity
-in Visual Dictionaries
-Ot´avio A. B. Penatti, Sandra Avila, Member, IEEE, Eduardo Valle, Ricardo da S. Torres, Member, IEEE"
 f0cc615b14c97482faa9c47eb855303c71ff03a7,Tracklet clustering for robust multiple object tracking using distance dependent Chinese restaurant processes,"SIViP
 DOI 10.1007/s11760-015-0817-x
 ORIGINAL PAPER
@@ -8499,12 +7313,6 @@ Received: 4 June 2015 / Revised: 19 August 2015 / Accepted: 10 September 2015
 f0b77702c8f2249ee1f48e51ff9b86faffe177c9,Reformulating Level Sets as Deep Recurrent Neural Network Approach to Semantic Segmentation,"Reformulating Level Sets as Deep Recurrent Neural Network Approach
 to Semantic Segmentation
 Ngan Le 1 Kha Gia Quach 1 2 Khoa Luu 1 Marios Savvides 1 Chenchen Zhu 1"
-f0d29be1a93158d320bef285442f63bb090f6c31,An Online and Flexible Multi-Object Tracking Framework using Long Short-Term Memory,"An Online and Flexible Multi-Object Tracking Framework using Long
-Short-Term Memory
-Xingyu Wan, Jinjun Wang, Sanping Zhou
-Xi’an Jiaotong University
-Institute of Artiﬁcial Intelligence and Robotics
-8 West Xianning Road, Xi’an, Shaanxi, China, 710049"
 f0e609a2e11a093273c0d8e3321e7b20eaca46e9,Closing the gap towards end-to-end autonomous vehicle system,"Closing the gap towards
 end-to-end autonomous vehicle system
 Yonatan Glassner∗, Liran Gispan∗, Ariel Ayash∗, and Tal Furman Shohet∗
@@ -8562,10 +7370,6 @@ Copyright © 2014 by the American Physiological Society."
 f0dd265dfbe9ffe86ca56ba053335626720059a3,CNN Fixations: An unraveling approach to visualize the discriminative image regions,"CNN Fixations: An unraveling approach to
 visualize the discriminative image regions
 Konda Reddy Mopuri*, Utsav Garg*, R. Venkatesh Babu, Senior Member, IEEE"
-f0c99016daf4ff2dcc2cde13822714155435128e,No Blind Spots: Full-Surround Multi-Object Tracking for Autonomous Vehicles using Cameras & LiDARs,"No Blind Spots: Full-Surround Multi-Object
-Tracking for Autonomous Vehicles using
-Cameras & LiDARs
-Akshay Rangesh, Member, IEEE, and Mohan M. Trivedi, Fellow, IEEE"
 f074f216e6eecd1be64398fdf1e06927b94c8df8,Classifying Faces with Non-negative Matrix Factorization,"Classifying Faces with Non-negative Matrix
 Factorization
 David Guillamet , Jordi Vitri`a
@@ -8573,18 +7377,6 @@ Computer Vision Center, Dept. Inform`atica
 Universitat Aut`onoma de Barcelona
 08193 Bellaterra, Barcelona, Spain"
 f00e51ec0e3894bdb2977a01824f37b15bb82c6e,A Gaussian Approximation of Feature Space for Fast Image Similarity,"Computer Science and ArtificialIntelligence LaboratoryTechnical Reportmassachusetts institute of technology, cambridge, ma 02139 usa — www.csail.mit.eduMIT-CSAIL-TR-2012-032October 1, 2012A Gaussian Approximation of Feature Space for Fast Image Similarity Michael Gharbi, Tomasz Malisiewicz, Sylvain Paris, and FrØdo Durand"
-f0aac566e3d2c06759b8f4f45a270d5af93b9705,Ear Structure Feature Extraction Based on Multi-scale Hessian Matrix,"International Journal of Signal Processing, Image Processing and Pattern Recognition
-Vol.9, No.5 (2016), pp.159-172
-http://dx.doi.org/10.14257/ijsip.2016.9.5.14
-Ear Structure Feature Extraction Based on Multi-scale Hessian
-Matrix
-,Ban Xiaojuan*1, Wang Guosheng3 and Tian Ying2
-Ma Chi1,2,3
-School of Computer & Communication Engineering, University of Science and
-College of Software, University of Science and Technology LiaoNing, Anshan,
-Technology Beijing, Beijing, China
-Beihai Yinhe Industry Investment Co.,Ltd., Beihai, China
-China"
 cfffae38fe34e29d47e6deccfd259788176dc213,Training bookcowgrass flower ? ? water sky doggrass water boat water chair road ? cow grass chair grass dog building ?,"TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. X, NO. X, DECEMBER 2012
 Matrix Completion for Weakly-supervised
 Multi-label Image Classiﬁcation
@@ -8623,14 +7415,6 @@ Linear Discriminant Analysis vs. Logistic Regression
 Benjamin Quost · Thierry Denœux ·
 Shoumei Li
 Received: date / Accepted: date"
-cfd933f71f4a69625390819b7645598867900eab,Person Authentication Using Face And Palm Vein : A Survey Of Recognition And Fusion Techniques,"INTERNATIONAL JOURNAL OF TECHNOLOGY ENHANCEMENTS AND EMERGING ENGINEERING RESEARCH, VOL 3, ISSUE 03                       55
-ISSN 2347-4289
-Person Authentication Using Face And Palm Vein:
-A Survey Of Recognition And Fusion Techniques
-Preethi M, Dhanashree Vaidya, Dr. S. Kar, Dr. A. M. Sapkal, Dr. Madhuri A. Joshi
-Dept. of Electronics and Telecommunication, College of Engineering, Pune, India,
-Image Processing & Machine Vision Section, Electronics & Instrumentation Services Division, BARC
-Email:"
 cfbfcf538c1c9bbf170a524995098fe4aacde374,Symmetric generalized low rank approximations of matrices,"978-1-4673-0046-9/12/$26.00 ©2012 IEEE
 ICASSP 2012"
 cfbb2d32586b58f5681e459afd236380acd86e28,Improving alignment of faces for recognition,"Improving Alignment of Faces for Recognition
@@ -8642,14 +7426,6 @@ D´epartement de g´enie informatique et g´enie logiciel
 ´Ecole Polytechnique de Montr´eal,
 Qu´ebec, Canada
 Qu´ebec, Canada"
-cf7e6d057e6ef01904770be3dfc9da29f9c1e197,An Adaptive Detection Method of Multiple Faces,"TELKOMNIKA Indonesian Journal of Electrical Engineering
-Vol.12, No.4, April 2014, pp. 2743 ~ 2752
-DOI: http://dx.doi.org/10.11591/telkomnika.v12i4.4368
-An Adaptive Detection Method of Multiple Faces
-      2743
-China West Normal University, No. 1 Shida Road, Computer School, Nanchong, China
-*Corresponding author, e-mail:
-Wei Li"
 cf40951840bfa9b8721d722e9422c73e3a6fbf59,Real-time Appearance-based Person Re-identification Over Multiple KinectTM Cameras,"Real-time appearance-based person re-identiﬁcation
 over multiple KinectTMcameras
 Riccardo Satta, Federico Pala, Giorgio Fumera and Fabio Roli
@@ -8726,11 +7502,6 @@ Université de Sherbrooke, 2MILA, Université de Montréal, 3Rice University, 4I
 {simon.brodeur, luca.celotti,
 {florian.golemo,
 {ankesh.anand,"
-cfc9056155bf32648448b588a752f694b4e8249c,Combining Contrast Information and Local Binary Patterns for Gender Classification,"Combining Contrast Information and Local
-Binary Patterns for Gender Classiﬁcation
-Juha Ylioinas, Abdenour Hadid, and Matti Pietik¨ainen
-Machine Vision Group, PO Box 4500,
-FI-90014 University of Oulu, Finland"
 cf6527d8d42a9958eea7d8d1f90ea4c86d591408,Convolutional Neural Network-Based Classification of Driver’s Emotion during Aggressive and Smooth Driving Using Multi-Modal Camera Sensors,"Article
 Convolutional Neural Network-Based Classiﬁcation
 of Driver’s Emotion during Aggressive and Smooth
@@ -8824,13 +7595,6 @@ If  not Barney, then what would  be  an example  of  a  computa-
 tional system that has emotions? I am not a philosopher, and this
 paper will not be  a  discussion  of  the meaning  of  this question in
 ny philosophical sense. However, as an engineer I am interested"
-cfb3c1c395b146021a70ae9d5cf7c76854108a86,S-Log: Skin based Log-Gabor Approach for Face Detection in Video,"S-Log: Skin based Log-Gabor Approach for Face Detection in Video
-Rajeshwari J1, K. Karibasappa2, Gopalkrishna M.T3
-Dayanada Sagar College of Engineering
-Oxford College of Engineering
-K.S. School of Engineering and Management
-Computer Science and Engineering Department
-Bangalore, India"
 cfc22c35ad191cf9d70f4a3655840748b0e1322c,Real-Time Dense Mapping for Self-driving Vehicles using Fisheye Cameras,"Real-Time Dense Mapping
 for Self-Driving Vehicles using Fisheye Cameras
 Zhaopeng Cui1, Lionel Heng2, Ye Chuan Yeo2, Andreas Geiger3, Marc Pollefeys1,4, and Torsten Sattler1"
@@ -8860,26 +7624,6 @@ Herzliya, Israel 4672560
 Eduard Oks
 Amazon Lab 126
 Herzliya, Israel 4672560"
-75f0d2d8aae00da73e4122c712ad230cfebe7729,AMassively Parallel Face Recognition System,"Hindawi Publishing Corporation
-EURASIP Journal on Embedded Systems
-Volume 2007, Article ID 72316, 13 pages
-doi:10.1155/2007/72316
-Research Article
-A Massively Parallel Face Recognition System
-Olli Lahdenoja,1, 2 Mika Laiho,1 Janne Maunu,1, 2 and Ari Paasio1
-Department of Information Technology, University of Turku, Joukahaisenkatu 3-5, 20014 Turku, Finland
-Turku Centre for Computer Science (TUCS), University of Turku, Joukahaisenkatu 3-5 B, 6th floor, 20520 Turku, Finland
-Received 12 April 2006; Revised 31 August 2006; Accepted 5 October 2006
-Recommended by Heinrich Garn
-We present methods for processing the LBPs (local binary patterns) with a massively parallel hardware, especially with CNN-UM
-(cellular nonlinear network-universal machine). In particular, we present a framework for implementing a massively parallel face
-recognition system, including a dedicated highly accurate algorithm suitable for various types of platforms (e.g., CNN-UM and
-digital FPGA). We study in detail a dedicated mixed-mode implementation of the algorithm and estimate its implementation cost
-in the view of its performance and accuracy restrictions.
-Copyright © 2007 Olli Lahdenoja et al. This is an open access article distributed under the Creative Commons Attribution License,
-which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
-INTRODUCTION
-Face recognition is easy for humans but extremely dif‌f‌icult"
 75522dfc1610c8765185c4344d97db33e1af5047,3D Human Body-Part Tracking and Action Classification Using A Hierarchical Body Model,"RASKIN, RUDZSKY, RIVLIN: BODY-PART TRACKING AND ACTION CLASSIFICATION
 D Human Body-Part Tracking and Action
 Classiﬁcation Using a Hierarchical Body
@@ -8890,10 +7634,6 @@ Ehud Rivlin
 Computer Science Department
 Technion -Israel Institute of Technology
 Haifa, Israel, 3200"
-75d571d53eb250e222d66461fa2400956b40eaa9,What Makes a Photograph Memorable?,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication.
-What makes a photograph memorable?
-Phillip Isola, Jianxiong Xiao, Member, IEEE, Devi Parikh, Member, IEEE, Antonio Torralba, Member, IEEE,
-nd Aude Oliva"
 758d7e1be64cc668c59ef33ba8882c8597406e53,"AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild","IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
 AffectNet: A Database for Facial Expression,
 Valence, and Arousal Computing in the Wild
@@ -8939,9 +7679,6 @@ Trento, Italy
 Universit`a degli Studi di Genova,
 Genova, Italy
 Site Spa, Bologna, Italy"
-754fa133a250d824c50b4c3b9c73975059954f41,Siamese Learning Visual Tracking: A Survey.,"Siamese Learning Visual Tracking: A Survey
-Roman Pflugfelder, Member, IEEE
-(Draft Article)"
 759a3b3821d9f0e08e0b0a62c8b693230afc3f8d,Attribute and simile classifiers for face verification,"Attribute and Simile Classiﬁers for Face Veriﬁcation
 Neeraj Kumar
 Alexander C. Berg
@@ -8988,18 +7725,6 @@ facial  range  images  from  130  persons  with  normal  facial
 expressions.  The  processing  time  of  the  recognition  system  is
 etter  than  3LMS.  Moreover,  it  is  6  times  faster  without  any
 hange of recognition rate. Memory size of this experimental was"
-7553fba5c7f73098524fbb58ca534a65f08e91e7,A Practical Approach for Determination of Human Gender & Age,"Harpreet Kaur Bhatia et al, International Journal of Computer Science and Mobile Computing, Vol.3 Issue.6, June- 2014, pg. 816-824
-Available Online at www.ijcsmc.com
-International Journal of Computer Science and Mobile Computing
-A Monthly Journal of Computer Science and Information Technology
-ISSN 2320–088X
-IJCSMC, Vol. 3, Issue. 6, June 2014, pg.816 – 824
-RESEARCH ARTICLE
-A Practical Approach for Determination
-of Human Gender & Age
-Harpreet Kaur Bhatia1, Ahsan Hussain2
-CSE Dept. & CSVTU University, India
-CSE Dept. & CSVTU University, India"
 75827a2021ac2ad2256144b2a2fe301948d39b51,AI Benchmark: Running Deep Neural Networks on Android Smartphones,"AI Benchmark: Running Deep Neural Networks
 on Android Smartphones
 Andrey Ignatov
@@ -9056,14 +7781,6 @@ Jianan Li Xiaodan Liang Yunchao Wei
 Tingfa Xu
 Jiashi Feng
 Shuicheng Yan"
-75a92d92ee59555c847973a7422d7356514cde2d,Exploiting Multiple Detections for Person Re-Identification,"Article
-Exploiting Multiple Detections for
-Person Re-Identiﬁcation
-Amran Bhuiyan *, Alessandro Perina and Vittorio Murino
-Pattern Analysis and Computer Vision (PAVIS), Istituto Italiano di Tecnologia, Via Morego 30,
-6163 Genova, Italy; (A.P.); (V.M.)
-* Correspondence: Tel.: +39-331-803-7176
-Received: 18 November 2017; Accepted: 11 January 2018; Published: 23 January 2018"
 75879ab7a77318bbe506cb9df309d99205862f6c,Analysis of emotion recognition from facial expressions using spatial and transform domain methods,"Analysis Of Emotion Recognition From Facial
 Expressions Using Spatial And Transform Domain
 Methods
@@ -9122,21 +7839,11 @@ August 2, 2017"
 978-1-4799-2893-4/14/$31.00 ©2014 IEEE
 Long Xu1, Chen Gong1, Jie Yang1(cid:3), Qiang Wu2, Lixiu Yao1
 . INTRODUCTION"
-75cf72819b8741777a961157f43d994238219f5e,Crowd Behavior Detection for Abnormal Conditions,"International Journal of Computer Systems (ISSN: 2394-1065), Volume 03– Issue 06, June, 2016
-Available at http://www.ijcsonline.com/
-Crowd Behavior Detection for Abnormal Conditions
-Aniket A. Patil, Prof. S. A. Shinde
-Department of Computer Engineering,
-Savitribai Phule Pune University, Pune, India"
 75e4efae6de6d1ac787a6ca381fb49381fcb062b,Hierarchical Representation Learning for Kinship Verification,"IEEE TRANSACTIONS ON IMAGE PROCESSING
 Hierarchical Representation Learning for Kinship
 Veriﬁcation
 Naman Kohli, Student Member, IEEE, Mayank Vatsa, Senior Member, IEEE, Richa Singh, Senior Member, IEEE,
 Afzel Noore, Senior Member, IEEE, and Angshul Majumdar, Senior Member, IEEE"
-7557e81c1189f0ef9643519e0664d60baed51721,Robust and Efficient Graph Correspondence Transfer for Person Re-identification,"DRAFT
-Transfer for Person Re-identiﬁcation
-Qin Zhou, Heng Fan, Hua Yang, Member, IEEE, Hang Su, Member, IEEE, Shibao Zheng, Member, IEEE,
-Shuang Wu, and Haibin Ling, Member, IEEE"
 75cb21fa931e957941c0237a1030aa36209bae36,GAUSSIAN PROCESS FOR ACTIVITY MODELING AND ANOMALY DETECTION,"GAUSSIAN PROCESS FOR ACTIVITY MODELING AND ANOMALY DETECTION
 Wentong Liaoa, Bodo Rosenhahna, Michael Ying Yangb
 Institute for Information Processing, Leibniz University Hannover, Germany
@@ -9182,16 +7889,6 @@ Zenilton Kleber Gonçalves do Patrocínio Júnior 2
 Silvio Jamil Ferzoli Guimarães 2"
 cc5a62bd7c45a9ca479506acb572566331354fa3,Eye localization through multiscale sparse dictionaries,"Eye Localization through Multiscale Sparse Dictionaries
 Fei Yang, Junzhou Huang, Peng Yang and Dimitris Metaxas"
-ccf5852bfb55e1fa6760f76139ab44dab89f2a17,"Recognize Faces across MultiView Videos and under Varying Illumination , Facial Expressions","Recognize Faces across Multi-View Videos and
-under Varying Illumination, Facial Expressions
-Research Scholar, Dept. Electronics & Communication Engineering,
-Mr. Steven Lawrence Fernandes1
-Karunya University,
-Coimbatore, Tamil Nadu, India
-Professor, Dept. Electronics & Communication Engineering,
-Dr. G. Josemin Bala2
-Karunya University,
-Coimbatore, Tamil Nadu, India"
 cc09cf5831fcae802ed2905a61ab502956655bbe,Shape-based instance detection under arbitrary viewpoint,"Shape-based instance detection under arbitrary
 viewpoint
 Edward Hsiao and Martial Hebert"
@@ -9213,15 +7910,6 @@ we present ways to apply these techniques to Database
 Cinema and other aspects of film and video creation.
 PROJECT DATE 2014
 URL http://misharabinovich.com/soyummy.html"
-cc8e378fd05152a81c2810f682a78c5057c8a735,Expression Invariant Face Recognition System based on Topographic Independent Component Analysis and Inner Product Classifier,"International Journal of Computer Sciences and Engineering    Open Access
-Research Paper                                          Volume-5, Issue-12                                          E-ISSN: 2347-2693
-Expression Invariant Face Recognition System based on Topographic
-Independent Component Analysis and Inner Product Classifier
-Aruna Bhat
-Department of Electrical Engineering, IIT Delhi, New Delhi, India
-*Corresponding Author:
-Available online at: www.ijcseonline.org
-Received: 07/Nov/2017, Revised: 22/Nov/2017, Accepted: 14/Dec/2017, Published: 31/Dec/2017"
 cc91001f9d299ad70deb6453d55b2c0b967f8c0d,Performance Enhancement of Face Recognition in Smart TV Using Symmetrical Fuzzy-Based Quality Assessment,"OPEN ACCESS
 ISSN 2073-8994
 Article
@@ -9267,14 +7955,6 @@ ny patent, copyright, trademark or other property or proprietary rights.
 UWE accepts no liability for any infringement of intellectual property rights
 in any material deposited but will remove such material from public view pend-
 ing investigation in the event of an allegation of any such infringement."
-ccf43c62e4bf76b6a48ff588ef7ed51e87ddf50b,Nutraceuticals and Cosmeceuticals for Human Beings – An Overview,"American Journal of Food Science and Health
-Vol. 2, No. 2, 2016, pp. 7-17
-http://www.aiscience.org/journal/ajfsh
-ISSN: 2381-7216 (Print); ISSN: 2381-7224 (Online)
-Nutraceuticals and Cosmeceuticals for Human
-Beings–An Overview
-R. Ramasubramania Raja*
-Department of Pharmacognosy, Narayana Pharmacy College, Nellore, India"
 cca228b47a603a9b9e2a1e3a1b278b35612d078d,Randomized Face Recognition on Partially Occluded Images,"Randomized Face Recognition on Partially
 Occluded Images
 Ariel Morelli Andres, Sebastian Padovani, Mariano Tepper, Marta Mejail, and
@@ -9285,18 +7965,6 @@ cc9f473584c1a7f224b42d4a3a3ea2864173cc28,Hephaestus: Data Reuse for Accelerating
 Accelerating Scientiﬁc Discovery
 Jennie Duggan
 Northwestern EECS"
-cc5d91b20c8769d1f040ff9a5166f76cc19d2d55,Self-Supervised Learning of Visual Features through Embedding Images into Text Topic Spaces,"Self-supervised learning of visual features through embedding images into text
-topic spaces
-Lluis Gomez∗
-Computer Vision Center, UAB, Spain
-Marc¸al Rusi˜nol
-Computer Vision Center, UAB, Spain
-Yash Patel∗
-CVIT, KCIS, IIIT Hyderabad, India
-Dimosthenis Karatzas
-Computer Vision Center, UAB, Spain
-C.V. Jawahar
-CVIT, KCIS, IIIT Hyderabad, India"
 cca198ae698e7956992f2fb326c04965b2964a18,Learning Pain from Emotion: Transferred HoT Data Representation for Pain Intensity Estimation,"Learning Pain from Emotion: Transferred HoT
 Data Representation for Pain Intensity
 Estimation
@@ -9311,15 +7979,6 @@ Yuejun Guo, Qing Xu(cid:3), Yu Yang, Sheng Liang, Yu Liu, Mateu Sbert"
 cc96eab1e55e771e417b758119ce5d7ef1722b43,An Empirical Study of Recent Face Alignment Methods,"An Empirical Study of Recent
 Face Alignment Methods
 Heng Yang, Xuhui Jia, Chen Change Loy and Peter Robinson"
-ccfcbf0eda6df876f0170bdb4d7b4ab4e7676f18,A Dynamic Appearance Descriptor Approach to Facial Actions Temporal Modeling,"JOURNAL OF LATEX CLASS FILES, VOL. 6, NO. 1, JUNE 2011
-A Dynamic Appearance Descriptor Approach to
-Facial Actions Temporal Modelling
-Bihan Jiang, Student Member, IEEE, Michel Valstar, Member, IEEE, Brais Martinez, Member, IEEE, and
-Maja Pantic, Fellow, IEEE"
-cc2df3a03ee731478ed48838c284ad4548563308,Towards a Better Metric for Evaluating Question Generation Systems,"Towards a Better Metric for Evaluating Question Generation Systems
-Preksha Nema†‡ Mitesh M. Khapra†‡
-IIT Madras, India
-Robert Bosch Center for Data Science and Artiﬁcial Intelligence, IIT Madras"
 cc3e1a6376928138dff5582b7a56d40cfb3b7367,Cost-Effective Features for Reidentification in Camera Networks,"Cost-effective features for
 re-identiﬁcation in camera networks
 Syed Fahad Tahir and Andrea Cavallaro"
@@ -9349,10 +8008,6 @@ destin´ee au d´epˆot et `a la diffusion de documents
 scientiﬁques de niveau recherche, publi´es ou non,
 ´emanant des ´etablissements d’enseignement et de
 recherche fran¸cais ou ´etrangers, des laboratoires"
-cc392ab1cfaee298e05488a4a1d84ece12220880,A new multi-scale fuzzy model for Histogram-Based Descriptors,"A NEW MULTI-SCALE FUZZY MODEL FOR HISTOGRAM-BASED DESCRIPTORS
-Lunshao Chaia, Zhen Qinb, Honggang Zhanga, Jun Guoa, Bir Bhanub
-Beijing University of Posts and Telecomuunictions, Beijing, 100876, China
-University of California at Riverside, Riverside, CA 92521, USA"
 cca2bee0973e347efd7b3d145b6d23286c801bd1,VoCMex: a voice corpus in Mexican Spanish for research in speaker recognition,"Int J Speech Technol
 DOI 10.1007/s10772-012-9183-z
 VoCMex: a voice corpus in Mexican Spanish for research
@@ -9377,15 +8032,6 @@ Jamal Kharroubi
 Faculty of Technical Sciences
 B.P. 2202 – Road of Imouzzer
 Fez – Morocco"
-cc31db984282bb70946f6881bab741aa841d3a7c,Learning Grimaces by Watching TV,"ALBANIE, VEDALDI: LEARNING GRIMACES BY WATCHING TV
-Learning Grimaces by Watching TV
-Samuel Albanie
-http://www.robots.ox.ac.uk/~albanie
-Andrea Vedaldi
-http://www.robots.ox.ac.uk/~vedaldi
-Engineering Science Department
-Univeristy of Oxford
-Oxford, UK"
 ccd99008d942b890cecd308a31ba61240eac9e54,Learning to Segment Every Thing,"Learning to Segment Every Thing
 Ronghang Hu1,2,∗
 Piotr Doll´ar2 Kaiming He2
@@ -9534,27 +8180,15 @@ Thomas G. Dietterich"
 via Spatio-Temporal Video Bundles Grouping
 Technical Report, November 2013
 Yongyi Lu, Liang Lin, Yuanlu Xu, Zefeng Lai"
-9595a267de2b0ecf7e4e2962a606c8854551e203,On the Relation between Color Image Denoising and Classification,"On the Relation between Color Image Denoising
-nd Classiﬁcation
-Jiqing Wu, Radu Timofte, Member, IEEE, Zhiwu Huang, Member, IEEE, and Luc Van Gool, Member, IEEE"
 95029b1041a169e5b4e1ad79f60bfedb7a6844d0,Learning Superpixels with Segmentation-Aware Affinity Loss,"Learning Superpixels with Segmentation-Aware Afﬁnity Loss
 Wei-Chih Tu1 Ming-Yu Liu2 Varun Jampani2 Deqing Sun2 Shao-Yi Chien1 Ming-Hsuan Yang2
 Jan Kautz2
 National Taiwan University 2NVIDIA 3UC Merced"
-956c634343e49319a5e3cba4f2bd2360bdcbc075,A novel incremental principal component analysis and its application for face recognition,"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 36, NO. 4, AUGUST 2006
-A Novel Incremental Principal Component Analysis
-nd Its Application for Face Recognition
-Haitao Zhao, Pong Chi Yuen, Member, IEEE, and James T. Kwok, Member, IEEE"
 9513503867b29b10223f17c86e47034371b6eb4f,Comparison of Optimisation Algorithms for Deformable Template Matching,"Comparison of optimisation algorithms for
 deformable template matching
 Vasileios Zografos
 Link¨oping University, Computer Vision Laboratory
 ISY, SE-581 83 Link¨oping, SWEDEN"
-95ace502ba23a8a5543b882937de23b892112cca,Facial Dynamics Interpreter Network: What Are the Important Relations Between Local Dynamics for Facial Trait Estimation?,"Facial Dynamics Interpreter Network: What are
-the Important Relations between Local
-Dynamics for Facial Trait Estimation?
-Seong Tae Kim and Yong Man Ro*
-School of Electrical Engineering, KAIST, Daejeon, Republic of Korea"
 95f990600abb9c8879e4f5f7cd03f3d696fcdec4,An Online Algorithm for Constrained Face Clustering in Videos,"Manuscript version: Author’s Accepted Manuscript
 The version presented in WRAP is the author’s accepted manuscript and may differ from the
 published version or Version of Record.
@@ -9575,24 +8209,6 @@ Copies of full items can be used for personal research or study, educational, or
 purposes without prior permission or charge. Provided that the authors, title and full
 ibliographic details are credited, a hyperlink and/or URL is given for the original metadata
 page and the content is not changed in any way."
-951f21a5671a4cd14b1ef1728dfe305bda72366f,Use of l2/3-norm Sparse Representation for Facial Expression Recognition,"International Journal of Science and Research (IJSR)
-ISSN (Online): 2319-7064
-Impact Factor (2012): 3.358
-Use of ℓ2/3-norm Sparse Representation for Facial
-Expression Recognition
-Sandeep Rangari1, Sandeep Gonnade2
-MATS University, MATS School of Engineering and Technology, Arang, Raipur, India
-MATS University, MATS School of Engineering and Technology, Arang, Raipur, India
-three
-to  discriminate
-represents  emotion,"
-959bcb16afdf303c34a8bfc11e9fcc9d40d76b1c,Temporal Coherency based Criteria for Predicting Video Frames using Deep Multi-stage Generative Adversarial Networks,"Temporal Coherency based Criteria for Predicting
-Video Frames using Deep Multi-stage Generative
-Adversarial Networks
-Prateep Bhattacharjee1, Sukhendu Das2
-Visualization and Perception Laboratory
-Department of Computer Science and Engineering
-Indian Institute of Technology Madras, Chennai, India"
 951af0494e8812fdb7d578b68c342ab876acb27e,DOCTEUR DE L’ECOLE NORMALE SUPERIEURE DE CACHAN,"THÈSEDEDOCTORATDEL’ÉCOLENORMALESUPÉRIEUREDECACHANprésentéeparJULIENMAIRALpourobtenirlegradedeDOCTEURDEL’ÉCOLENORMALESUPÉRIEUREDECACHANDomaine:MATHÉMATIQUESAPPLIQUÉESSujetdelathèse:Représentationsparcimonieusesenapprentissagestatistique,traitementd’imageetvisionparordinateur—Sparsecodingformachinelearning,imageprocessingandcomputervisionThèseprésentéeetsoutenueàCachanle30novembre2010devantlejurycomposéde:FrancisBACHDirecteurderecherche,INRIAParis-RocquencourtDirecteurdethèseStéphaneMALLATProfesseur,EcolePolytechnique,New-YorkUniversityRapporteurEricMOULINESProfesseur,Télécom-ParisTechExaminateurBrunoOLSHAUSENProfesseur,UniversityofCalifornia,BerkeleyRapporteurJeanPONCEProfesseur,EcoleNormaleSupérieure,ParisDirecteurdethèseGuillermoSAPIROProfesseur,UniversityofMinnesotaExaminateurJean-PhilippeVERTDirecteurderecherche,EcolesdesMines-ParisTechExaminateurThèsepréparéeauseindel’équipeWillowdulaboratored’informatiquedel’ÉcoleNormaleSupérieure,Paris.(INRIA/ENS/CNRSUMR8548).23avenued’Italie,75214Paris."
 95225bab187483e37823daab5c503f6b327fb008,Improved MinMax Cut Graph Clustering with Nonnegative Relaxation,"Improved MinMax Cut Graph Clustering with
 Nonnegative Relaxation
@@ -9625,19 +8241,6 @@ Davide Baltieri, Roberto Vezzani, Rita Cucchiara
 University of Modena and Reggio Emilia
 Via Vignolese 905, 41125 Modena - Italy
 {davide.baltieri, roberto.vezzani,"
-954909051c1d7d5a8ba885f1c09afe04c8aab0fb,IGCV3: Interleaved Low-Rank Group Convolutions for Efficient Deep Neural Networks,"STUDENT, PROF, COLLABORATOR: BMVC AUTHOR GUIDELINES
-IGCV3: Interleaved Low-Rank Group
-Convolutions for Efﬁcient Deep Neural
-Networks
-University of Science and Technology
-of China
-Anhui, China
-Microsoft Research Asia,
-Beijing, China
-Ke Sun1
-Mingjie Li1
-Dong Liu1
-Jingdong Wang2"
 95593fb20df8ce1273cebe0690cf2cdab054b9b5,Robust Multi-Image HDR Reconstruction for the Modulo Camera,
 95ea564bd983129ddb5535a6741e72bb1162c779,Multi-Task Learning by Deep Collaboration and Application in Facial Landmark Detection,"Multi-Task Learning by Deep Collaboration and
 Application in Facial Landmark Detection
@@ -9658,46 +8261,6 @@ Explaining Potential Risks in Traffic Scenes by Combining
 Logical Inference and Physical Simulation
 Ryo Takahashi, Naoya Inoue, Yasutaka Kuriya, Sosuke Kobayashi, and Kentaro Inui
 from  observation  and"
-95fb31beaa745557fa33ec4f670ab4e130ff5bf4,Speeding up spatial approximation search in metric spaces,"Speeding up Spatial Approximation Search
-in Metric Spaces
-KARINA FIGUEROA
-Universidad Michoacana, Mexico
-EDGAR CHAVEZ
-Universidad Michoacana / CICESE, Mexico
-GONZALO NAVARRO
-RODRIGO PAREDES
-University of Chile, Chile
-Proximity searching consists in retrieving from a database those elements that are similar to a
-query object. The usual model for proximity searching is a metric space where the distance,
-which models the proximity, is expensive to compute. An index uses precomputed distances to
-speed up query processing. Among all the known indices, the baseline for performance for about
-twenty years has been AESA. This index uses an iterative procedure, where at each iteration it
-ﬁrst chooses the next promising element (“pivot”) to compare to the query, and then it discards
-database elements that can be proved not relevant to the query using the pivot. The next pivot
-in AESA is chosen as the one minimizing the sum of lower bounds to the distance to the query
-proved by previous pivots. In this paper we introduce the new index iAESA, which establishes a
-new performance baseline for metric space searching. The difference with AESA is the method
-to select the next pivot. In iAESA, each candidate sorts previous pivots by closeness to it, and"
-c86e6ed734d3aa967deae00df003557b6e937d3d,Generative Adversarial Networks with Decoder-Encoder Output Noise,"Generative Adversarial Networks with
-Decoder-Encoder Output Noise
-Guoqiang Zhong, Member, IEEE, Wei Gao, Yongbin Liu, Youzhao Yang
-onditional distribution of their neighbors. In [32], Portilla and
-Simoncelli proposed a parametric texture model based on joint
-statistics, which uses a decomposition method that is called
-steerable pyramid decomposition to decompose the texture
-of images. An example-based super-resolution algorithm [11]
-was proposed in 2002, which uses a Markov network to model
-the spatial relationship between the pixels of an image. A
-scene completion algorithm [16] was proposed in 2007, which
-pplied a semantic scene match technique. These traditional
-lgorithms can be applied to particular image generation tasks,
-such as texture synthesis and super-resolution. Their common
-haracteristic is that they predict the images pixel by pixel
-rather than generate an image as a whole, and the basic idea
-of them is to make an interpolation according to the existing
-part of the images. Here, the problem is, given a set of images,
-an we generate totally new images with the same distribution
-of the given ones?"
 c81b303005459285a5864ea4de71f77025cd5be5,Norm-Induced Entropies for Decision Forests,"Norm-induced entropies for decision forests
 Christoph Lassner
 Rainer Lienhart
@@ -9736,18 +8299,6 @@ c8f216dbd43dda14783677f44bb336c92211cd46,Synthesis from 3 D Mesh Sequences Drive
 SPEECH FEATURES
 Felix Kuhnke and J¨orn Ostermann
 Institut f¨ur Informationsverarbeitung, Leibniz Universit¨at Hannover, Germany"
-c896946612069f162864edfbecf5c1a8a077ed79,The Image Multi Feature Retrieval based on SVM Semantic Classification,"International Journal of Hybrid Information Technology
-Vol.9, No.3 (2016), pp. 291-300
-http://dx.doi.org/10.14257/ijhit.2016.9.3.27
-The Image Multi Feature Retrieval based on SVM Semantic
-Classification
-Che Chang1,2*, Yu Xiaoyang1 and Bai Yamei3
-. Measuring and Control Technology and Instrumentations,Harbin University of
-Science and Technology, Harbin, China
-. School of Engineering,Harbin University, Harbin, China
-. School of  Electronic and Information Engineering,Harbin Huade University
-Harbin, China
-E-mail:"
 c88a1d52d92a47704a797fce2202970bb1f2008c,RECOGNIZING FACE SKETCHES BY HUMAN VOLUNTEERS,"RECOGNIZING FACE SKETCHES BY HUMAN VOLUNTEERS
 Priyanka Reddy Gangam
 Submitted in Partial Fulfillment of the Requirements
@@ -9794,15 +8345,6 @@ I. INTRODUCTION
 With computers to handle more and more complicated
 things in variable environments like driverless car and ad-
 vanced medical diagnosis expert system, higher artiﬁcial intel-"
-c84233f854bbed17c22ba0df6048cbb1dd4d3248,Exploring Locally Rigid Discriminative Patches for Learning Relative Attributes,"Y. VERMA, C. V. JAWAHAR: EXPLORING PATCHES FOR RELATIVE ATTRIBUTES
-Exploring Locally Rigid Discriminative
-Patches for Learning Relative Attributes
-Yashaswi Verma
-http://researchweb.iiit.ac.in/~yashaswi.verma/
-C. V. Jawahar
-http://www.iiit.ac.in/~jawahar/
-IIIT-Hyderabad, India
-http://cvit.iiit.ac.in"
 c8855bebdaa985dfc4c1a07e5f74a0e29787e47e,Multi-label Object Attribute Classification using a Convolutional Neural Network,"Multi-label Object Attribute Classiﬁcation using
 Convolutional Neural Network
 Soubarna Banik, Mikko Lauri, Simone Frintrop
@@ -9844,15 +8386,6 @@ Xirong Li(cid:63)1, Qin Jin(cid:63)1, Shuai Liao1, Junwei Liang1, Xixi He1, Yuji
 Weiyu Lan1, Bin Xiao2, Yanxiong Lu2, Jieping Xu1
 Multimedia Computing Lab, School of Information, Renmin University of China
 Pattern Recognition Center, WeChat Technical Architecture Department, Tencent"
-c8012c6d71c286777b7a818c4cadb540d8549b43,Diagnosis of Esophagitis Based on Face Recognition Techniques,"The Open Medical Informatics Journal, 2010, 4, 58-62
-Open Access
-Diagnosis of Esophagitis Based on Face Recognition Techniques
-Santosh S. Saraf
-*,1, Gururaj R. Udupi2 and Santosh D. Hajare3
-Research  Center,  Department  of  Electronics  and  Communications  Engg.,  Gogte  Institute  of  Technology,  Belgaum,
-India
-Vishwanathrao Deshpande Rural Institute of Technology, Haliyal, India
-Department of Gastroenterology, K.L.E. Prabhakar Kore Hospital and Research Center, Belgaum, India"
 c840d85f6dce0fb69fb6113923f17e1e314c6134,Disparity Sliding Window: Object Proposals From Disparity Images,"Disparity Sliding Window: Object Proposals From Disparity Images
 Julian M¨uller1, Andreas Fregin2 and Klaus Dietmayer1"
 c8db8764f9d8f5d44e739bbcb663fbfc0a40fb3d,Modeling for part-based visual object detection based on local features,"Modeling for part-based visual object
@@ -9946,14 +8479,6 @@ Peng Wang, Ruigang Yang, Binbin Cao, Wei Xu, Yuanqing Lin
 Baidu Research
 National Engineering Laboratory for Deep Learning Technology and Applications
 {wangpeng54, yangruigang, caobinbin, wei.xu,"
-c81ee278d27423fd16c1a114dcae486687ee27ff,Search Based Face Annotation Using Weakly Labeled Facial Images,"Search Based Face Annotation Using Weakly
-Labeled Facial Images
-Shital Shinde1, Archana Chaugule2
-Computer Department, Savitribai Phule Pune University
-D.Y.Patil Institute of Engineering and Technology, Pimpri, Pune-18
-Mahatma Phulenagar, 120/2 Mahaganpati soc, Chinchwad, Pune-19, MH, India
-D.Y.Patil Institute of Engineering and Technology, Pimpri, Pune-18, Savitribai Phule Pune University
-DYPIET, Pimpri, Pune-18, MH, India"
 c8fc65c83473c633e2bf1c13031ccd10617cc8a2,Every Object Tells a Story,"Every Object Tells a Story
 James Pustejovsky
 Computer Science Department
@@ -10003,21 +8528,12 @@ Adobe Research"
 693905c29feb7f9be3517308c8a9c2dc68aa8682,Self-supervised CNN for Unconstrained 3D Facial Performance Capture from an RGB-D Camera,"Self-supervised CNN for Unconstrained 3D Facial
 Performance Capture from an RGB-D Camera
 Yudong Guo, Juyong Zhang†, Lin Cai, Jianfei Cai and Jianmin Zheng"
-69063f7e0a60ad6ce16a877bc8f11b59e5f7348e,Class-Specific Image Deblurring,"Class-Speciﬁc Image Deblurring
-Saeed Anwar1, Cong Phuoc Huynh1
-, Fatih Porikli1
-The Australian National University∗ Canberra ACT 2601, Australia
-NICTA, Locked Bag 8001, Canberra ACT 2601, Australia"
 699b6cbd72ee0274699b939863813499c377ea00,Enlightening Deep Neural Networks with Knowledge of Confounding Factors,"Enlightening Deep Neural Networks
 with Knowledge of Confounding Factors
 Yu Zhong
 Gil Ettinger
 {yu.zhong,
 Systems & Technology Research"
-6960bfc668aad1b537fbf3f1b48328e7d440b80b,Fully Automatic Recognition of the Temporal Phases of Facial Actions,"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 42, NO. 1, FEBRUARY 2012
-Fully Automatic Recognition of the
-Temporal Phases of Facial Actions
-Michel F. Valstar, Member, IEEE, and Maja Pantic, Senior Member, IEEE"
 6957baa0db5576997aef9de43b93fe8fd4d07632,Identifica\c{c}\~ao autom\'atica de picha\c{c}\~ao a partir de imagens urbanas,"Identiﬁcac¸˜ao autom´atica de pichac¸˜ao a partir de
 imagens urbanas
 Eric K. Tokuda and Roberto M. Cesar-Jr.
@@ -10067,10 +8583,6 @@ obtained from a single vision sensor. Unlike typical multimodal biometric system
 utilizes gesture video signals combined with facial images. Whereas physical information such as face, fingerprints, and iris is fixed
 nd not changeable, behavioral information such as gestures and signatures can be freely changed by the user, similar to a password.
 Therefore, it can be a countermeasure when the physical information is exposed. We aim to investigate the potential possibility of"
-6903496ee5d4c24ca5f3f18211f406e0ba8442d6,Multi-Mapping Image-to-Image Translation with Central Biasing Normalization,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2018
-Multi-Mapping Image-to-Image Translation with
-Central Biasing Normalization
-Xiaoming Yu, Zhenqiang Ying, Student Member, IEEE, Thomas Li, Shan Liu, and Ge Li, Member, IEEE,"
 69c03f69ddf77586f83bf13d473abf53a70e6793,"EigenFaces Image normalization : rotation , scale and intensity Eye coordinates + input frame Voting method Person identity DCT HMM Face extraction Recognition Modules","Lemieux & Parizeau, Vision Interface 2003.
 Flexible multi-classiﬁer architecture for
 face recognition systems
@@ -10146,17 +8658,6 @@ Sheryl Brahnam
 Computer Information Systems Department
 Southwest Missouri State University
 Springfield, MO 65804"
-69a55c30c085ad1b72dd2789b3f699b2f4d3169f,Automatic Happiness Strength Analysis of a Group of People using Facial Expressions,"International Journal of Computer Trends and Technology (IJCTT) – Volume 34 Number 3 - April 2016
-Automatic Happiness Strength Analysis of a
-Group of People using Facial Expressions
-Sagiri Prasanthi#1, Maddali M.V.M. Kumar*2,
-#1PG Student, #2Assistant Professor
-#1, #2Department of MCA, St. Ann’s College of Engineering & Technology, Andhra Pradesh, India
-is  a  collective  concern"
-691eb8eb9f5d5fbf5d76349098b78e5d6fc25ccc,Deep Learning of Part-Based Representation of Data Using Sparse Autoencoders With Nonnegativity Constraints,"Deep Learning of Part-based Representation of Data
-Using Sparse Autoencoders with Nonnegativity
-Constraints
-Ehsan Hosseini-Asl, Member, IEEE, Jacek M. Zurada, Life Fellow, IEEE, Olfa Nasraoui, Senior Member, IEEE"
 690d669115ad6fabd53e0562de95e35f1078dfbb,"Progressive versus Random Projections for Compressive Capture of Images, Lightfields and Higher Dimensional Visual Signals","Progressive versus Random Projections for Compressive Capture of Images,
 Lightﬁelds and Higher Dimensional Visual Signals
 Rohit Pandharkar
@@ -10167,15 +8668,6 @@ Ashok Veeraraghavan
 Ramesh Raskar
 MIT Media Lab
 75 Amherst St, Cambridge, MA"
-69c8b0ec77d3164df2069a5133780a36ec8e91ad,Unsupervised 3D Reconstruction from a Single Image via Adversarial Learning,"Unsupervised 3D Reconstruction from a Single Image via Adversarial Learning
-Lingjing Wang
-NYU Multimedia and Visual Computing Lab
-Courant Institute of Mathematical Science
-NYU Tandon School of Engineering, USA
-Yi Fang ∗
-NYU Multimedia and Visual Computing Lab
-Dept. of ECE, NYU Abu Dhabi, UAE
-Dept. of ECE, NYU Tandon School of Engineering, USA"
 695f6dc7165aa3fca15d1b1deb4c496fc093ac19,Learning Discriminative Visual N-grams from Mid-level Image Features.,"GUPTA, PANDEY, CHIA: VISUAL N-GRAMS
 Learning Discriminative Visual N-grams
 from Mid-level Image Features
@@ -10191,17 +8683,6 @@ Singapore
 Rakuten Institute of Technology
 Singapore"
 69f27ca2f1280587004c8fae6b3b0021305e52eb,Title of dissertation : Scene and Video Understanding,
-69447482c6d7d0fde4001231ca84c31f866a2d5d,Survey of Advanced Facial Feature Tracking and Facial Expression Recognition,"ISSN (Print)    : 2319-5940
-ISSN (Online) : 2278-1021
-International Journal of Advanced Research in Computer and Communication Engineering
-Vol. 2, Issue 10, October 2013
-Survey of Advanced Facial Feature Tracking and
-Facial Expression Recognition
-Karthick.K1, J.Jasmine2
-PG Scholar, Department of Computer science and Technology, Kalaignar Karunanidhi Institute of Technology,
-Coimbatore, Tamilnadu, India1
-Assistant Professor, Department of Computer science and Technology, Kalaignar Karunanidhi Institute of Technology,
-Coimbatore, Tamilnadu, India2"
 695b040a9550a46b5ffe31e4a6abbadfac02c1ad,Face recognition with illumination distinction description,"1st International Conference on Pattern Recognition (ICPR 2012)
 November 11-15, 2012. Tsukuba, Japan
 978-4-9906441-1-6 ©2012 IAPR"
@@ -10243,13 +8724,6 @@ Matthias Nießner1
 Technical University of Munich
 University Federico II of Naples
 University of Erlangen-Nuremberg"
-695e4c975740d2aedcfc42d7ec445b4b2b56cbeb,Principal Component Analysis : An Efficient Facial Feature Extraction Technique,"SSRG International Journal of Electronics and Communication Engineering - (ICRTESTM) - Special Issue – April 2017
-Principal Component Analysis: An Efficient
-Facial Feature Extraction Technique
-Research scholar, ECE Dept, JJTU, Rajasthan, India, 333001(Associate Professor, SVIT, Secunderabad-500
-Drakshayani Desai, 2Dr. Ramakrishna Seemakurti.
-Research Guide (Pricipal,, SVIT, Secunderabd, India, 500003) (Approved Research Guide, JJTU, Jhunjhunu-
-33001, Rajasthan, India)"
 6971bdac5119c4cc1b6d92adac605e13f1bcd80f,Limiting the reconstruction capability of generative neural network using negative learning,"LIMITING THE RECONSTRUCTION CAPABILITY OF GENERATIVE NEURAL NETWORK
 USING NEGATIVE LEARNING
 Asim Munawar, Phongtharin Vinayavekhin and Giovanni De Magistris
@@ -10434,15 +8908,6 @@ d50e51d0a349dd904b85734083e59643ba99bd2c,A Robust Face Recognition method,"Inter
 ISSN 2229-5518
 A Robust Face Recognition method
 G.Seshikala,U.P.Kulakrni,M.N.GiriPrasad"
-d54f508c943b8415bfdd30d9210869ec93ff3f03,A method of illumination compensation for human face image based on quotient image q,"Available online at www.sciencedirect.com
-Information Sciences 178 (2008) 2705–2721
-www.elsevier.com/locate/ins
-A method of illumination compensation for human face
-image based on quotient image q
-Wang Ying-hui a,b, Ning Xiao-juan a,*, Yang Chun-xia a, Wang Qiong-fang b
-School of Computer Science Engineering, Xi’an University of Technology, Xi’an 710048, China
-Department of Computer Science, Shaanxi Normal University, Xi’an 710062, China
-Received 23 February 2007; received in revised form 2 December 2007; accepted 14 December 2007"
 d5579b2708a1c713e1b2feb8646533ce26085a3a,Effective Use of Dilated Convolutions for Segmenting Small Object Instances in Remote Sensing Imagery,"Effective Use of Dilated Convolutions for Segmenting Small Object Instances in
 Remote Sensing Imagery
 Ryuhei Hamaguchi  Aito Fujita  Keisuke Nemoto
@@ -10474,26 +8939,6 @@ different angles and which may also be partially occluded. Speciﬁcally, face r
 respect to the following factors [19]:
 . face image resolution – face images can be captured at different resolutions: face images scanned from documents may
 have very high resolution, while face images captured with a video camera will mostly be of very low resolution,"
-d59f18fcb07648381aa5232842eabba1db52383e,Robust Facial Expression Recognition using Spatially Localized Geometric Model 125 2 . IDENTIFICATION OF FEATURE REGIONS,"International Conference on Systemics, Cybernetics and Informatics, February 12–15, 2004
-ROBUST FACIAL EXPRESSION RECOGNITION USING SPATIALLY
-LOCALIZED GEOMETRIC MODEL
-Department of Electrical Engineering
-Dept. of Computer Sc. and Engg.
-Ashutosh Saxena
-IIT Kanpur
-Kanpur 208016, India
-Kanpur 208016, India
-Ankit Anand
-IIT Kanpur
-Prof. Amitabha Mukerjee
-Dept. of Computer Sc. and Engg.
-IIT Kanpur
-Kanpur 208016, India
-While  approaches  based  on  3D  deformable  facial  model  have
-chieved expression recognition rates of as high as 98% [2], they
-re  computationally  inefficient  and  require  considerable  apriori
-training  based  on  3D  information,  which  is  often  unavailable.
-Recognition  from  2D  images  remains  a  difficult  yet  important"
 d5d3c1b299e81b4ab96d052f8a37013305b731d9,Performance Evaluation of Human Detection Systems for Robot Safety,"J Intell Robot Syst
 DOI 10.1007/s10846-016-0334-3
 Performance Evaluation of Human Detection Systems
@@ -10606,10 +9051,6 @@ Face Synthesis from Visual Attributes via Sketch using
 Conditional VAEs and GANs
 Xing Di · Vishal M. Patel
 Received: date / Accepted: date"
-d5cdcaa19a62e3cb97da013555b99fe35e724e38,Improved ArtGAN for Conditional Synthesis of Natural Image and Artwork,"Improved ArtGAN for Conditional Synthesis of
-Natural Image and Artwork
-Wei Ren Tan, Student Member, IEEE, Chee Seng Chan, Senior Member, IEEE,
-Hern´an E. Aguirre, Member, IEEE, and Kiyoshi Tanaka, Member, IEEE"
 d5b83d6b4a3c1093edc9138ab9dfe4e965a80261,Skeleton-Based Action Recognition Using Spatio-Temporal LSTM Network with Trust Gates,"Skeleton-Based Action Recognition Using
 Spatio-Temporal LSTM Network with Trust Gates
 Jun Liu, Amir Shahroudy, Dong Xu, Alex C. Kot, and Gang Wang"
@@ -10672,15 +9113,6 @@ Miaojing Shi1,2
 Holger Caesar1
 University of Edinburgh 2Tencent Youtu Lab
 Vittorio Ferrari1"
-f202c78e58d33a65c19183414ad0ee91be440d61,Investigating the Influence of Biological Sex on the Behavioral and Neural Basis of Face Recognition,"New Research
-Sensory and Motor Systems
-Investigating the Influence of Biological Sex on
-the Behavioral and Neural Basis of Face
-Recognition
-K. Suzanne Scherf,1,2 Daniel B. Elbich,1 and Natalie V. Motta-Mena1
-DOI:http://dx.doi.org/10.1523/ENEURO.0104-17.2017
-Department of Psychology, Pennsylvania State University, University Park, PA 16802, and 2Department of
-Neuroscience, Pennsylvania State University, University Park, PA 16802"
 f22058a3003cee6b17c6c25c8a635a653e78614c,Multimodal Attention in Recurrent Neural Networks for Visual Question Answering,"Global Journal of Computer Science and Technology: D
 Neural & Artificial Intelligence
 Volume 17   Issue 1 Version 1.0 Year 2017
@@ -10794,17 +9226,6 @@ f2fafa5d2c49034ba8f6318f869822b462b33a42,iQIYI-VID: A Large Dataset for Multi-mo
 Yuanliu Liu, Peipei Shi, Bo Peng, He Yan, Yong Zhou, Bing Han, Yi Zheng, Chao Lin,
 Jianbin Jiang,Yin Fan, Tingwei Gao, Ganwen Wang, Jian Liu, Xiangju Lu, Danming Xie
 iQIYI, Inc."
-f22a7a7a8cdd323270d1f8173c0289d61981dc73,Face Recognition System Using Wavelet Normalization,"ISSN(Online): 2319-8753
-ISSN (Print):   2347-6710
-International Journal of Innovative Research in Science,
-Engineering and Technology
-(An ISO 3297: 2007 Certified Organization)
-Vol. 4, Issue 12, December 2015
-Face Recognition System Using
-Wavelet Normalization
-R.Anitha 1, S.Ramila 2
-Assistant Professor, Dept. of CSE, Sri Krishna College of Technology, Coimbatore, India 1
-Assistant Professor, Dept. of CSE, Sri Krishna College of Technology, Coimbatore, India 2"
 f2b547b0bbda1478cbecbd5c184c3c42c3db7e3c,Semi-parametric Image Synthesis,
 f26d34d8a8d082ce2c81937f61c28f3769c38372,Probability of Seeing Increases Saccadic Readiness,"Probability of Seeing Increases Saccadic Readiness
 The´ re` se Collins*
@@ -10840,10 +9261,6 @@ Tobias Hinz and Stefan Wermter ∗
 Universit¨at Hamburg, Department of Informatics, Knowledge Technology
 Vogt-Koelln-Str. 30, 22527 Hamburg, Germany
 http://www.informatik.uni-hamburg.de/WTM/"
-c32383330df27625592134edd72d69bb6b5cff5c,Intrinsic Illumination Subspace for Lighting Insensitive Face Recognition,"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 42, NO. 2, APRIL 2012
-Intrinsic Illumination Subspace for Lighting
-Insensitive Face Recognition
-Chia-Ping Chen and Chu-Song Chen, Member, IEEE"
 c37a971f7a57f7345fdc479fa329d9b425ee02be,A Novice Guide towards Human Motion Analysis and Understanding,"A Novice Guide towards Human Motion Analysis and Understanding
 Dr. Ahmed Nabil Mohamed"
 c3599c91d0e3473178c1578b731b03e4be5d3ff1,Improving Resource Efficiency in Cloud Computing a Dissertation Submitted to the Department of Electrical Engineering and the Committee on Graduate Studies of Stanford University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy,"IMPROVING RESOURCE EFFICIENCY IN CLOUD COMPUTING
@@ -11030,30 +9447,6 @@ Mickaël Chen
 Sorbonne Universités, UPMC Univ Paris 06, UMR 7606, LIP6, F-75005, Paris, France
 Ludovic Denoyer
 Sorbonne Universités, UPMC Univ Paris 06, UMR 7606, LIP6, F-75005, Paris, France"
-c3d60c8b1dff411982ccd8875496f1e74d2cefc4,Multi-view X-ray R-CNN,"Multi-view X-ray R-CNN
-Jan-Martin O. Steitz[0000−0002−3549−312X], Faraz
-Saeedan
-Department of Computer Science, TU Darmstadt, Darmstadt, Germany"
-c3341286ece958e6b05df56d788456b61313380b,Estimating Attention of Faces due to its Growing Level of Emotions,"Estimating Attention of Faces due to its Growing Level of Emotions
-Ravi Kant Kumar*, Jogendra Garain, Dakshina Ranjan Kisku and Goutam Sanyal
-Department of Computer Science and Engineering
-National Institute of Technology
-Durgapur, India
-E-mail: {vit.ravikant, jogs.cse, drkisku,
-imperative
-nd  feeling  [2]  of  a  person  at  that  moment.  Facial
-expression  plays  an
-in  non-verbal
-ommunication as well as to predicting the behavior of the
-person.  During  a  group  discussion,  our  attention
-utomatically  goes  towards  those  participants  who  put
-more  stressed  on  his  words  or  talk  in  a  sentimental  or
-emphatic  voice.  Same  phenomenon  occurs  with  the  non-
-verbal  visual  communication.  The  face  reflecting  the
-higher  expression  of  a  particular  emotion  draws  more
-ttention  [3,  4]  in  the  discussion.  A  particular  object  (It
-lso  may  be  face),  which  gives  us  more  visualization  is
-onsider as a salient object and this phenomenon is called"
 c3ea346826467f04779e55679679c7c7e549c8a2,Learning Short-Cut Connections for Object Counting,"OÑORO-RUBIO, NIEPERT, LÓPEZ-SASTRE: LEARNING SHORT-CUT CONNECTIONS. . .
 Learning Short-Cut Connections for Object
 Counting
@@ -11149,20 +9542,9 @@ c348118690d2e6544ec1e68f904dbf9e5b6397bd,Video-to-Video Synthesis,"Video-to-Vide
 Ting-Chun Wang1, Ming-Yu Liu1, Jun-Yan Zhu2, Guilin Liu1,
 Andrew Tao1, Jan Kautz1, Bryan Catanzaro1
 NVIDIA, 2MIT CSAIL"
-c3bcc4ee9e81ce9c5c0845f34e9992872a8defc0,A New Scheme for Image Recognition Using Higher-Order Local Autocorrelation and Factor Analysis,"MVA2005  IAPR  Conference on Machine VIsion Applications, May 16-18, 2005 Tsukuba Science City, Japan
-A New Scheme for Image Recognition Using Higher-Order Local
-Autocorrelation and Factor Analysis
-Naoyuki Nomotoy, Yusuke Shinoharay, Takayoshi Shirakiy, Takumi Kobayashiy, Nobuyuki Otsuy yyy
-yThe University of Tokyo
-Tokyo, Japan
-yyyAIST
-Tukuba, Japan
-f shiraki, takumi, otsug"
 c3285a1d6ec6972156fea9e6dc9a8d88cd001617,Extreme 3D Face Reconstruction: Seeing Through Occlusions,
 c141b7c4ccb4a0e5d2a327aa260b318c7c3bcfbb,Real-Time Adaptive Image Compression,"Real-Time Adaptive Image Compression
 Oren Rippel * 1 Lubomir Bourdev * 1"
-c1ebbdb47cb6a0ed49c4d1cf39d7565060e6a7ee,Robust Facial Landmark Localization Based on Texture and Pose Correlated Initialization,"Robust Facial Landmark Localization Based on
-Yiyun Pan, Junwei Zhou, Member, IEEE, Yongsheng Gao, Senior Member, IEEE, Shengwu Xiong"
 c1d98fca75c63fd5975fc2fcd3fe07ac02de4a5b,An End-to-End Traffic Vision and Counting System Using Computer Vision and Machine Learning: The Challenges in Real-Time Processing,"SIGNAL 2018 : The Third International Conference on Advances in Signal, Image and Video Processing
 An End-to-End Traffic Vision and Counting System Using Computer Vision and
 Machine Learning: The Challenges in Real-Time Processing
@@ -11183,14 +9565,6 @@ Los Angeles, USA
 Email:
 William Chernicoff
 Toyota Mobility Foundation"
-c175381a6b84ebd0a920ff44ccdccabd98bdfb94,Paper on Retrieval Magnets for Facial Duplication by Search Based Face Annotation,"International Journal of Science and Research (IJSR)
-ISSN (Online): 2319-7064
-Impact Factor (2012): 3.358
-A Review Paper on Retrieval Magnets for Facial
-Duplication by Search Based Face Annotation
-Deepika B. Patil1, Ayesha Butalia 2
-P.G. Student, Department of Computer Engineering, GMRCEM, Wagholi, Pune, India,
-Professor, Department of Computer Engineering, GMRCEM, Wagholi, Pune, India,"
 c18e11d0578dc67e46160afa527e1a9e73b8fa15,Predicting Motion of Vulnerable Road Users using High-Definition Maps and Efficient ConvNets,"Predicting Motion of Vulnerable Road Users
 using High-Deﬁnition Maps and Efﬁcient ConvNets
 Fang-Chieh Chou, Tsung-Han Lin, Henggang Cui, Vladan Radosavljevic,
@@ -11225,9 +9599,6 @@ Prof. Min Chen, BSc, PhD, FBCS, FEG, FLSW
 Tag der mündlichen Prüfung: 27. Mai 2013
 Visualisierungsinstitut
 der Universität Stuttgart"
-c16bae6b2e578df2cba8e436e02bdeda281c2743,Tensor Discriminant Color Space for Face Recognition,"Tensor Discriminant Color Space for Face
-Recognition
-Su-Jing Wang, Jian Yang, Member, IEEE, Na Zhang, and Chun-Guang Zhou*"
 c1ff88493721af1940df0d00bcfeefaa14f1711f,Subspace Regression: Predicting a Subspace from one Sample,"#1369
 CVPR 2010 Submission #1369. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE.
 #1369
@@ -11459,9 +9830,6 @@ Vol:3, No:11, 2009
 Local Steerable Pyramid Binary Pattern Sequence
 LSPBPS for face recognition method
 Mohamed El Aroussi, Mohammed El Hassouni, Sanaa Ghouzali, Mohammed Rziza, and Driss Aboutajdine"
-1ecf4055831ca23c9f6026ef866dac95c8b8f9de,Eye Gaze Tracking With a Web Camera in a Desktop Environment,"Eye Gaze Tracking With a Web Camera
-in a Desktop Environment
-Yiu-ming Cheung, Senior Member, IEEE, and Qinmu Peng, Member, IEEE"
 1eb4ea011a3122dc7ef3447e10c1dad5b69b0642,Contextual Visual Recognition from Images and Videos,"Contextual Visual Recognition from Images and Videos
 Georgia Gkioxari
 Jitendra Malik
@@ -11477,10 +9845,6 @@ Approximate Nearest Neighbor Search?
 Masakazu Iwamura, Tomokazu Sato and Koichi Kise
 Graduate School of Engineering, Osaka Prefecture University
 {masa,"
-1e83e2abcb258cd62b160e3f31a490a6bc042e83,Metric Learning in Codebook Generation of Bag-of-Words for Person Re-identification,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015
-Metric Learning in Codebook Generation of
-Bag-of-Words for Person Re-identiﬁcation
-Lu Tian, Student Member, IEEE, and Shengjin Wang, Member, IEEE"
 1ecb56e7c06a380b3ce582af3a629f6ef0104457,View-invariant face detection method based on local PCA cells,"List of Contents Vol.8
 Contents of
 Journal of Advanced Computational
@@ -11605,18 +9969,6 @@ Contractor and the contents do not necessarily have the approval or endorsement
 Department of National Defence of Canada.
 Defence Research and Development Canada 
 &RQWUDFW5HSRUW"
-1e93ec0f5c29069beedbe7d617f5167b82b70730,Filtering SVM frame-by-frame binary classification in a detection framework,"FILTERING SVM FRAME-BY-FRAME BINARY CLASSIFICATION IN A DETECTION
-FRAMEWORK
-Alejandro Betancourt1,2, Pietro Morerio1, Lucio Marcenaro1, Matthias Rauterberg2, Carlo Regazzoni1
-Information and Signal Processing for Cognitive
-University of Genoa, Italy
-Telecommunications Group.
-Department of Naval, Electric, Electronic
-nd Telecommunications Engineering.
-Designed Intelligence Group.
-Department of Industrial Design.
-Eindhoven University of Technology.
-Eindhoven, Netherlands."
 1e7ae86a78a9b4860aa720fb0fd0bdc199b092c3,A Brief Review of Facial Emotion Recognition Based on Visual Information,"Article
 A Brief Review of Facial Emotion Recognition Based
 on Visual Information
@@ -11646,29 +9998,8 @@ CLASSIFICATION
 Christer Loob, Pejman Rasti, Iiris Lusi, Julio C. S. Jacques
 Junior, Xavier Baro, Sergio Escalera, Tomasz Sapinski,
 Dorota Kaminska and Gholamreza Anbarjafari"
-1e8eee51fd3bf7a9570d6ee6aa9a09454254689d,Face Search at Scale,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TPAMI.2016.2582166, IEEE
-Transactions on Pattern Analysis and Machine Intelligence
-Face Search at Scale
-Dayong Wang, Member, IEEE, Charles Otto, Student Member, IEEE, Anil K. Jain, Fellow, IEEE"
-1e9ace30e55c57c14f609fa45a459458ed40dd77,DisguiseNet: A Contrastive Approach for Disguised Face Verification in the Wild,"DisguiseNet : A Contrastive Approach for Disguised Face Veriﬁcation in the Wild
-Skand Vishwanath Peri
-Abhinav Dhall
-Learning Affect and Semantic Image AnalysIs (LASII) Group,
-Indian Institute of Technology Ropar, India"
 1e2d9ea6fe9c50a5c26a629b94446250e1be4e7d,The Freiburg Groceries Dataset,"The Freiburg Groceries Dataset
 Philipp Jund, Nichola Abdo, Andreas Eitel, Wolfram Burgard"
-1e0ba1a61ed0c6d4a76697de1e185ed5def60fb4,Learning to Parse Video into Stable Spatiotemporal Volumes,"Learning to Parse Video into Stable Spatiotemporal Volumes1
-Thomas Dean
-Google Inc.
-We are interested in learning how to exploit continuity, motion and context to account for stable, recov-
-erable, spatiotemporal phenomena embedded in video. While most humans can make sense of still images,
-for the most part, we need continuity and motion to make sense of the world around us. Humans are also
-ided by strong priors that allow us to make conﬁdent predictions despite ambiguity, noise and occlusion.
-The idea of combining top-down prior knowledge and bottom-up cues derived from motion and other
-low-level features has been around almost as long as research in computer vision, e.g., [10], and has recently
-seen renewed interest, e.g., [3, 2, 6, 11]. Rather than the traditional tasks of object recognition or image
-ategorization, here we focus on the task of explaining each new frame in a video in terms of a continuously
-evolving representation of spatiotemporal volumes that account for the complete visual ﬁeld. For the purpose"
 1ea2a53a6cb9c08312276a2f0646935d5fab5ed3,Real-time Crowd Tracking using Parameter Optimized Mixture of Motion Models,"Noname manuscript No.
 (will be inserted by the editor)
 Real-time Crowd Tracking using Parameter Optimized
@@ -11697,12 +10028,6 @@ A series of experiments illustrates the good behavior of the algorithm in terms
 performance and robustness with respect to the violation of the postulated low den-
 sity separation assumption. The minimum entropy solution bene(cid:12)ts from unlabeled
 data and is able to challenge mixture models and manifold learning in a number of"
-1e284c51e005099b482eba9590427e29038d75c6,Pose Invariant Recognition using SIFT Based Feature Extraction and MRF,"IJSRD - International Journal for Scientific Research & Development| Vol. 3, Issue 03, 2015 | ISSN (online): 2321-0613
-Pose Invariant Recognition using SIFT Based Feature Extraction and
-Sushama Kumari R B1 D.Gnana Jebadas2
-PG Student (M.E) 2Assistant Professor
-Department of Applied Electronics 2Department of Electronics Communication Engineering
-,2Narayanaguru College of Engineering, Manjalumoodu, K.K (DIST)-Tamilnadu 629151, India"
 1ebcf5dbb37fcd369530b0ee4df5d4a60f756f3e,Unsupervised High-level Feature Learning by Ensemble Projection for Semi-supervised Image Classification and Image Clustering,"High-level Feature Learning by Ensemble Projection for Image
 Classiﬁcation with Limited Annotations $
 Dengxin Dai∗, Luc Van Gool
@@ -11767,14 +10092,6 @@ Tel-Aviv, Israel"
 1e5c6c9fa9ba089931cfb2bc81e4368a4db5dd2d,Multi- View Fusion for Action Recognition in Child-Robot Interaction,"978-1-4799-7061-2/18/$31.00 ©2018 IEEE
 ICIP 2018
 #2Kinect #1Kinect #3Multi-view action recognition systemSenseActDecisionSpeakRec.ActionActFig.1:Multi-viewactionrecognitionsystemforchild-robotinteraction.presentspontaneousbehaviorandaninformalwayofcommunica-tion.Inaddition,thesameactionscanbeperformedinavarietyofwaysandawidespectrum,furthercomplicatingtherecognitionofactions.Althoughhumanactionrecognitionisapopularproblemwithmanyproposedmethods[8–13],therequirementsofmulti-viewac-tionrecognitiondiffersigniﬁcantlyasithastotakeintoaccountbothactionrecognitionthatresultsfromsingleviewsandalsothefusionamongtheresultinginformationfromthedifferentstreams[14,15].Incross-viewactionrecognitionworksitisattemptedtoshareknowledgefortheactionamongthedifferentsetupviews.Forexample,in[16]aspeciﬁcviewistreatedasthetargetdomainandtheotherviewsassourcedomainsinordertoformulateacross-viewlearningframework.Inotherapproaches,theknowledgeofactionsistransferredfromthedifferentviewsinasinglecanoni-calview[17].In[18]itisproposedtolearnview-invariantfeaturesrobusttoviewvariationsusingdeepmodels.Intheﬁeldofmulti-viewactionrecognition,anewglobalrepresentationthatiscalledmulti-viewsupervectorhasalsobeenproposedinordertoenhancerecognitionperformance[19].Finally,anotherinterestingapproachispresentedin[20]whereitisattemptedtotransferthelow-levelfeaturesintoahigh-levelsemanticspaceandamulti-tasklearningapproachforjointactionmodelingisexamined.Inthispaperwedevelopamulti-viewactionrecognitionsystemsuitableforCRI.Themaincontributionsofthispapercanbesum-marizedasfollows:1)Single-viewmethodsareexploredinordertocreaterobustactionrecognitionmodelsforparticularusers,i.e.children,underdifﬁculttaskswithfewtrainingdata.2)Methodsforthefusionofinformationfromdifferentstreamsinamulti-viewsys-temareproposedtoenhanceactionrecognitionduringCRI.3)Themulti-viewactionrecognitionsystemisintegratedinroboticplat-"
-1e8711d2fc4b05eac0699c82f4698154c2b057d3,The unreasonable effectiveness of small neural ensembles in high-dimensional brain,"The unreasonable effectiveness of small neural ensembles
-in high-dimensional brain
-A.N. Gorbana,b,∗, V.A. Makarovb,c, I.Y. Tyukina,b,d
-Instituto de Matem´atica Interdisciplinar, Faculty of Mathematics, Universidad Complutense de Madrid, Avda Complutense s/n, 28040 Madrid,
-Department of Mathematics, University of Leicester, Leicester, LE1 7RH, UK
-Lobachevsky University, Nizhni Novgorod, Russia
-dSaint-Petersburg State Electrotechnical University, Saint-Petersburg, Russia
-Spain"
 1e146982a7b088e7a3790d2683484944c3b9dcf7,Video Person Re-Identification for Wide Area Tracking based on Recurrent Neural Networks,"Video Person Re-Identification for Wide Area Tracking based on
 Recurrent Neural Networks
 McLaughlin, N., Martinez del Rincon, J., & Miller, P. (2017). Video Person Re-Identification for Wide Area
@@ -11860,9 +10177,6 @@ Department of Computer Science
 State University of New York at
 Binghamton
 NY, USA."
-1e21078efc0aa7a3881d0e87cb5dd5918523f525,Network Consistent Data Association,"Network Consistent Data Association
-Anirban Chakraborty, Member, IEEE, Abir Das, Student Member, IEEE,
-nd Amit K. Roy-Chowdhury, Senior Member, IEEE"
 1e1e66783f51a206509b0a427e68b3f6e40a27c8,Semi-supervised estimation of perceived age from face images,"SEMI-SUPERVISED ESTIMATION OF PERCEIVED AGE
 FROM FACE IMAGES
 VALWAY Technology Center, NEC Soft, Ltd., Tokyo, Japan
@@ -11876,10 +10190,6 @@ Cordelia Schmid
 CHESNEAU ET AL.: DETECTING PARTS FOR ACTION LOCALIZATION
 Detecting Parts for Action Localization
 Inria∗"
-1e41a3fdaac9f306c0ef0a978ae050d884d77d2a,Robust Object Recognition with Cortex-Like Mechanisms,"Robust Object Recognition with
-Cortex-Like Mechanisms
-Thomas Serre, Lior Wolf, Stanley Bileschi, Maximilian Riesenhuber, and
-Tomaso Poggio, Member, IEEE"
 1eadafc27372b33a73eca062438a58d4280fd3a1,DeepSkeleton: Learning Multi-Task Scale-Associated Deep Side Outputs for Object Skeleton Extraction in Natural Images,"DeepSkeleton: Learning Multi-task Scale-associated
 Deep Side Outputs for Object Skeleton Extraction
 in Natural Images
@@ -12124,46 +10434,6 @@ Shashanka Ubaru
 Arya Mazumdar
 Yousef Saad
 University of Minnesota-Twin Cities, MN USA"
-0953df0cb7a40a29100eb3089863451ee8e6db47,Chapter 10 PERCEPTUAL INTERFACES,"Chapter 10
-PERCEPTUAL INTERFACES
-Matthew Turk
-nd Mathias K¨olsch
-A keyboard! How quaint.
-— Scotty, in the ﬁlm Star Trek IV: The Voyage Home (1986)
-Introduction
-Computer vision research has traditionally been motivated by a few main
-reas of application. The most prominent of these include biological vision
-modeling, robot navigation and manipulation, surveillance, medical imaging,
-nd various inspection, detection, and recognition tasks. In recent years, a
-new area, often referred to as perceptual interfaces, has emerged to mo-
-tivate an increasingly large amount of research within the machine vision
-ommunity. The general focus of this effort is to integrate multiple per-
-eptual modalities (such as computer vision, speech and sound processing,
-nd haptic I/O) into the user interface. For computer vision technology in
-particular, the primary aim is to use vision as an effective input modality
-in human-computer interaction. Broadly deﬁned, perceptual interfaces are
-highly interactive, multimodal interfaces that enable rich, natural, and ef-
-ﬁcient interaction with computers. More speciﬁcally, perceptual interfaces"
-0967341790643f680f3fc9dc87bfe311723be4e4,A Perception-Driven Transcale Display Scheme for Space Image Sequences,"Hindawi
-Advances in Multimedia
-Volume 2018, Article ID 6045701, 14 pages
-https://doi.org/10.1155/2018/6045701
-Research Article
-A Perception-Driven Transcale Display Scheme for
-Space Image Sequences
-Lingling Zi
-,1 Xin Cong
-,1 Yanfei Peng,1 and Pei Yang2
-School of Electronic and Information Engineering, Liaoning Technical University, Huludao 125105, China
-College of Science, Liaoning Technical University, Fuxin 123000, China
-Correspondence should be addressed to Xin Cong;
-Received 22 May 2018; Accepted 19 September 2018; Published 4 October 2018
-Academic Editor: Deepu Rajan
-Copyright © 2018 Lingling Zi et al. This is an open access article distributed under the Creative Commons Attribution License,
-which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
-With the rapid development of multimedia technology, the way of obtaining high-quality motion reproduction for space targets has
-ttracted much attention in recent years. This paper proposes a Perception-driven Transcale Display Scheme, which significantly
-improves the awareness of multimedia processing. This new scheme contains two important modules, transcale description based"
 09b0040ad09d61f3403c57c437c03271f8614add,HUMAN ACTIVITY RECOGNITION AND GYMNASTICS ANALYSIS THROUGH DEPTH IMAGERY by,"HUMAN ACTIVITY RECOGNITION AND
 GYMNASTICS ANALYSIS THROUGH
 DEPTH IMAGERY
@@ -12175,10 +10445,6 @@ Harris Papadopoulos
 Computer Science and Engineering Department, Frederick University,
 7 Y. Frederickou St., Palouriotisa, Nicosia 1036, Cyprus
 Editor: Alex Gammerman, Vladimir Vovk, Zhiyuan Luo, and Harris Papadopoulos"
-09718bf335b926907ded5cb4c94784fd20e5ccd8,"Recognizing partially occluded, expression variant faces from single training image per person with SOM and soft k-NN ensemble","Recognizing Partially Occluded, Expression Variant
-Faces From Single Training Image per Person
-With SOM and Soft k-NN Ensemble
-Xiaoyang Tan, Songcan Chen, Zhi-Hua Zhou, Member, IEEE, and Fuyan Zhang"
 09d954e980133014cb4dfe3f6b1444edaa099c97,Real-time self-adaptive deep stereo,"Real-time self-adaptive deep stereo
 Alessio Tonioni, Fabio Tosi, Matteo Poggi, Stefano Mattoccia and Luigi Di Stefano
 Department of Computer Science and Engineering (DISI)
@@ -12248,9 +10514,6 @@ for Visual Question Answering
 Jiasen Lu∗, Jianwei Yang∗, Dhruv Batra∗† , Devi Parikh∗†
 Virginia Tech, † Georgia Institute of Technology
 {jiasenlu, jw2yang, dbatra,"
-0969aa7d4557699b7460e4159658828efafed8bd,Con-Text: Text Detection for Fine-Grained Object Classification,"Con-Text: Text Detection for Fine-grained Object
-Classiﬁcation
-Sezer Karaoglu, Ran Tao, Jan C. van Gemert and Theo Gevers, Member, IEEE,"
 09926ed62511c340f4540b5bc53cf2480e8063f8,Tubelet Detector for Spatio-Temporal Action Localization,"Action Tubelet Detector for Spatio-Temporal Action Localization
 Vicky Kalogeiton1,2
 Philippe Weinzaepfel3
@@ -12278,24 +10541,6 @@ Deva Ramanan
 Charless Fowlkes
 Department of Computer Science
 University of California at Irvine"
-09d453d4949b9d2b0dad1d5288e02ca9ec7da450,A Method for Predicting Vehicles Motion Based on Road Scene Reconstruction and Neural Networks in Real Time,"IT in Industry, vol. 6, 2018                                                                                                                        Published online 17-Feb-2018
-A Method for Predicting Vehicles Motion Based on
-Road Scene Reconstruction and Neural Networks in
-Real Time
-Prof. D. Sc. Nina Krapukhina, PhD student Nikolay Kamenov
-The National University of Science and Technology MISIS Moscow, Russia"
-09c4732280c3b2586e390d818ef0056a8de73e2c,A New Method of Histogram Computation for Efficient Implementation of the HOG Algorithm,"Article
-A New Method of Histogram Computation for
-Efﬁcient Implementation of the HOG Algorithm †
-Mariana-Eugenia Ilas 1,* ID and Constantin Ilas 2
-Department of Electronics, Telecommunications and IT, University Politehnica Bucharest,
-Bucharest 060042, Romania
-Department of Automatics and Computer Science, University Politehnica Bucharest,
-Bucharest 060042, Romania;
-* Correspondence: Tel.: +40-21-402-4618
-This paper is an extended version of our paper published in the 9th Computer Science & Electronic
-Engineering Conference (CEEC), Colchester, UK, 27–29 September 2017.
-Received: 5 January 2018; Accepted: 27 February 2018; Published: 1 March 2018"
 09cf3d036f84b6b3ac5244a2ecf8ac74f69de5d3,Integrating Graph Partitioning and Matching for Trajectory Analysis in Video Surveillance,"Integrating Graph Partitioning and Matching for
 Trajectory Analysis in Video Surveillance
 Liang Lin, Yongyi Lu, Yan Pan, Xiaowu Chen"
@@ -12355,13 +10600,6 @@ Haicheng Wang
 035140108
 COMP4801 Final Year Project
 Project Code: 17007"
-1740a0732e8e308f5dd395313313cc3289666f13,Preference-Aware View Recommendation System for Cameras Based on Bag of Aesthetics-Preserving Features,"Transactions on Multimedia
-Page 22 of 32
-Preference-Aware View Recommendation System
-for Cameras Based on Bag of
-Aesthetics-Preserving Features
-Hsiao-Hang Su, Tse-Wei Chen, Member, IEEE, Chieh-Chi Kao, Winston H. Hsu, Member, IEEE,
-nd Shao-Yi Chien*, Member, IEEE"
 177cbeb83c3a0868b9a5c75cd74edf4b972cba80,Exact Primitives for Time Series Data Mining,"UNIVERSITY OF CALIFORNIA
 RIVERSIDE
 Exact Primitives for Time Series Data Mining
@@ -12465,9 +10703,6 @@ Bi Li, Wenxuan Xie, Wenjun Zeng, Fellow, IEEE, and Wenyu Liu, Senior Member, IEE
 for Semantic Segmentation
 Di Lin1, Yuanfeng Ji1, Dani Lischinski2, Daniel Cohen-Or1,3, and Hui Huang1(cid:63)
 Shenzhen University 2The Hebrew University of Jerusalem 3Tel Aviv University"
-175fcfe655b5601b21fdfb3c61bff49c7a8ca297,Semantic Human Matting,"Semantic Human Ma(cid:130)ing
-(cid:139)an Chen1, Tiezheng Ge1, Yanyu Xu1,2, Zhiqiang Zhang1, Xinxin Yang1, Kun Gai1
-Alibaba Group, Beijing, China; 2ShanghaiTech University, Shanghai, China"
 17ff59bb388b155f613f7566ba7cd71ec780cdec,Asymmetric Sparse Kernel Approximations for Large-Scale Visual Search,"Asymmetric sparse kernel approximations
 for large-scale visual search
 Damek Davis
@@ -12479,17 +10714,6 @@ Los Angeles, CA 90095
 Stefano Soatto
 University of California
 Los Angeles, CA 90095"
-17ad76ef00d4cb584389682ca6b138a8bdc9a2da,Continuous Multimodal Emotion Recognition Approach for AVEC 2017,"Continuous Multimodal Emotion Recognition
-Approach for AVEC 2017
-Narotam Singh*, Nittin Singh†, Abhinav Dhall‡
-Department of Computer Science and Engineering, Indian Institute of Technology Ropar
-Email:
-India"
-17257fc03b611315ae49bd53d229188b889002e6,Hard Negative Mining for Metric Learning Based Zero-Shot Classification,"Hard Negative Mining for
-Metric Learning Based Zero-Shot Classiﬁcation
-Maxime Bucher1,2, St´ephane Herbin1, Fr´ed´eric Jurie2
-ONERA - The French Aerospace Lab, Palaiseau, France
-Normandie Univ, UNICAEN, ENSICAEN, CNRS, Caen, France"
 1742e6c347037d5d4ccbdf5c7a27dfbf0afedb91,A Unified Framework for Representation-Based Subspace Clustering of Out-of-Sample and Large-Scale Data,"JOURNAL OF LATEX CLASS FILES, VOL. 13, NO. 9, SEPTEMBER 2014
 A Uniﬁed Framework for Representation-Based
 Subspace Clustering of Out-of-Sample and
@@ -12530,16 +10754,6 @@ Oncel Tuzel
 Yuichi Taguchi
 John R. Hershey
 Mitsubishi Electric Research Labs (MERL), Cambridge, MA, USA"
-17e974f463ae01c518ffb1f77852b59dd8f78b56,Review of Different Face Recognition Techniques,"International Association of Scientific Innovation and Research (IASIR)
-(An Association Unifying the Sciences, Engineering, and Applied Research)
-ISSN (Print): 2279-0063
-ISSN (Online): 2279-0071
-International Journal of Software and Web Sciences (IJSWS)
-www.iasir.net
-Review of Different Face Recognition Techniques
-Ravikant Gupta*, Dilip Dandotiya*, Satyendra Dhakad*, Yogesh Tayal**, Pramod kumar Pandey**
-*M.Tech. Student of Electronics & Instrumentation Department, ITM University, Gwalior, India
-**Faculty of Electronics & Instrumentation Department, ITM University, Gwalior, India"
 17c62bff70eb0919864f111df4930062aded729a,Encoding Spatial Context in Local Image Descriptors,"Universit¨at des Saarlandes
 Max-Planck-Institut f¨ur Informatik
 Encoding Spatial Context in
@@ -12670,12 +10884,6 @@ Xingjian Shi, Dit-Yan Yeung, Senior Member, IEEE"
 11691f1e7c9dbcbd6dfd256ba7ac710581552baa,SoccerNet: A Scalable Dataset for Action Spotting in Soccer Videos,"SoccerNet: A Scalable Dataset for Action Spotting in Soccer Videos
 Silvio Giancola, Mohieddine Amine, Tarek Dghaily, Bernard Ghanem
 King Abdullah University of Science and Technology (KAUST), Saudi Arabia"
-1134a6be0f469ff2c8caab266bbdacf482f32179,FACIAL EXPRESSION IDENTIFICATION USING FOUR-BIT CO-OCCURRENCE MATRIXFEATURES AND K-NN CLASSIFIER,"IJRET: International Journal of Research in Engineering and Technology        eISSN: 2319-1163 | pISSN: 2321-7308
-FACIAL EXPRESSION IDENTIFICATION USING FOUR-BIT CO-
-OCCURRENCE MATRIXFEATURES AND K-NN CLASSIFIER
-Bonagiri  C S K Sunil Kumar1, V Bala Shankar2, Pullela S V V S R Kumar3
-,2,3 Department of Computer Science & Engineering, Aditya College of Engineering, Surampalem, East Godavari
-District, Andhra Pradesh, India"
 1174b869c325222c3446d616975842e8d2989cf2,CosFace: Large Margin Cosine Loss for Deep Face Recognition,"CosFace: Large Margin Cosine Loss for Deep Face Recognition
 Hao Wang, Yitong Wang, Zheng Zhou, Xing Ji, Dihong Gong, Jingchao Zhou,
 Zhifeng Li∗, and Wei Liu∗
@@ -12683,16 +10891,6 @@ Tencent AI Lab"
 1172ce24f6e9242b9c26c84c6aa89a72ed8203d0,Find your own way: Weakly-supervised segmentation of path proposals for urban autonomy,"Find Your Own Way: Weakly-Supervised Segmentation of Path
 Proposals for Urban Autonomy
 Dan Barnes, Will Maddern and Ingmar Posner"
-1117073bba23f66717ca631e7077ad2b42f5c08b,Audio-Visual Speech Enhancement Using Multimodal Deep Convolutional Neural Networks,"Audio-Visual Speech Enhancement Using
-Multimodal Deep Convolutional
-Neural Networks
-Jen-Cheng Hou, Syu-Siang Wang, Ying-Hui Lai, Yu Tsao, Member, IEEE,
-Hsiu-Wen Chang, and Hsin-Min Wang, Senior Member, IEEE"
-11d9bee72759e23f19117fc8cbb60b487e8ac79e,Benchmark Visual Question Answer Models by using Focus Map,"Benchmark Visual Question Answer Models by using Focus Map
-Wenda Qiu
-Yueyang Xianzang
-Zhekai Zhang
-Shanghai Jiaotong University"
 1114c2aba97a5782a48341817811df2438d0fdbf,Robust Visual Tracking using Multi-Frame Multi-Feature Joint Modeling,"Robust Visual Tracking using Multi-Frame
 Multi-Feature Joint Modeling
 Peng Zhang∗, Shujian Yu∗, Student Member, IEEE, Jiamiao Xu, Xinge You†, Senior Member, IEEE,
@@ -12742,9 +10940,6 @@ Lexington High School, KTByte Computer Science Academy"
 Human Actions by Multiple Spatio-Temporal Scales
 Recurrent Neural Networks
 Haanvid Lee, Minju Jung, and Jun Tani"
-1183db5f409e8498d1a0f542703f908275a6dc34,Robust Visual Tracking and Vehicle Classification via Sparse Representation,"Robust Visual Tracking and Vehicle
-Classiﬁcation via Sparse Representation
-Xue Mei and Haibin Ling, Member, IEEE"
 11b00a4be68e9622d7b4698aca84da85aca3e288,Modeling Social Interactions in Real Work Environments,"Modeling Social Interactions in Real Work Environments
 Salvatore Vanini
 SUPSI-DTI
@@ -12771,46 +10966,9 @@ Vipin Vijayan, Kevin W. Bowyer, and Patrick J. Flynn."
 1169f3386a49daccbe199cccb518238a0130a537,"Analyzing Complex Events and Human Actions in ""in-the-wild"" Videos",
 115724ce1ce9422dad095b301c7d096498ad50d3,The E2E Dataset: New Challenges For End-to-End Generation,"Saarbr¨ucken, Germany, 15-17 August 2017. c(cid:13)2017 Association for Computational Linguistics
 Proceedings of the SIGDIAL 2017 Conference, pages 201–206,"
-11606059047b2f3b2293a43af0a5eacd01830be0,Pedestrian detection from traffic scenes based on probabilistic models of the contour fragments,"Pedestrian detection from traffic scenes based on
-probabilistic models of the contour fragments
-Florin Florian, Ion Giosan, Sergiu Nedevschi
-Computer Science Department
-Technical University of Cluj-Napoca, Romania
-Ion.Giosan,"
 1151a81118368e7596843b8db2508e4974fd7435,A Testbed for Cross-Dataset Analysis,"A Testbed for Cross-Dataset Analysis
 Tatiana Tommasi and Tinne Tuytelaars
 ESAT-PSI/VISICS - iMinds, KU Leuven, Belgium"
-11943efec248fcac57ff6913424e230d0a02e977,Auxiliary Tasks in Multi-task Learning,"Auxiliary Tasks in Multi-task Learning
-Lukas Liebel
-Marco Körner
-Computer Vision Research Group, Chair of Remote Sensing Technology
-Technical University of Munich, Germany
-{lukas.liebel,
-Multi-task convolutional neural networks (CNNs) have shown impressive results for certain combinations of tasks, such
-s single-image depth estimation (SIDE) and semantic segmentation. This is achieved by pushing the network towards
-learning a robust representation that generalizes well to different atomic tasks. We extend this concept by adding
-uxiliary tasks, which are of minor relevance for the application, to the set of learned tasks. As a kind of additional
-regularization, they are expected to boost the performance of the ultimately desired main tasks. To study the proposed
-pproach, we picked vision-based road scene understanding (RSU) as an exemplary application. Since multi-task
-learning requires specialized datasets, particularly when using extensive sets of tasks, we provide a multi-modal dataset
-for multi-task RSU, called synMT. More than 2.5 · 105 synthetic images, annotated with 21 different labels, were
-cquired from the video game Grand Theft Auto V (GTA V). Our proposed deep multi-task CNN architecture was
-trained on various combination of tasks using synMT. The experiments conﬁrmed that auxiliary tasks can indeed boost
-network performance, both in terms of ﬁnal results and training time.
-Introduction
-Various applications require solving several atomic tasks from
-the computer vision domain using a single image as input. Such"
-11811c547fe91e63547cc7081a859d13b4752f90,Designing Efficient Multimodal Classification Systems Based on Features and Svm Kernels Selection,"Volume 57, Number 3, 2016                                                   ACTA TECHNICA NAPOCENSIS
-Electronics and Telecommunications
-________________________________________________________________________________
-DESIGNING EFFICIENT MULTIMODAL CLASSIFICATION SYSTEMS
-BASED ON FEATURES AND SVM KERNELS SELECTION
-Anca APATEAN
-Technical University of Cluj-Napoca, Communications Department
-Address, Phone and Fax Numbers, Email"
-1119b4b038fd7d1d337d4aee232dea6c56f20cf1,A Sparse Embedding and Least Variance Encoding Approach to Hashing,"A Sparse Embedding and Least Variance Encoding
-Approach to Hashing
-Xiaofeng Zhu, Lei Zhang, Member, IEEE, Zi Huang"
 1120e88663a38ed05120af378f57ecf557660160,Generic Object Crowd Tracking by Multi-Task Learning,"LUOETAL.:GENERICOBJECTCROWDTRACKINGBYMULTI-TASKLEARNING
 Generic Object Crowd Tracking by
 Multi-Task Learning
@@ -12821,11 +10979,6 @@ http://www.iis.ee.ic.ac.uk/~tkkim
 Department of Electrical and Electronic
 Engineering, Imperial College,
 London, UK"
-11fe6d45aa2b33c2ec10d9786a71c15ec4d3dca8,Tied Factor Analysis for Face Recognition across Large Pose Differences,"JUNE 2008
-Tied Factor Analysis for Face Recognition
-cross Large Pose Differences
-Simon J.D. Prince, Member, IEEE, James H. Elder, Member, IEEE,
-Jonathan Warrell, Member, IEEE, and Fatima M. Felisberti"
 11155ee686bfb675816a2acdf5a8ddf06e67b65f,EmoDetect – Smart Emotion Detection from Facial Expressions,"EmoDetect – Smart Emotion Detection from Facial Expressions
 Rishabh Animesh
 Skand Hurkat
@@ -12841,10 +10994,6 @@ Vishwajeet Singh1, Killamsetti Ravi Kumar2, K Eswaran3
 ALPES, Bolarum, Hyderabad 500010,
 ALPES, Bolarum, Hyderabad 500010,
 SNIST, Ghatkesar, Hyderabad 501301,"
-11d04269aa147450f37215beb3ae44207daf3511,Using Visual Context and Region Semantics for High-Level Concept Detection,"Using Visual Context and Region Semantics for
-High-Level Concept Detection
-Phivos Mylonas, Member, IEEE, Evaggelos Spyrou, Student Member, IEEE, Yannis Avrithis, Member, IEEE, and
-Stefanos Kollias, Member, IEEE"
 111f2f1255fa9e5a82753bf5b3f2f0974e87f86d,Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms,"Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms
 {tag}                                                 {/tag}
 International Journal of Computer Applications
@@ -12978,11 +11127,6 @@ Hang Chu1
 Daiqing Li1 Sanja Fidler1
 University of Toronto 2Vector Institute
 {chuhang1122, daiqing,"
-2cce7a5289c4124d9b23fe67963f3d635b63091c,Towards intent dependent image enhancement - state-of-the-art and recent attempts,"TOWARDS INTENT DEPENDENT IMAGE ENHANCEMENT
-State-of-the-art and Recent Attempts
-Marco Bressan, Gabriela Csurka and Sebastien Favre
-Xerox Research Centre Europe, 6, ch. de Maupertuis, 38240 Meylan, France
-Keywords:"
 2c564f5241b0905baafc3677e7ca15c27fd2c6e7,An Integrated Approach to Contextual Face Detection,"AN INTEGRATED APPROACH TO CONTEXTUAL FACE
 DETECTION.
 Santi Segu´ı1, Michal Drozdzal1,2, Petia Radeva1,2 and Jordi Vitri`a1,2
@@ -13021,26 +11165,6 @@ Department of Electrical and Computer Engineering, Babol Noushirvani University
 Reza Ghaderi
 Department of nuclear Engineering, Shahid Beheshti University of Tehran, Tehran, Iran
 Received: 27/Jul/2016            Revised: 07/Jan/2017            Accepted: 14/Jan/2017"
-2c07d9a383e0bb7e1c8ba07084ba8bcf71af2aad,Robust Ear Recognition via Nonnegative Sparse Representation of Gabor Orientation Information,"Hindawi Publishing Corporation
-e Scientiﬁc World Journal
-Volume 2014, Article ID 131605, 11 pages
-http://dx.doi.org/10.1155/2014/131605
-Research Article
-Robust Ear Recognition via Nonnegative Sparse Representation
-of Gabor Orientation Information
-Baoqing Zhang, Zhichun Mu, Hui Zeng, and Shuang Luo
-School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China
-Correspondence should be addressed to Zhichun Mu; muzc
-Received 21 December 2013; Accepted 18 January 2014; Published 24 February 2014
-Academic Editors: S. Kobashi and A. Materka
-Copyright © 2014 Baoqing Zhang et al. This is an open access article distributed under the Creative Commons Attribution License,
-which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
-Orientation information is critical to the accuracy of ear recognition systems. In this paper, a new feature extraction approach is
-investigated for ear recognition by using orientation information of Gabor wavelets. The proposed Gabor orientation feature can
-not only avoid too much redundancy in conventional Gabor feature but also tend to extract more precise orientation information of
-the ear shape contours. Then, Gabor orientation feature based nonnegative sparse representation classification (Gabor orientation
-+ NSRC) is proposed for ear recognition. Compared with SRC in which the sparse coding coefficients can be negative, the
-nonnegativity of NSRC conforms to the intuitive notion of combining parts to form a whole and therefore is more consistent"
 2c786b32a621a52fc7d00499e4b056f149a4fba7,Face Recognition with Decision Tree-Based Local Binary Patterns,"Face Recognition with Decision Tree-based Local
 Binary Patterns
 Daniel Maturana, Domingo Mery and ´Alvaro Soto
@@ -13108,12 +11232,6 @@ models can be used to select a subject’s best expressions across a range of em
 2c72096bbecd70000f919b1cec3f31a649c94fd5,Neural Network Interpretation via Fine Grained Textual Summarization,"Neural Network Interpretation via Fine-Grained Textual Summarization
 Pei Guo, Connor Anderson, Kolton Pearson, Ryan Farrell
 Brigham Young University"
-2c5d1e0719f3ad7f66e1763685ae536806f0c23b,AENet: Learning Deep Audio Features for Video Analysis,"AENet: Learning Deep Audio Features for Video
-Analysis
-Naoya Takahashi, Member, IEEE, Michael Gygli, Member, IEEE, and Luc Van Gool, Member, IEEE"
-2cdc1b728c90d4da31f924879a39d00008d52daa,A Side of Data with My Robot : Three Datasets for Mobile Manipulation in Human Environments,"A Side of Data with My Robot: Three Datasets for Mobile Manipulation in Human Environments
-Matei Ciocarlie, Member, IEEE, Caroline Pantofaru, Member, IEEE, Kaijen Hsiao, Member, IEEE,
-Gary Bradski, Member, IEEE, Peter Brook, and Ethan Dreyfuss"
 2c2bf22e2f0a1817475aefb37e0c4e0404e8d479,Structured Prediction of 3D Human Pose with Deep Neural Networks,"TEKIN ET AL.: STRUCTURED PREDICTION OF 3D HUMAN POSE
 Structured Prediction of 3D Human Pose
 with Deep Neural Networks
@@ -13140,11 +11258,6 @@ Xucong Zhang, Yusuke Sugano∗, Mario Fritz, Andreas Bulling"
 2c0a71b5e111d2c7d99c3f23989d317a0d845adc,N-best maximal decoders for part models,"N-best maximal decoders for part models
 Dennis Park Deva Ramanan
 UC Irvine"
-2c86443519b46c83073b17c6a98da0fe781a2730,Confidence Propagation through CNNs for Guided Sparse Depth Regression.,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015
-Conﬁdence Propagation through CNNs for
-Guided Sparse Depth Regression
-Abdelrahman Eldesokey, Student Member, IEEE, Michael Felsberg, Senior Member, IEEE,
-nd Fahad Shahbaz Khan, Member, IEEE"
 2c2786ea6386f2d611fc9dbf209362699b104f83,Title of Dissertation Local Feature Representations for Facial Expression Recognition Based on Differences of Gray Color Values of Neighboring Pixels,1)LOCAL FEATURE REPRESENTATIONS FOR FACIAL EXPRESSION RECOGNITION BASED ON DIFFERENCES OF GRAY COLOR VALUES OF NEIGHBORING PIXELS        Mohammad Shahidul Islam          A Dissertation Submitted in Partial  Fulfillment of the Requirement for the Degree of  Doctor of Philosophy (Computer Science and Information Systems) School of Applied Statistics National Institute of Development Administration 2013
 2c93c8da5dfe5c50119949881f90ac5a0a4f39fe,Advanced local motion patterns for macro and micro facial expression recognition,"Advanced local motion patterns for macro and micro facial
 expression recognition
@@ -13190,10 +11303,6 @@ Faculdade de Ciências e Tecnologia
 Universidade Nova de Lisboa
 Departamento de Informática
 Caparica, Portugal"
-2c5b5a5e4b8cd001e535118c2fa90bff95d51648,Combining Facial Dynamics With Appearance for Age Estimation,"Combining Facial Dynamics With Appearance
-for Age Estimation
-Hamdi Dibeklio˘glu, Member, IEEE, Fares Alnajar, Student Member, IEEE,
-Albert Ali Salah, Member, IEEE, and Theo Gevers, Member, IEEE"
 2c1cd58790cf07d5fa7f1f1f096023a993a6ead3,"Improving 3 D perception for Object Detection , Classification and Localization using Fused Multi-modal Sensors","Improving 3D perception for Object Detection,
 Classiﬁcation and Localization using Fused Multi-modal
 Sensors
@@ -13237,16 +11346,6 @@ Department of Electrical Engineering - EESC/USP
 Email:"
 2c7932c2096669113328a75d1ad1d1bfb8f86ad0,Multi30K: Multilingual English-German Image Descriptions,"Proceedings of the 5th Workshop on Vision and Language, pages 70–74,
 Berlin, Germany, August 12 2016. c(cid:13)2016 Association for Computational Linguistics"
-2c34bf897bad780e124d5539099405c28f3279ac,Robust Face Recognition via Block Sparse Bayesian Learning,"Robust Face Recognition via Block Sparse Bayesian Learning
-Taiyong Li1,2, Zhilin Zhang3,4,∗
-School of Financial Information Engineering, Southwestern University of Finance and Economics, Chengdu 610074,
-China
-Institute of Chinese Payment System, Southwestern University of Finance and Economics, Chengdu 610074, China
-Department of Electrical and Computer Engineering, University of California at San Diego, La Jolla, CA 92093-0407,
-Samsung R&D Institute America - Dallas, 1301 East Lookout Drive, Richardson, TX 75082, USA"
-2c8f24f859bbbc4193d4d83645ef467bcf25adc2,Classification in the Presence of Label Noise: A Survey,"Classiﬁcation in the Presence of
-Label Noise: a Survey
-Benoît Frénay and Michel Verleysen, Member, IEEE"
 2c7b72d0b66074bff2f0b3493673a51f6f094d5f,A biometric verification system based on the fusion of palmprint and face features,"A Biometric Verification System Based on the Fusion of Palmprint and Face
 Features
 Slobodan Ribaric, Ivan Fratric and Kristina Kis
@@ -13466,24 +11565,7 @@ Neural Network for Fast Object Detection
 Zhaowei Cai1, Quanfu Fan2, Rogerio S. Feris2, and Nuno Vasconcelos1
 SVCL, UC San Diego
 IBM T. J. Watson Research"
-833a2c168849697aae3589bbeef0cbca22808fe8,"Quantity, Contrast, and Convention in Cross-Situated Language Comprehension","Proceedings of the 19th Conference on Computational Language Learning, pages 226–236,
-Beijing, China, July 30-31, 2015. c(cid:13)2015 Association for Computational Linguistics"
 8399c71abc9a820bacd9c4e21c85c461c0b830b3,"Adaboost with ""Keypoint Presence Features"" for Real-Time Vehicle Visual Detection","Author manuscript, published in ""16th World Congress on Intelligent Transport Systems (ITSwc'2009), Sweden (2009)"""
-83d1617092b34804c3825fdf4292120c382fe043,Appearance-Based Multimodal Human Tracking and Identification for Healthcare in the Digital Home,"Sensors 2014, 14, 14253-14277; doi:10.3390/s140814253
-OPEN ACCESS
-sensors
-ISSN 1424-8220
-www.mdpi.com/journal/sensors
-Article
-Appearance-Based Multimodal Human Tracking and
-Identification for Healthcare in the Digital Home
-Mau-Tsuen Yang * and Shen-Yen Huang
-Department of Computer Science & Information Engineering, National Dong-Hwa University, No. 1,
-Sec. 2, Da-Hsueh Rd., Shoufeng, Hualien 974, Taiwan; E-Mail:
-*  Author to whom correspondence should be addressed; E-Mail:
-Tel.: +886-3-863-4028; Fax: +886-3-863-4010.
-Received: 2 April 2014; in revised form: 3 July 2014 / Accepted: 8 July 2014 /
-Published: 5 August 2014"
 83b20fdd3eafd21a6971dacc73d85c484a093bfc,Interleaved Structured Sparse Convolutional Neural Networks,"Interleaved Structured Sparse Convolutional Neural Networks
 Guotian Xie1,2,∗ Jingdong Wang3† Ting Zhang3
 Jianhuang Lai1,2 Richang Hong4 Guo-Jun Qi5
@@ -13494,12 +11576,6 @@ Automatic Person Identification using Multiple Cues
 Danuwat Swangpol and Thanarat Chalidabhongse
 Faculty of Information Technology, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand
 (Tel: +66-2-737-2551; E-mail: ,"
-83c19722450e8f7dcb89dabb38265f19efafba27,A framework with updateable joint images re-ranking for Person Re-identification.,"A framework with updateable joint images re-ranking for Person
-Re-identification
-Yuan Mingyue1,2  Yin Dong1,2*  Ding Jingwen1,3*  Luo Yuhao1,2  Zhou Zhipeng1,2
-Zhu Chengfeng1,2  Zhang Rui1,2
-School of Information Science Technology, USTC, Hefei, Anhui 230027, China
-Key Laboratory of Electromagnetic Space Information of CAS, Hefei, Anhui 230027, China"
 838420cebfdad4e93221f8fe203c09155983141a,Subspace Alignment Based Domain Adaptation for RCNN Detector,"RAJ, NAMBOODIRI, TUYTELAARS: ADAPTING RCNN DETECTOR
 Subspace Alignment Based Domain
 Adaptation for RCNN Detector
@@ -13515,20 +11591,6 @@ Kanpur, India.
 ESAT, PSI-VISICS
 KU Leuven,
 Heverlee, Belgium"
-8326b11dd0b81dcc169ce21fc12e0c9d632db6bd,Recognition : A Unified Approach on Tracking and Recognition,"ISSN: 2321-8169
-International Journal on Recent and Innovation Trends in Computing and Communication
-Volume: 2 Issue: 11
-3532 – 3539
-_______________________________________________________________________________________________
-Tracking and Recognition: A Unified Approach on Tracking and Recognition
-Ms. Anuja V. Vaidya
-Dr. Mrs. S.B. Patil
-Dept. of Electronics & Communication
-Dept of Electronics & Communication
-Dr. J.J. Magdum College of  Engg. Jaysingpur,
-Dr. J.J. Magdum College of Engg. Jaysingpur,
-Maharashtra, India
-Maharashtra, India"
 83cc0768927dfdac32f2d5753cf70ac23b7cddeb,BLACKFACE SURVEILLANCE CAMERA DATABASE FOR EVALUATING FACE RECOGNITION IN LOW QUALITY SCENARIOS,"ISSN:
 Print    -  2277 - 0593
 Online -  2315 - 7461
@@ -13568,26 +11630,6 @@ Liuyuan Deng, Ming Yang, Hao Li, Tianyi Li, Bing Hu, Chunxiang Wang"
 Lightweight OpenPose
 Daniil Osokin
 Intel"
-83bdd4e4993d5213a3dd1fb3dc69c40eee643a6a,Review : Recent Structure-From-Motion Algorithms 3 D Shape Reconstruction,"IJCSNS International Journal of Computer Science and Network Security, VOL.16 No.4, April 2016
-Review: Recent Structure-From-Motion Algorithms 3D Shape
-Reconstruction
-University College of Engineering Khammam, INDIA
-K. Punnam Chandar
-Dept. of E.C.E
-T. Satya Savithri
-Dept. of E.C.E J.N.T.U Hyderabad, INDIA
-limit
-their  deployment
-is  an  active  area  of
-ameras and the other is reconstructing the 3D face model
-from  2D  images.  The  high  cost  of  the  3D  depth  sensing
-ameras
-in  multimedia  and
-surveillance  applications.  The  alternative  is  to  develop
-lgorithms  to  reconstruct  the  3D  face  model  from  2D
-images  and
-research.  The
-reconstruction accuracy depends on the quality of the 2D"
 833cd4265bd8162d3cfb483ce8f31eaef28e7a2e,TOWARDS EFFECTIVE GANS,"Under review as a conference paper at ICLR 2018
 TOWARDS EFFECTIVE GANS
 FOR DATA DISTRIBUTIONS WITH DIVERSE MODES
@@ -13691,11 +11733,6 @@ A thesis submitted in partial fulﬁllment of the requirements for the de-
 gree of Magister Scientiae in the Department of Computer Science,
 University of the Western Cape.
 May 2006"
-83df0ec6071dfda29da831860fdb2a1f19a6b3bc,3D Face Recognition Using Joint Differential Invariants,"D Face Recognition Using Joint Differential
-Invariants
-Marinella Cadoni1, Manuele Bicego1,2, and Enrico Grosso1
-Computer Vision Laboratory, DEIR, University of Sassari, Italy
-Computer Science Dept., University of Verona, Italy"
 834f5ab0cb374b13a6e19198d550e7a32901a4b2,Face Translation between Images and Videos using Identity-aware CycleGAN,"Face Translation between Images and Videos using Identity-aware CycleGAN
 Zhiwu Huang†, Bernhard Kratzwald†, Danda Pani Paudel†, Jiqing Wu†, Luc Van Gool†‡
 Computer Vision Lab, ETH Zurich, Switzerland
@@ -13720,11 +11757,6 @@ June 9, 2016"
 in cities using deep learning and computer vision
 Mohamed R. Ibrahim1, James Haworth2 and Tao Cheng3
 Department of Civil, Environmental and Geomatic Engineering, University College London (UCL)"
-83968f81f23a34e18e850fe2cf68bab51e22e35c,Attention-driven parts-based object detection,"Attention-Driven Parts-Based Object Detection
-Ilkka Autio & J.T. Lindgren
-Department of Computer Science
-University of Helsinki
-Finland"
 83fd5c23204147844a0528c21e645b757edd7af9,USDOT number localization and recognition from vehicle side-view NIR images,"USDOT Number Localization and Recognition From Vehicle Side-View NIR
 Images
 Orhan Bulan, Safwan Wshah, Ramesh Palghat, Vladimir Kozitsky and Aaron Burry
@@ -13837,26 +11869,6 @@ TTI-Chicago"
 bb288a5c653659411f95ef5db8e1ad652e0a8173,Learning Depth From Single Images With Deep Neural Network Embedding Focal Length,"Learning Depth from Single Images with Deep
 Neural Network Embedding Focal Length
 Lei He, Guanghui Wang (Senior Member, IEEE) and Zhanyi Hu"
-bb451dc2420e1a090c4796c19716f93a9ef867c9,A Review on : Automatic Movie Character Annotation by Robust Face-Name Graph Matching,"International Journal of Computer Applications (0975 – 8887)
-Volume 104 – No.5, October 2014
-A Review on: Automatic Movie Character Annotation
-y Robust Face-Name Graph Matching
-Bhandare P.S.
-Research Scholar
-Sinhgad College of
-Engineering, korti, Pandharpur,
-Solapur University, INDIA
-Gadekar P.R.
-Assistant Professor
-Sinhgad College of
-Engineering, korti, Pandharpur,
-Solapur University, INDIA
-Bandgar Vishal V.
-Assistant Professor
-College of Engineering (Poly),
-Pandharpur, Solapur, INDIA
-Bhise Avdhut S.
-HOD, Department of"
 bba22e04fbe124bf58330e5d911d873a80afa0eb,Probabilistic Global Scale Estimation for MonoSLAM Based on Generic Object Detection,"Probabilistic Global Scale Estimation for MonoSLAM
 Based on Generic Object Detection
 Centro de Investigaci´on en Matem´aticas - Universidad de Guanajuato
@@ -13913,9 +11925,6 @@ Guildford, GU2 7XH, UK
 Email: [ponti, leonardo.sampaio.ribeiro,
 Email: [t.bui,
 tools,"
-bb7c093c41fcec269b6a7a950902cc95429bb289,Robust video object tracking via Bayesian model averaging based feature fusion,"Robust video object tracking via Bayesian model
-veraging based feature fusion
-Yi Dai, Bin Liu, Member, IEEE"
 bb22104d2128e323051fb58a6fe1b3d24a9e9a46,Analyzing Facial Expression by Fusing Manifolds,")=OEC .=?E= -NFHAIIE >O .KIEC
 9A;= +D=C1,2 +DK5C +DA1,3 ;E2EC 0KC1,2,3
 1IJEJKJA B 1BH=JE 5?EA?A 5EE?= 6=EM=
@@ -13938,10 +11947,6 @@ ABBA?JELAAII B KH =CHEJD
 A=EEC DK= AJEI F=OI = EFHJ=J HA E DK= ?KE?=JE 6"
 bb08d1570685a20861e9b8c15c57aae9c01d3eac,Modeling cooperative navigation in dense human crowds,"Modeling Cooperative Navigation in Dense Human Crowds
 Anirudh Vemula1, Katharina Muelling1 and Jean Oh1"
-bbc76f0e50ab96e7318816e24c65fd3459d0497c,Survey of Pedestrian Detection for Advanced Driver Assistance Systems,"JULY 2010
-Survey of Pedestrian Detection for
-Advanced Driver Assistance Systems
-David Gero´ nimo, Antonio M. Lo´ pez, Angel D. Sappa, Member, IEEE, and Thorsten Graf"
 bbd1eb87c0686fddb838421050007e934b2d74ab,Look at Boundary: A Boundary-Aware Face Alignment Algorithm,"(68	points)	COFW	(29	points)	AFLW	(19	points)	Figure1:Theﬁrstcolumnshowsthefaceimagesfromdifferentdatasetswithdifferentnumberoflandmarks.Thesecondcolumnillustratestheuniversallydeﬁnedfacialboundariesestimatedbyourmethods.Withthehelpofboundaryinformation,ourapproachachieveshighaccuracylocalisationresultsacrossmultipledatasetsandannotationprotocols,asshowninthethirdcolumn.Differenttofacedetection[45]andrecognition[75],facealignmentidentiﬁesgeometrystructureofhumanfacewhichcanbeviewedasmodelinghighlystructuredout-put.Eachfaciallandmarkisstronglyassociatedwithawell-deﬁnedfacialboundary,e.g.,eyelidandnosebridge.However,comparedtoboundaries,faciallandmarksarenotsowell-deﬁned.Faciallandmarksotherthancornerscanhardlyremainthesamesemanticallocationswithlargeposevariationandocclusion.Besides,differentannotationschemesofexistingdatasetsleadtoadifferentnumberoflandmarks[28,5,66,30](19/29/68/194points)andanno-tationschemeoffuturefacealignmentdatasetscanhardlybedetermined.Webelievethereasoningofauniquefacial"
 bbc8254b170918d619574496c138dac101dee61f,Context-aware robot navigation using interactively built semantic maps,"Research Article
 Akansel Cosgun* and Henrik I. Christensen
@@ -13966,11 +11971,6 @@ bb6ac4e26499dea5bdedb05b269f40f56247b4c6,An Action Unit based Hierarchical Rando
 bb7f2c5d84797742f1d819ea34d1f4b4f8d7c197,From Images to 3D Shape Attributes.,"TO APPEAR IN TPAMI
 From Images to 3D Shape Attributes
 David F. Fouhey, Abhinav Gupta, Andrew Zisserman"
-bb97664df153ac563e46ec2233346129cafe601b,A study on the use of Boundary Equilibrium GAN for Approximate Frontalization of Unconstrained Faces to aid in Surveillance,"A study on the use of Boundary Equilibrium GAN for Approximate
-Frontalization of Unconstrained Faces to aid in Surveillance
-Wazeer Zulﬁkar, Sebastin Santy, Sahith Dambekodi and Tirtharaj Dash
-BITS Pilani - KK Birla Goa Campus, Goa, India
-{f20150003, f20150357, f20150192,"
 587f81ae87b42c18c565694c694439c65557d6d5,DeepFace : Face Generation using Deep Learning,"DeepFace: Face Generation using Deep Learning
 Hardie Cate
 Fahim Dalvi
@@ -13983,13 +11983,6 @@ University of T¨ubingen, T¨ubingen, Germany
 Leibniz-Institut f¨ur Wissensmedien, T¨ubingen, Germany
 Hector Research Institute of Education Sciences and Psychology, T¨ubingen,
 Germany"
-58542eeef9317ffab9b155579256d11efb4610f2,"Face Recognition Revisited On Pose , Alignment , Color , Illumination And Expression-Pyten","International Journal of Science and Research (IJSR)
-ISSN (Online): 2319-7064
-Index Copernicus Value (2013): 6.14 | Impact Factor (2014): 5.611
-Face Recognition Revisited on Pose, Alignment,
-Color, Illumination and Expression-PyTen
-Mugdha Tripathi
-Computer Science, BIT Noida, India"
 58d16e23e1192be4acaf6a29c1f5995817146554,Bringing back simplicity and lightliness into neural image captioning,"Bringing back simplicity and lightliness into neural image captioning
 Jean-Benoit Delbrouck and St´ephane Dupont
 {jean-benoit.delbrouck,
@@ -14025,15 +12018,6 @@ Dojun Yang
 Joon-Ho Kim
 Samsung Research, Samsung Electronics
 {hyun0772.lee, joody.kim, dojun.yang,"
-58db008b204d0c3c6744f280e8367b4057173259,Facial Expression Recognition,"International  Journal  of Current Engineering  and Technology
-ISSN 2277 - 4106
-© 2012  INPRESSCO.  All  Rights Reserved.
-Available at http://inpressco.com/category/ijcet
-Research Article
-Facial Expression  Recognition
-Riti Kushwahaa and  Neeta Naina*
-Department of Computer  Engineering Malaviya National Institute of Technology, Jaipur, Rajasthan, India
-Accepted 3June  2012,  Available online 8 June 2012"
 58fa85ed57e661df93ca4cdb27d210afe5d2cdcd,Facial expression recognition by re-ranking with global and local generic features,"Cancún Center, Cancún, México, December 4-8, 2016
 978-1-5090-4847-2/16/$31.00 ©2016 IEEE"
 587b607a176588b4646bcdb3d60b6204e98806fe,Extraction in Volumetric Bioimages A Dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Electrical Engineering,"UNIVERSITY OF CALIFORNIA
@@ -14123,27 +12107,6 @@ Hangzhou Normal University
 Frédéric Gosselin
 Université de Montréal
 Caroline Blais"
-58970f1f51432a094faaeb3f4f70aa1778d61a42,Face Alignment Via Component-Based Discriminative Search,"Face Alignment via Component-based Discriminative
-Search
-Lin Liang
-Rong Xiao
-Fang Wen
-Jian Sun
-Microsoft Research Asia
-Beijing, China"
-5872a8ae1879c3f20d94e7cc5a4fcef47b654c7e,Sparse Matching of Salient Facial Curves for Recognizing 3 D Faces,"International Journal of Science and Research (IJSR)
-ISSN (Online): 2319-7064
-Index Copernicus Value (2015): 78.96 | Impact Factor (2015): 6.391
-Sparse Matching of Salient Facial Curves for
-Recognizing 3D Faces
-Madhura Patil1, L. J. Sankpal2
-Pune University, Sinhgad Academy of Engineering, Kondhwa, Pune 411048, India
-Professor, Pune University, Sinhgad Academy of Engineering, Kondhwa, Pune 411048
-cknowledgment
-unique  mark
-cknowledgment.
-increase  acquisition  commotion
-furthermore"
 5860cf0f24f2ec3f8cbc39292976eed52ba2eafd,COMPUTATION EvaBio : A TOOL FOR PERFORMANCE EVALUATION IN BIOMETRICS,"International Journal of Automated Identification Technology, 3(2), July-December 2011, pp. 51-60
 COMPUTATION EvaBio: A TOOL FOR PERFORMANCE
 EVALUATION IN BIOMETRICS
@@ -14236,22 +12199,8 @@ Sinc(i)-FICH-UNL, CONICET, Ciudad Universitaria UNL - Santa Fe (Argentina)
 Laboratorio de Cibern´etica-FI-UNER, C.C. 47 Suc. 3-3100, Entre R´ıos (Argentina)"
 5882e62866fe1fcf7f8458e0bd0bcb39057afce3,Attention to Head Locations for Crowd Counting,"Attention to Head Locations for Crowd Counting
 Youmei Zhang, Chunluan Zhou, Faliang Chang, and Alex C. Kot, Fellow Member, IEEE"
-58a5c2f9f60bdc6ab640767cb21fd6ba04eef5d7,Towards a Unified 3 D Affective Model,"Towards a Unified 3D Affective Model
-Kuderna-Iulian Benţa1, Hannelore-Inge Lisei2, Marcel Cremene1
-Technical University of Cluj-Napoca, 400016 Cluj-Napoca, România,
-“Babeş-Bolyai“ University, 400084 Cluj-Napoca, România,
-{Iulian.Benta, Marcel.Cremene,"
 58a6eb3584b2f5df2f25d39a218904d510cae516,The UAVid Dataset for Video Semantic Segmentation,"The UAVid Dataset for Video Semantic Segmentation
 Ye Lyu1, George Vosselman1, Guisong Xia2, Alper Yilmaz3, Michael Ying Yang1∗"
-58a3d1e4745d047429facc96685d31da86eaccd4,AuxNet: Auxiliary tasks enhanced Semantic Segmentation for Automated Driving,"AuxNet: Auxiliary tasks enhanced
-Semantic Segmentation for Automated Driving
-Sumanth Chennupati1,3, Ganesh Sistu2, Senthil Yogamani2 and Samir Rawashdeh3
-Valeo Troy, United States
-Valeo Vision Systems, Ireland
-{sumanth.chennupati,
-University of Michigan-Dearborn
-Keywords:
-Semantic Segmentation, Multitask Learning, Auxiliary Tasks, Automated Driving."
 0dccc881cb9b474186a01fd60eb3a3e061fa6546,Effective face frontalization in unconstrained images,"Effective Face Frontalization in Unconstrained Images
 Tal Hassner1, Shai Harel1 †, Eran Paz1 † and Roee Enbar2
 The open University of Israel. 2Adience.
@@ -14297,21 +12246,6 @@ Hadidc
 Centre de D(cid:19)eveloppement des Technologies Avanc(cid:19)ees (DZ),
 Ecole Nationale Sup(cid:18)erieure d’Informatique (DZ),
 University of Oulu (FI)"
-0dfb47e206c762d2f4caeb99fd9019ade78c2c98,Custom Pictorial Structures for Re-identification,"CHENG et al.: CUSTOM PICTORIAL STRUCTURES FOR RE-IDENTIFICATION
-Custom Pictorial Structures for
-Re-identiﬁcation
-Dong Seon Cheng1
-Marco Cristani1,2
-Michele Stoppa2
-Loris Bazzani1
-Vittorio Murino1,2
-http://profs.sci.univr.it/~swan
-Dipartimento di Informatica
-University of Verona
-Italy
-Istituto Italiano di Tecnologia
-Via Morego, 30
-6163 Genova, Italy"
 0d96c9d14f079b7b8b6b56b4fa86f611a4ff237f,Semi-supervised low-rank mapping learning for multi-label classification,"Semi-supervised Low-Rank Mapping Learning for Multi-label Classiﬁcation
 Liping Jing1, Liu Yang1, Jian Yu1, Michael K. Ng2
 Beijing Key Lab of Trafﬁc Data Analysis and Mining, Beijing Jiaotong University. 2Department of Mathematics, Hong Kong Baptist University.
@@ -14414,12 +12348,6 @@ Northwestern Polytechincal University, 2Xidian University, 3Carnegie Mellon Univ
 Emilien Dupont
 Suhas Suresha
 Schlumberger Software Technology Innovation Center"
-0d21472dbf20d4c1bd48a15267b4a59eff80e309,Multi-component models for object detection,"Multi-component Models for Object Detection
-Chunhui Gu1, Pablo Arbel´aez2, Yuanqing Lin3, Kai Yu4, and Jitendra Malik2
-Google Inc., Mountain View, CA, USA
-UC Berkeley, Berkeley, CA, USA
-NEC Labs America, Cupertino, CA, USA
-Baidu Inc., Beijing, China"
 0df347f5e3118fac7c351917e3a497899b071d1e,Datasheets for Datasets,"Datasheets for Datasets
 Timnit Gebru 1 Jamie Morgenstern 2 Briana Vecchione 3 Jennifer Wortman Vaughan 1 Hanna Wallach 1
 Hal Daumé III 1 4 Kate Crawford 1 5"
@@ -14525,13 +12453,6 @@ Jing Xiao†
 Tony X. Han∗
 Dept. of ECE, Univ. of Missouri
 Columbia, MO, USA"
-0d33b6c8b4d1a3cb6d669b4b8c11c2a54c203d1a,Detection and Tracking of Faces in Videos: A Review of Related Work,"Detection and Tracking of Faces in Videos: A Review
-© 2016 IJEDR | Volume 4, Issue 2 | ISSN: 2321-9939
-of Related Work
-Seema Saini, 2 Parminder Sandal
-Student, 2Assistant Professor
-, 2Dept. of Electronics & Comm., S S I E T, Punjab, India
-________________________________________________________________________________________________________"
 0db787317ba0d63ec8f9918905e7db181a489026,Automatic Eye Localization in Color Images,"Automatic Eye Localization in Color Images
 José Gilvan Rodrigues Maia1, Fernando de Carvalho Gomes1, Osvaldo de Souza2
 Departamento de Computação – Universidade Federal do Ceará (UFC)
@@ -14595,10 +12516,6 @@ http://pss.sagepub.com
 Lisa Feldman Barrett1,2,3 and Elizabeth A. Kensinger1,3
 Boston College; 2Psychiatric Neuroimaging Program, Massachusetts General Hospital, Harvard Medical School; and 3Athinoula A. Martinos
 Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School"
-0dd74bbda5dd3d9305636d4b6f0dad85d6e19572,Heterogeneous Face Attribute Estimation: A Deep Multi-Task Learning Approach,"Heterogeneous Face Attribute Estimation:
-A Deep Multi-Task Learning Approach
-Hu Han, Member, IEEE, Anil K. Jain, Fellow, IEEE, Fang Wang,
-Shiguang Shan, Senior Member, IEEE and Xilin Chen, Fellow, IEEE"
 0d2a9f3357717e0a44eb82d5eabfc047cc4d46f1,Classifier Ensembles with Trajectory Under-Sampling for Face Re-Identification,"Classiﬁer Ensembles with Trajectory Under-Sampling
 for Face Re-Identiﬁcation
 Roghayeh Soleymani1, Eric Granger1 and Giorgio Fumera2
@@ -14646,11 +12563,6 @@ Ryan Farrell1,2
 Forrest Iandola1
 ICSI / UC Berkeley 2Brigham Young University
 Trevor Darrell1"
-0d6b28691e1aa2a17ffaa98b9b38ac3140fb3306,Review of Perceptual Resemblance of Local Plastic Surgery Facial Images using Near Sets,"Review of Perceptual Resemblance of Local
-Plastic Surgery Facial Images using Near Sets
-Prachi V. Wagde1, Roshni Khedgaonkar2
-,2 Department of Computer Technology,
-YCCE Nagpur, India"
 0da611ca979327840161df87564fd07299c268b5,Bodyprint: Biometric User Identification on Mobile Devices Using the Capacitive Touchscreen to Scan Body Parts,"Bodyprint
 Biometric User Identification on Mobile Devices
 Using the Capacitive Touchscreen to Scan Body Parts
@@ -14723,17 +12635,6 @@ FaceID-BOINC: adapta¸c˜ao de algoritmos de reconhecimento facial (eigenfaces)
 em m´aquinas multicore e GPUs integrado num cliente para plataforma BOINC
 Nuno Miguel Abreu Teixeira - 55397
 Instituto Superior T´ecnico"
-b6aaaf6290ba0ca13be61d122907617f1ea86315,Embedded Face Recognition Using Cascaded Structures PROEFSCHRIFT,"Embedded Face Recognition
-Using Cascaded Structures
-PROEFSCHRIFT
-ter verkrijging van de graad van doctor aan de
-Technische Universiteit Eindhoven, op gezag van de
-Rector Magniﬁcus, prof.dr.ir. C.J. van Duijn, voor een
-ommissie aangewezen door het College voor
-Promoties in het openbaar te verdedigen op
-dinsdag 3 oktober 2006 om 16.00 uur
-Fei Zuo
-geboren te Xi’an, China"
 b6aaef3be3e93a5429511011b3fcf1c768521efc,Car Detection and Tracking from a Vehicle Driving on a Roundabout,"Bachelor thesis
 Czech
 Technical
@@ -14792,10 +12693,6 @@ Christian Banz, Peter Pirsch, and Holger Blume
 Institute of Microelectronic Systems
 Leibniz Universität Hannover, Hannover, Germany
 KEY WORDS: Stereoscopic, Quality, Matching, Vision, Reconstruction, Camera, Disparity Estimation, Semi-Global Matching"
-b613b30a7cbe76700855479a8d25164fa7b6b9f1,Identifying User-Specific Facial Affects from Spontaneous Expressions with Minimal Annotation,"Identifying User-Specific Facial Affects from
-Spontaneous Expressions with Minimal Annotation
-Michael Xuelin Huang, Grace Ngai, Kien A. Hua, Fellow, IEEE, Stephen C.F. Chan, Member, IEEE
-nd Hong Va Leong, Member, IEEE Computer Society"
 b6dc1cd3cabdfea7363d41773a315a0d241dc836,Local Context Priors for Object Proposal Generation,"Local Context Priors for Object Proposal
 Generation
 Marko Ristin1, Juergen Gall2, and Luc Van Gool1,3
@@ -14810,9 +12707,6 @@ the date of receipt and acceptance should be inserted later"
 b68dfa8723be662e6af76bef159ed929bf8a1a2f,Distance weighted discrimination of face images for gender classification,"Distance weighted discrimination of face images for
 gender classiﬁcation
 Mónica Benito1, Eduardo García-Portugués1,4, J. S. Marron2, and Daniel Peña1,3"
-b6d794f73ef7f2a6ffb4738a7dee334f512046bf,Deep Learning Algorithms with Applications to Video Analytics for A Smart City: A Survey,"Deep Learning Algorithms with Applications to
-Video Analytics for A Smart City: A Survey
-Li Wang, Member, IEEE, and Dennis Sng"
 b6fd905efd5da32bd32047896074a821477cb564,An Human Perceptive Model for Person Re-identification,"An Human Perceptive Model for Person Re-identiﬁcation
 Angelo Cardellicchio1, Tiziana D’Orazio1, Tiziano Politi2 and Vito Ren`o1
 National Research Council, Institute of Intelligent Systems for Automation, Bari, Italia
@@ -14876,22 +12770,6 @@ Semantics
 Nipun Bhatia, Rakshit Kumar, Samir Menon
 Department of Computer Science, Stanford University.
 December 14, 2007"
-b69f7660985be23abda72990cb1f367778960275,Object Recognition based on Principal Component Analysis to Image Patches,"International Journal of Scientific & Engineering Research, Volume 4, Issue 6, June-2013                                                                    1096
-ISSN 2229-5518
-Object Recognition based on Principal
-Component Analysis to Image Patches
-R.Ahilapriyadharsini
-Mepco Schlenk Engineering
-College,
-Sivakasi, India
-S.Arivazhagan
-M.Gowthami
-Mepco Schlenk Engineering
-Renganayagi Varatharaj College of
-College,
-Sivakasi, India
-Engineering, Salvarpatti,
-Sivakasi, India."
 b67e0ae9d64ec06b3e1c25c7f7e8b86020612d33,VOCABULARY-INFORMED VISUAL FEATURE AUGMEN-,"Under review as a conference paper at ICLR 2018
 VOCABULARY-INFORMED VISUAL FEATURE AUGMEN-
 TATION FOR ONE-SHOT LEARNING"
@@ -14903,11 +12781,6 @@ Northwestern Polytechnical University 2Johns Hopkins University 3Beihang Univers
 b63041d05b78a66724fbcb2803508999bf885d6b,Deep Sets,"Deep Sets
 Manzil Zaheer 1 2 Satwik Kottur 2 Siamak Ravanbhakhsh 2 Barnabas Poczos 2 Ruslan Ssalakhutdinov 2
 Alexander Smola 1 2"
-b658fefafe36edf7c62fbc9eb728ef971f478e27,Learning a low-rank shared dictionary for object classification,"ACCEPTED TO IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2016
-LEARNING A LOW-RANK SHARED DICTIONARY
-FOR OBJECT CLASSIFICATION
-Tiep H. Vu, Vishal Monga
-Pennsylvania State University, University Park, PA"
 b6f682648418422e992e3ef78a6965773550d36b,"CBMM Memo No . 061 February 8 , 2017 Full interpretation of minimal images","February 8, 2017"
 b62628ac06bbac998a3ab825324a41a11bc3a988,Xm2vtsdb: the Extended M2vts Database,"SecondInternationalConferenceonAudioandVideo-basedBiometricPersonAuthentication(AVBPA'		),WashingtonD.C,
 XMVTSDB:TheExtendedMVTSDatabase
@@ -14958,10 +12831,6 @@ S´ergio Montazzolli Silva[0000−0003−2444−3175] and Cl´audio Rosito
 Jung[0000−0002−4711−5783]
 Institute of Informatics - Federal University of Rio Grande do Sul
 Porto Alegre, Brazil"
-2e1ff08fb5790e3b5ba7864408628467795a9df4,Human Pose Estimation with Fields of Parts,"Human Pose Estimation
-with Fields of Parts
-Martin Kiefel and Peter Vincent Gehler
-Max Planck Institute for Intelligent Systems, T¨ubingen Germany"
 2e56209ed179be641e6df5efd11be8b3d54a62e9,Combining Deep and Handcrafted Image Features for Presentation Attack Detection in Face Recognition Systems Using Visible-Light Camera Sensors,"Article
 Combining Deep and Handcrafted Image Features for
 Presentation Attack Detection in Face Recognition
@@ -15061,26 +12930,6 @@ The  starting  point  of  our  dataset  is  a  real
 surveillance  setup,  composed  by  8  different
 surveillance cameras, monitoring a section of the
 ampus  of  the  University  of  Modena  and  Reggio"
-2eb37a3f362cffdcf5882a94a20a1212dfed25d9,Local Feature Based Face Recognition,"Local Feature Based Face Recognition
-Sanjay A. Pardeshi and Sanjay N. Talbar
-R.I.T., Rajaramnagar and S.G.G.S. COE &T, Nanded
-India
-. Introduction
-A  reliable  automatic  face  recognition  (AFR)  system  is  a  need  of  time  because  in  today's
-networked  world,  maintaining  the  security  of  private  information  or  physical  property  is
-ecoming increasingly important and difficult as well. Most of the time criminals have been
-taking  the  advantage  of  fundamental  flaws  in  the  conventional  access  control  systems  i.e.
-the systems operating on credit card, ATM etc. do not grant access by ""who we are"", but by
-""what  we  have”.  The  biometric  based  access  control systems  have  a  potential  to  overcome
-most  of  the  deficiencies  of  conventional  access  control  systems  and  has  been  gaining  the
-importance  in  recent  years.  These  systems  can  be  designed  with  biometric  traits  such  as
-fingerprint,  face,  iris,  signature,  hand  geometry  etc.  But  comparison  of  different  biometric
-traits shows that face is very attractive biometric because of its non-intrusiveness and social
-cceptability.  It  provides  automated  methods  of  verifying  or  recognizing  the  identity  of  a
-living person based on its facial characteristics.
-In last decade, major advances occurred in face recognition, with many systems capable of
-chieving  recognition  rates  greater  than  90%.  However  real-world  scenarios  remain  a
-hallenge, because face acquisition process can undergo to a wide range of variations. Hence"
 2ed9a69ee6509c0b3fe5a51d1116dccc877653ba,Reconstruction and Analysis of Shapes from 3D Scans,"Reconstruction and Analysis
 of Shapes from 3D Scans"
 2e1add06cc82d139348056fe43282f1ca1832e5b,Local 3 D Shape Analysis for Facial Expression Recognition,"Local 3D Shape Analysis for Facial Expression
@@ -15178,21 +13027,6 @@ Oleksii Kuchaiev, Ganesh Venkatesh, Hao Wu
 NVIDIA
 {pauliusm, alben, dagarcia, bginsburg, mhouston,
 okuchaiev, gavenkatesh,"
-2e956e178fd50ab140f30f9255a83d853c8be210,Robust Facial Expression Recognition via Compressive Sensing,"Sensors 2012, 12, 3747-3761; doi:10.3390/s120303747
-OPEN ACCESS
-sensors
-ISSN 1424-8220
-www.mdpi.com/journal/sensors
-Article
-Robust Facial Expression Recognition via Compressive Sensing
-Shiqing Zhang 1, Xiaoming Zhao 2,* and Bicheng Lei 1
-School of Physics and Electronic Engineering, Taizhou University, Taizhou 318000, China;
-E-Mails: (S.Z.); (B.L.)
-Department of Computer Science, Taizhou University, Taizhou 318000, China
-*  Author to whom correspondence should be addressed; E-Mail:
-Tel./Fax: +86-576-8513-7178.
-Received: 28 December 2011; in revised form: 19 February 2012 / Accepted: 16 March 2012 /
-Published: 21 March 2012"
 2e55fd3f5138e55250aed84a7dc17adfc34970d3,The implications of social neuroscience for social disability.,"J Autism Dev Disord (2012) 42:1256–1262
 DOI 10.1007/s10803-012-1514-z
 O R I G I N A L P A P E R
@@ -15268,10 +13102,6 @@ E‐mail:"
 ENSEMBLE FOR ATTRIBUTE PERSONALIZATION
 Shrenik Lad1, Bernardino Romera Paredes2, Julien Valentin2, Philip Torr2, Devi Parikh1
 . Virginia Tech 2. University of Oxford"
-2e585adbe1f434396ca6a669dd91914d4d4bf42a,Early Prediction for Physical Human Robot Collaboration in the Operating Room,"TO APPEAR IN AUTONOMOUS ROBOTS, SPECIAL ISSUE IN LEARNING FOR HUMAN-ROBOT COLLABORATION
-Early Prediction for Physical Human Robot
-Collaboration in the Operating Room
-Tian Zhou, Student Member, IEEE, and Juan Wachs, Member, IEEE"
 2efc4eee3953f6b52e23989bbcc2598a91e18ba0,External Cameras and a Mobile Robot for Enhanced Multi-person Tracking,"RFAntennas2D SICKLaserFirewire Cameraon PTU        LaptopCamera 1Flea RGB Camera 2Flea RGBHubFirewireFigure1:Perceptualplatform;staticcameras(withroughpositionsandﬁeldsofview)andthemobilerobotRackham.Thispaperisstructuredasfollows:architectureofthecooperativesystemispresentedinsection2.Sec-tion3describesthedifferentdetectionmodalitiesthatdrivethemulti-persontracker(presentedinsection4).Evaluationsandresultsarepresentedinsection5fol-lowedbyconcludingremarksinsection6.2ARCHITECTUREOurcooperativeframeworkismadeupofamobilerobotandtwoﬁxedviewwall-mountedRGBflea2cameras(ﬁgure1).Thecamerashaveamaximumres-olutionof640x480pixelsandareconnectedtoadual-coreIntelCentrinoLaptopviaaﬁre-wirecable.Therobot,calledRackham,isaniRobotB21rmobileplat-form.Ithasvarioussensors,ofwhichitsSICKLaserRangeFinder(LRF)isutilizedinthiswork.Commu-nicationbetweenthemobilerobotandthecomputer"
 2e64682caf77309db573ee439d988233f71e88ad,Establishing Good Benchmarks and Baselines for Face Recognition,"Author manuscript, published in ""Workshop on Faces in 'Real-Life' Images: Detection, Alignment, and Recognition, Marseille : France
 (2008)"""
@@ -15306,18 +13136,6 @@ WP BRP 60/PSY/2016
 This Working Paper is an output of a research project implemented at the National Research
 University Higher School of Economics (HSE). Any opinions or claims contained in this
 Working Paper do not necessarily reflect the views of HSE"
-e2a9b3e9001d57483acbb63dc2cfb91a90d3c12d,"Image worth Evaluation for False Biometric Detection : Submission to Iris , Fingerprint and Face Recognition","Volume 5, Issue 2, February 2015                                  ISSN: 2277 128X
-International Journal of Advanced Research in
-Computer Science and Software Engineering
-Research Paper
-Available online at: www.ijarcsse.com
-Image worth Evaluation for False Biometric Detection: Submission to
-Iris, Fingerprint and Face Recognition
-Boggarapu Srinivasulu, 2 Dr. M. Ekambaram Naidu, 3Dr. E. Sreenivasa Reddy
-Assistant Professor, Dept of CSE, Mother Theresa Institute of Engineering & Technology
-Palamaner, Chittoor Dist, AP, India
-Principal & Professor (CSE), TRR Engineering College, Hyderabad, India
-Dean& Professor (CSE), Acharya Nagarjuna University, Nagarjunanagar, Guntur, India"
 e27301701e4d2d7da4171e6c560c4fb3f974bf2d,Comparative Evaluations of Selected Tracking-by-Detection Approaches,"Comparative Evaluations of Selected
 Tracking-by-Detection Approaches
 Alhayat Ali Mekonnen, Frédéric Lerasle
@@ -15358,16 +13176,6 @@ L’archive ouverte pluridisciplinaire HAL, est
 destinée au dépôt et à la diffusion de documents
 scientifiques de niveau recherche, publiés ou non,
 émanant des établissements d’enseignement et de"
-e267c813d8804019fbd8e018171dd05255b10fee,PERFORMANCE ANALYSIS OF PCA BASED TECHNIQUES FOR FACE AUTHENTICATION,"Canadian Journal of Pure and Applied Sciences
-Vol. 9, No. 1, pp. 3299-3306, February 2015
-Online ISSN: 1920-3853; Print ISSN: 1715-9997
-Available online at www.cjpas.net
-PERFORMANCE ANALYSIS OF PCA BASED TECHNIQUES
-FOR FACE AUTHENTICATION
-*Krishna Dharavath, Fazal Ahmed Talukdar, Rabul Hussain Laskar
-Speech and Image Processing Research Lab.,
-Department of Electronics and Communication Engineering
-National Institute of Technology Silchar, India"
 e27ef52c641c2b5100a1b34fd0b819e84a31b4df,SARC3D: A New 3D Body Model for People Tracking and Re-identification,"SARC3D: a new 3D body model for People
 Tracking and Re-identiﬁcation
 Davide Baltieri, Roberto Vezzani, and Rita Cucchiara
@@ -15556,10 +13364,6 @@ referred  to  as  “mind-reading”  (Siegal  and  Varley  2002;  Stone  et  al
 998).  In  particular,  individuals  with  autism  have  distinct  diffi-"
 e25e07cfd0818a499033caf9d7aa8ef4feec981b,Semantic Segmentation for Real-World Data by Jointly Exploiting Supervised and Transferrable Knowledge,"Pages 84.1-84.12
 DOI: https://dx.doi.org/10.5244/C.30.84"
-e23a75430f777e982b0715b6f8a048d4bbfea438,Maximum Margin Metric Learning over Discriminative Nullspace for Person Re-identification,"Maximum Margin Metric Learning Over Discriminative
-Nullspace for Person Re-identiﬁcation
-T M Feroz Ali1 and Subhasis Chaudhuri1
-Indian Institute of Technology Bombay, Mumbai, India"
 e2b8ba13586bb9a96e4813472d1f763d37ead47d,Media Content Access : Image-Based Filtering,"(IJACSA) International Journal of Advanced Computer Science and Applications,
 Vol. 9, No. 3, 2018
 Media Content Access: Image-Based Filtering
@@ -15670,14 +13474,6 @@ P.G. Student 2Assistant Professor
 ,2DR C V Raman Institute of Science and Technology Kota, bilaspur
 systems,
 surveillance"
-7ed5dca8725d59714d61ef8e1a14cc4b71c56d3f,Face Sketch to Photo Matching Using LFDA and Pre-Processing,"International Journal of Science and Research (IJSR)
-ISSN (Online): 2319-7064
-Impact Factor (2012): 3.358
-Face Sketch to Photo Matching Using LFDA and
-Pre-Processing
-Pushpa Gopal Ambhore1, Lokesh Bijole2
-Research Scholar, 2Assistant professor, Computer Engineering Department,
-Padm. Dr. V. B. Kolte College of Engineering, Malkapur, Maharashtra, India"
 7e7430b5b6ffc470284b8fa94840797610d450ad,Free-space detection using online disparity-supervised color modeling,"Free-space detection using online disparity-supervised
 olor modeling
 Sanberg, W.P.; Dubbelman, G.; de With, P.H.N.
@@ -15718,12 +13514,6 @@ CLASSIFICATION
 Habib Ullah
 Advisor: Nicola Conci, PhD
 February 2015"
-7e2ff809f2f38eaf070fe36ad054e61c31b6b9e8,"Learning Sparse High Dimensional Filters: Image Filtering, Dense CRFs and Bilateral Neural Networks","Learning Sparse High Dimensional Filters:
-Image Filtering, Dense CRFs and Bilateral Neural Networks
-Varun Jampani1, Martin Kiefel1,2 and Peter V. Gehler1,2
-Max Planck Institute for Intelligent Systems, T¨ubingen, 72076, Germany
-Bernstein Center for Computational Neuroscience, T¨ubingen, 72076, Germany
-{varun.jampani, martin.kiefel,"
 7e5414277148c8fdf9903068b001887225b69868,Perceptive Parallel Processes Coordinating Geometry and Texture,"Perceptive Parallel Processes Coordinating Geometry and Texture
 Marco A. Gutierrez1, Rafael E. Banchs2 and Luis F. D'Haro2"
 7e3693fffef8d83ac109309a77f2545d32c10fc3,The effect of Ramadan fasting on spatial attention through emotional stimuli,"Psychology Research and Behavior Management
@@ -15746,14 +13536,6 @@ Department of clinical sciences, Faculty
 of Biosciences and Medical engineering,
 Universiti Teknologi Malaysia (UTM),
 81310 Johor Bahru, Johor, Malaysia"
-7e79c3a92f60c55a6970f89acfa152bcf74823e0,Face Recognition using FSS-DSOP for Small Sample Size Problem with Illumination Variations,"Int. J. Advance. Soft Comput. Appl., Vol. 1, No. 2, November 2009
-ISSN 2074-8523; Copyright © ICSRS Publication, 2009
-www.i-csrs.org
-Face Recognition using FSS-DSOP for Small
-Sample Size Problem with Illumination
-Variations
-Ganesh Bhat, K.K. Achary
-Canara Engineering College,Department of Electronics, India"
 7e53ab07d0ce28484830329036a1fc018b9644dd,Online multiple people tracking-by-detection in crowded scenes,"Journal of Advances in Computer Engineering and Technology, 1(2) 2015
 Online multiple people tracking-by-detection in
 rowded scenes
@@ -15777,26 +13559,6 @@ Institute of Cartography and Geoinformatics,
 Ruprecht-Karls Universit¨at Heidelberg, Germany
 Heidelberg, Germany
 Leibniz Universit¨at Hannover, Germany"
-7ed1b3a0c270c6cac133e91858e3848d843e1ec2,Principal Component Analysis With Complex Kernels,"IEEE TRANSACTIONS ON NEURAL NETWORKS & LEARNING SYSTEMS- SPECIAL ISSUE ON COMPLEX- AND HYPERCOMPLEX-VALUED NEURAL NETWORKS 1
-Principal Component Analysis With Complex Kernels
-Athanasios Papaioannou, Student Member, IEEE, Stefanos Zafeiriou, Member, IEEE,
-Non-linear complex representations, via the use of complex kernels,
-an be applied to model and capture the nonlinearities of complex
-data. Even though, the theoretical tools of Complex Reproducing Kernel
-Hilbert Spaces (CRKHS) have been recently successfully applied to the
-design of digital ﬁlters and regression and classiﬁcation frameworks
-there is limited research on component analysis and dimensionality
-reduction in CRKHS. The aim of this paper is to properly formulate the
-most popular component analysis methodology, i.e. Principal Component
-Analysis (PCA), in CRKHS. In particular, we deﬁne a general Widely
-Linear Kernel Complex PCA (WLCKPCA) framework. Furthermore, we
-show how to efﬁciently perform Widely Linear PCA (WLPCA) in small
-sample sized problems. Finally, we show the usefulness of the proposed
-framework in robust reconstruction using Euler data representation.
-Index Terms—Principal Component Analysis, Complex Kernels, Pat-
-tern Recognition, Machine vision
-I. INTRODUCTION
-P RINCIPAL component analysis (PCA), which appeared ﬁrst"
 7ea07b7b27d59300840df17e5881dbe3a4769872,Detection driven adaptive multi-cue integration for multiple human tracking,"Detection Driven Adaptive Multi-cue Integration for Multiple Human Tracking
 Ming Yang, Fengjun Lv, Wei Xu, Yihong Gong
 NEC Laboratories America, Inc.
@@ -15887,11 +13649,6 @@ Copyright 2007 Eyad Haj Said"
 fdf533eeb1306ba418b09210387833bdf27bb756,Exploiting Unrelated Tasks in Multi-Task Learning,
 fdf31db5aa8cf8a7f9ac84fcc7b0949e8e000a41,MODELING FASHION Anonymous ICME submission,"MODELING FASHION
 Anonymous ICME submission"
-fd8bb112b197e23183feeb6d1f4506d180caa4fc,Fashion Clothes Matching Scheme Learned from Fashionista ’ S Suggestions in Microblog,"FASHION CLOTHES MATCHING SCHEME LEARNED FROM FASHIONISTA’S
-SUGGESTIONS IN MICROBLOG
-Guangyu Gao1, Yihang Zhang1, Songyang Du2
-School of Software, Beijing Institute of Technology. Beijing 100081, China
-Beijing Special Vehicle Research Institute. Beijing 100072, China"
 fd8b1715ad34858bf8650ac549c4249d86edbb7c,A survey of techniques for human segmentation from static images,"International Association of Scientific Innovation and Research (IASIR)
 (An Association Unifying the Sciences, Engineering, and Applied Research)
 ISSN (Print): 2279-0063
@@ -16004,9 +13761,6 @@ Sage Publications, Inc., Association for Psychological Science are collaborating
 digitize, preserve and extend access to Psychological Science in the Public Interest
 This content downloaded from 129.133.179.122 on Tue, 07 Feb 2017 15:41:42 UTC
 All use subject to http://about.jstor.org/terms"
-fd67b9812fa4aef6c5dfb633df4406105cdb4e8f,Zero-Shot Learning with Generative Latent Prototype Model,"Zero-Shot Learning with Generative Latent
-Prototype Model
-Yanan Li, Student Member, IEEE, Donghui Wang, Member, IEEE"
 fdca08416bdadda91ae977db7d503e8610dd744f,The Ksera Project (http://www.ksera under the 7th Framework Programme (fp7) for Research and Technological Development under Grant Human Robot Interaction Ksera Project (http://www.ksera-project.eu) Has Received Funding from the European Commission under the 7th Framework Programme (fp7) for Researc,"ICT-2009.7.1
 KSERA Project
 010-248085
@@ -16024,11 +13778,6 @@ under the 7th Framework Programme (FP7) for Research and Technological Developme
 under the 7th Framework Programme (FP7) for Research and Technological Development under grant
 greement n°2010-248085."
 fd4537b92ab9fa7c653e9e5b9c4f815914a498c0,One-Sided Unsupervised Domain Mapping,
-fd6d2e4f939b8d804a6b5908bded8f1ad2563e38,Stabilizing GAN Training with Multiple Random Projections,"Stabilizing GAN Training with
-Multiple Random Projections
-Behnam Neyshabur Srinadh Bhojanapalli Ayan Chakrabarti
-Toyota Technological Institute at Chicago
-6045 S. Kenwood Ave., Chicago, IL 60637"
 fde3f34a1accadb73269e4beef487611f682b781,"Before A Computer Can Draw, It Must First Learn To See","Before A Computer Can Draw, It Must First Learn To See
 Derrall Heath and Dan Ventura
 Computer Science Department
@@ -16212,14 +13961,6 @@ Research Center and Laboratoire
 d’Informatique de Grenoble (LIG)
 655 avenue de l’Europe
 8 334 Saint Ismier Cedex, France"
-5cbed05521a44b568c77879fb0b84e1fa27d12e0,Gait-Based Recognition of Humans Using Continuous HMMs,"Gait-based Recognition of Humans Using Continuous HMMs(cid:3)
-A. Kale, A.N. Rajagopalan, N. Cuntoor and V. Kr¨uger
- Center for Automation Research
-University of Maryland at College Park
-College Park, MD 20742
- Department of Electrical Engineering
-Indian Institute of Technology Madras
-Chennai-600 036, India"
 5cebc83001ea0737cc46360850fd294327c82013,MEMORY-BASED GAIT RECOGNITION 1 Memory-based Gait Recognition,"DANLIUet al.:MEMORY-BASEDGAITRECOGNITION
 Memory-based Gait Recognition
 Dan Liu
@@ -16255,15 +13996,6 @@ ompensating the egomotion of the camera. To obtain the optical flow, two consecu
 pixels; then each cell is tracked in the current frame to find corresponding cell in the next frame. Using at least three corresponding
 ells, affine transformation is performed according to each corresponding cell in the consecutive images, so that conformed optical
 flows are extracted. The regions of moving object are detected as transformed objects, which are different from the previously"
-5c5e1f367e8768a9fb0f1b2f9dbfa060a22e75c0,Reference Face Graph for Face Recognition,"Reference Face Graph for Face Recognition
-Mehran Kafai, Member, IEEE, Le An, Student Member, IEEE, and Bir Bhanu, Fellow, IEEE"
-5c5304b79ebc2afd28ade6bb88daa80144ae3587,Review of Human-Robot Interactive Modelling and Application for Elders,"COMPUTER MODELLING & NEW TECHNOLOGIES 2014 18(12C) 408-413
-Han Jing, Xie, Lun Xu Shangmou, Wang Zhiliang
-Review of Human-Robot Interactive Modelling and
-Application for Elders
-Jing Han, Lun Xie*, Shangmou Xu, Zhiliang Wang
-School of Computer and Communication Engineering, University of Science and Technology Beijing, No.30 Xueyuan  road, Beijing, China
-Received 23 November 2014, www.cmnt.lv"
 5c1e0e94d6cb74448c7b3c1e0db42121be4e9bd6,Saliency Detection using regression trees on hierarchical image segments,"SALIENCY DETECTION USING REGRESSION TREES ON
 HIERARCHICAL IMAGE SEGMENTS
 G¨okhan Yildirim, Appu Shaji, Sabine S¨usstrunk
@@ -16371,30 +14103,6 @@ Rahul Tewari
 Paulo R. S. Mendonc¸a
 Amazon Web Services"
 5c3fd194ba96c5eea41c0772ad0b2292dedcd197,Understanding the Energy Saving Potential of Smart Scale Selection in the Viola and Jones Facial Detection Algorithm,
-5cb1277bc7257e7b4cfc1699199c6d8e13ff0b1a,Refining Synthetic Images with Semantic Layouts by Adversarial Training,"Proceedings of Machine Learning Research 95:863-878, 2018
-ACML 2018
-Reﬁning Synthetic Images with Semantic Layouts by
-Adversarial Training
-Tongtong Zhao
-Dalian Maritime University
-Dalian 116026, China
-Yuxiao Yan
-Dalian Maritime University
-Dalian 116026, China
-JinJia Peng
-Dalian Maritime University
-Dalian 116026, China
-HaoHui Wei
-Dalian Maritime University
-Dalian 116026, China
-Xianping Fu
-Dalian Maritime University
-Dalian 116026, China
-Editors: Jun Zhu and Ichiro Takeuchi"
-5cfa8d0384bcdf5dfd7501561c748e69f3a2a747,Lip AUs Detection by Boost-SVM and Gabor,"Lip AUs Detection by Boost-SVM and Gabor
-Xianmei Wang, Yuyu Liang, Xiujie Zhao and Zhiliang Wang
-School of Computer and Communication Engineering, University of Science and Technology, Beijing, China
-Email:"
 5cdc02ed9f456219369fe3115321564c9955b9ae,Real-time Analysis and Visualization of the YFCC 100 m Dataset,"Real-time Analysis and Visualization
 of the YFCC100m Dataset
 Firstname Lastname
@@ -16405,8 +14113,6 @@ Chengchao Qu1,2 Christian Herrmann1,2 Eduardo Monari2 Tobias Schuchert2
 J¨urgen Beyerer2,1
 Vision and Fusion Laboratory (IES), Karlsruhe Institute of Technology (KIT)
 Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (Fraunhofer IOSB)"
-5c77901df1e0f52a9774b39e730c31afbc1214a7,Learning Social Tag Relevance by Neighbor Voting,"Learning Social Tag Relevance by Neighbor Voting
-Xirong Li, Cees G. M. Snoek, Member, IEEE, Marcel Worring, Member, IEEE"
 5cff58d081a4732b11e6da498196ed6fbb54d15b,Adversarial Examples for Semantic Segmentation and Object Detection,"Adversarial Examples for Semantic Segmentation and Object Detection
 Cihang Xie1*, Jianyu Wang2*, Zhishuai Zhang1∗, Yuyin Zhou1, Lingxi Xie1, Alan Yuille1
 Department of Computer Science, The Johns Hopkins University, Baltimore, MD 21218 USA
@@ -16519,46 +14225,12 @@ Yecheng Lyu and Xinming Huang
 Department of Electrical and Computer Engineering
 Worcester Polytechnic Institute
 Worcester, MA 01609, USA"
-7ff1c4e0ad0dae92d4f25b93783fadde8f07276d,An efficient example-based approach for image super-resolution,"IEEE Int. Conference Neural Networks & Signal Processing
-Zhenjiang, China, June 8~10, 2008
-AN EFFICIENT EXAMPLE-BASED APPROACH FOR IMAGE
-SUPER-RESOLUTION
-Xiaoguang Li1,2, Kin Man Lam2, Guoping Qiu3, Lansun Shen1 and Suyu Wang1
-. Signal & Information Processing Lab. Beijing University of Technology, Beijing, China, 100124
-. Centre for Signal Processing, Department of Electronic and Information Engineering, The Hong Kong
-Polytechnic University, Hong Kong
-. Department of Computer Science, Nottingham University, UK"
-7ffa7a36e5414a0f2b16b1d8f93442ab15e2235d,"The CMU Pose, Illumination, and Expression Database","IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 25, NO. 12, DECEMBER 2003
-REFERENCES
-[1] M. Carcassoni and E.R. Hancock, “Spectral Correspondence for Point
-Pattern Matching,” Pattern Recognition, vol. 36, no. 1, pp. 193-204, 2003.
-[2] H. Chui and A. Rangarajan, “Non-Rigid Point Matching Using Mixture
-Models,” Proc. Workshop Math. Methods in Biomedical Image Analysis, pp. 190-
-97, 2000.
-F.R.K. Chung, Spectral Graph Theory, CBMS series, AMS ed. vol. 92, 1997.
-T.F. Cootes, C.J. Taylor, D.H. Cooper, and J. Graham, “Active Shape
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-[5] A.D.J. Cross and E.R. Hancock, “Graph Matching with Dual Step Em
-Algorithm,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20,
-pp. 1236-1253, 1998.
-S. Gold and A. Rangarajan, “A Graduated Assignment Algorithm for
-Graph Matching,” IEEE Trans. Pattern Analysis and Machine Intelligence,
-vol. 18, no. 4, pp. 377-388, Apr. 1996.
-P.J. Green, “Bayesian Reconstruction from Emission Tomography Data
-Using a Modified Em Algorithm,” IEEE Trans. Medical Imaging, vol. 9,
-pp. 84-93, 1990."
 7f44f8a5fd48b2d70cc2f344b4d1e7095f4f1fe5,Sparse Output Coding for Scalable Visual Recognition,"Int J Comput Vis (2016) 119:60–75
 DOI 10.1007/s11263-015-0839-4
 Sparse Output Coding for Scalable Visual Recognition
 Bin Zhao1 · Eric P. Xing1
 Received: 15 May 2013 / Accepted: 16 June 2015 / Published online: 26 June 2015
 © Springer Science+Business Media New York 2015"
-7f511a6a2b38a26f077a5aec4baf5dffc981d881,Low-Latency Human Action Recognition with Weighted Multi-Region Convolutional Neural Network,"LOW-LATENCY HUMAN ACTION RECOGNITION WITH WEIGHTED MULTI-REGION
-CONVOLUTIONAL NEURAL NETWORK
-Yunfeng Wang(cid:63), Wengang Zhou(cid:63), Qilin Zhang†, Xiaotian Zhu(cid:63), Houqiang Li(cid:63)
-(cid:63)University of Science and Technology of China, Hefei, Anhui, China
-HERE Technologies, Chicago, Illinois, USA"
 7ff83f10e49e81ce6f66270e8f3f42dd2c6eb3ed,PIRM Challenge on Perceptual Image Enhancement on Smartphones: Report,"PIRM Challenge on Perceptual Image Enhancement
 on Smartphones: Report
 Andrey Ignatov, Radu Timofte, Thang Van Vu, Tung Minh Luu, Trung X Pham, Cao Van Nguyen,
@@ -16579,19 +14251,11 @@ Paul Natsev
 Balakrishnan Varadarajan
 Sudheendra Vijayanarasimhan
 Google Research"
-7ff0ad5c34f02b9c394ed0d8a3db9c270dc70e44,Learning a temporally invariant representation for visual tracking,"LEARNING A TEMPORALLY INVARIANT REPRESENTATION FOR VISUAL TRACKING
-Chao Ma(cid:63)†, Xiaokang Yang(cid:63), Chongyang Zhang(cid:63), and Ming-Hsuan Yang†
-(cid:63)Shanghai Jiao Tong University, China
-University of California at Merced, USA"
 7fdcb6638a9e01986cd8fb4133b4448700087faf,Expression-Invariant Multispectral Face Recognition : You Can Smile Now !,"Expression-Invariant Multispectral Face Recognition:
 You Can Smile Now!
 Ioannis A. Kakadiarisa, George Passalisa, George Todericia, Yunliang Lua,
 Nikos Karampatziakisa, Najam Murtuzaa, Theoharis Theoharisa
 Computational Biomedicine Lab, Dept. of Computer Science, Univ. of Houston, TX, USA"
-7f65bbc93cf414d4889773b697b1833e85f0a15f,Neural Perspective to Jigsaw Puzzle Solving,"Neural Perspective to Jigsaw Puzzle Solving
-Viveka Kulharia⇤, Arnab Ghosh⇤, Nikhil Patil?, Piyush Rai
-Department of Computer Science, IIT Kanpur
-Kanpur, India"
 7fa41631cdef8f7fba7e1289dd4c5f3723b172ab,A robust and isotropic curved surface representation for 3D faces description,"A robust and isotropic curved surface representation for 3D faces
 description
 Majdi Jribi and Faouzi Ghorbel"
@@ -16601,16 +14265,6 @@ www.iosrjournals.org
 Improved Face Recognition Rate Using HOG Features and SVM
 Classifier
 Harihara Santosh Dadi, Gopala Krishna Mohan Pillutla"
-7fa4e972da46735971aad52413d17c4014c49e6e,How to Train Triplet Networks with 100K Identities?,"How to Train Triplet Networks with 100K Identities?
-Chong Wang
-Orion Star
-Beijing, China
-Xue Zhang
-Orion Star
-Beijing, China
-Xipeng Lan
-Orion Star
-Beijing, China"
 7f3da52c13c70fd5b93c2ccebdd4a4527fa597fa,Deep Multi-task Learning to Recognise Subtle Facial Expressions of Mental States,"Deep Multi-Task Learning to Recognise Subtle Facial Expressions of
 Mental States
 Hu, G., Liu, L., Yuan, Y., Yu, Z., Hua, Y., Zhang, Z., ... Yang, Y. (2018). Deep Multi-Task Learning to Recognise
@@ -16737,30 +14391,6 @@ Karen L. Schmidt, Zara Ambadar, Jeffrey F. Cohn, and L. Ian Reed"
 7fc70f6dbbbc9221552c8547cd10ffc13d11b276,Respectful cameras: detecting visual markers in real-time to address privacy concerns,"Respectful Cameras: Detecting Visual Markers in
 Real-Time to Address Privacy Concerns
 Jeremy Schiff, Marci Meingast, Deirdre K. Mulligan, Shankar Sastry, Ken Goldberg"
-7f0fadae16cc74b6176ba940aa2f8b5a0a67e09e,An Expert Local Mesh Correlation Histograms for Biomedical Image Indexing and Retrieval,"CHAPTER 1
-An Expert Local Mesh Correlation Histograms for
-Biomedical Image Indexing and Retrieval
-Santosh Kumar Vipparthi, Subrahmanyam Murala, S.K. Nagar and Anil
-Balaji Gonde
-Santosh Kumar Vipparthi
-Department of Computer Science and Engineering
-Malaviya National Institute of Technology
-Jaipur, India
-e-mail:
-Subrahmanyam Murala
-Department of Electrical Engineering
-Indian Institute of Technology Ropar
-India
-e-mail:
-S.K. Nagar
-Department of Electrical Engineering
-Indian Institute of Technology Banaras Hindu University
-India
-e-mail:"
-7f268f29d2c8f58cea4946536f5e2325777fa8fa,Facial Emotion Recognition in Curvelet Domain,"Facial Emotion Recognition in Curvelet Domain
-Gyanendra K Verma and Bhupesh Kumar Singh
-Indian Institute of Informaiton Technology, Allahabad, India
-Allahabad, India - 211012"
 3347d3e9f8a2da66e1c00f6a1e56bb37d27145ae,devant le jury composé de:,"Spécialité: Informatique et Télécommunications    Ecole doctorale: Informatique, Télécommunications et Electronique de Paris  Présentée par   Raluca-Diana ŞAMBRA-PETRE  Pour obtenir le grade de DOCTEUR DE TELECOM SUDPARIS    MODELISATION ET INFERENCE 2D/3D DE CONNAISSANCES POUR L'ACCES INTELLIGENT AUX CONTENUS VISUELS ENRICHIS     Soutenue le 18 Juin 2013 à Paris                              devant le jury composé de :   Président de jury: Madame le Maître de Conférences, HDR Catherine ACHARD Rapporteur:  Monsieur le Professeur Marc ANTONINI Rapporteur:  Monsieur le Professeur Constantin VERTAN Examinateur:  Monsieur le Professeur Miroslaw BOBER  Examinateur:  Monsieur le Docteur Olivier MARTINOT Directeur de thèse:  Monsieur le Professeur Titus ZAHARIA    Thèse n°: 2013TELE0012      THESE DE DOCTORAT CONJOINT TELECOM SUDPARIS et L'UNIVERSITE PIERRE ET MARIE CURIE"
 33919313bb3cf09b00f9fa2253b30af33a52bc51,Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs,"Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs
 Anton Osokin∗,1 Jean-Baptiste Alayrac∗,1
@@ -16834,13 +14464,6 @@ vertising or promotional purposes or for creating new collec-
 tive works for resale or redistribution to servers or lists, or to
 reuse any copyrighted component of this work in other works
 must be obtained from the IEEE."
-3316521a5527c7700af8ae6aef32a79a8b83672c,People-tracking-by-detection and people-detection-by-tracking,"People-Tracking-by-Detection and People-Detection-by-Tracking
-Mykhaylo Andriluka
-Stefan Roth
-Bernt Schiele
-Computer Science Department
-TU Darmstadt, Germany
-{andriluka, sroth,"
 33ef644ef5085237b4f529251d6c895d32d6052f,TasselNet: counting maize tassels in the wild via local counts regression network,"Lu et al.
 RESEARCH ARTICLES
 TasselNet: Counting maize tassels in the wild via
@@ -16883,12 +14506,6 @@ Cross Modal Matching
 Alexis Mignon and Fr´ed´eric Jurie
 GREYC, CNRS UMR 6072, Universit´e de Caen Basse-Normandie, France
 first name.last"
-333e7ad7f915d8ee3bb43a93ea167d6026aa3c22,3D Assisted Face Recognition: Dealing With Expression Variations,"This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication.
-The final version of record is available at http://dx.doi.org/10.1109/TIFS.2014.2309851
-DRAFT
-D Assisted Face Recognition: Dealing With
-Expression Variations
-Nesli Erdogmus, Member, IEEE, Jean-Luc Dugelay, Fellow Member, IEEE"
 33ea400ca2105b9a3cd0e3c7c147e06c2d3c6d79,Vision based Decision-Support and Safety Systems for Robotic Surgery,"Vision based Decision-Support and Safety Systems for
 Robotic Surgery
 Suren Kumar
@@ -16904,12 +14521,6 @@ Pankaj Singhal
 Director of Robotic Surgery
 Jason J. Corso
 Assistant Professor"
-33e4844a95bc2df4619e6d43bd009b24a20fb79a,Automatic Face Detection Using Color Based Segmentation and Computing Eigen face,"International Journal of Enhanced Research in Science Technology & Engineering, ISSN: 2319-7463
-Vol. 2 Issue 10, October-2013, pp: (97-105), Available online at: www.erpublications.com
-Automatic Face Detection Using Color Based
-Segmentation and Computing Eigen face
-Surya Prakash Ahirwar1, Dr. Shailja Shukla2
-Department of Electrical Engineering, Jabalpur Engineering College, India"
 33c485b59249af2d763d6951cd11e4080f3bbb3d,Fusing 2D Uncertainty and 3D Cues for Monocular Body Pose Estimation,"Fusing 2D Uncertainty and 3D Cues for Monocular Body Pose Estimation
 Bugra Tekin
 Pablo M´arquez-Neila
@@ -16919,21 +14530,12 @@ EPFL, Switzerland"
 336fe31c25c9128f43f2dfe454041e7c608557d1,H-CNN: Spatial Hashing Based CNN for 3D Shape Analysis.,"H-CNN: Spatial Hashing Based CNN for 3D
 Shape Analysis
 Tianjia Shao, Yin Yang, Yanlin Weng, Qiming Hou, Kun Zhou"
-3326838b53788bdb79d3b37b3ddad6a619ce53b1,Recent Advances in the Automatic Recognition of Audio-Visual Speech,"Article appears in: Proceedings of the IEEE, vol. 91, no. 9, September 2003
-Recent Advances in the Automatic Recognition of
-Audio-Visual Speech
-Gerasimos Potamianos, Member, IEEE, Chalapathy Neti, Member, IEEE, Guillaume Gravier,
-Ashutosh Garg, Student Member, IEEE, and Andrew W. Senior, Senior Member, IEEE
-(Invited Paper)"
 3333b35ddb698be76dd27bffad131c1daa694bf2,Comparing Robustness of Two-Dimensional PCA and Eigenfaces for Face Recognition,"Comparing Robustness of Two-Dimensional
 PCA and Eigenfaces for Face Recognition
 Muriel Visani, Christophe Garcia, and Christophe Laurent
 France Telecom R&D - DIH/HDM
 , rue du Clos Courtel
 5512 Cesson-S´evign´e Cedex - France"
-3352426a67eabe3516812cb66a77aeb8b4df4d1b,Joint Multi-view Face Alignment in the Wild,"JOURNAL OF LATEX CLASS FILES, VOL. 4, NO. 5, APRIL 2015
-Joint Multi-view Face Alignment in the Wild
-Jiankang Deng, Student Member, IEEE, George Trigeorgis, Yuxiang Zhou, and Stefanos Zafeiriou, Member, IEEE"
 33695e0779e67c7722449e9a3e2e55fde64cfd99,Riemannian coding and dictionary learning: Kernels to the rescue,"Riemannian Coding and Dictionary Learning: Kernels to the Rescue
 Mehrtash Harandi, Mathieu Salzmann
 Australian National University & NICTA
@@ -16971,13 +14573,6 @@ Laurence Conty
 nd High-Level Vision using Diverse Datasets and Limited Memory
 Iasonas Kokkinos
 CentraleSup´elec - INRIA"
-33a4744818b2847d7d3650bd547932cdcddc2f04,Sparse Polynomial Mapping for Manifold Learning,"International Journal of Signal Processing, Image Processing and Pattern Recognition
-Vol. 7, No. 6 (2014), pp. 335-344
-http://dx.doi.org/10.14257/ijsip.2014.7.6.29
-Sparse Polynomial Mapping for Manifold Learning
-Ying Xia*, Qiang Lu and Hae-Young Bae
-Research Center of Spatial Information System, Chongqing University of Posts and
-Telecommunications, Chongqing 400065, China"
 330a34b8dfb3f6adaf6401c3ececf9f4127505a0,Feature selection for pose invariant lip biometrics,"INTERSPEECH 2010
 Feature Selection for Pose Invariant Lip Biometrics
 Adrian Pass, Jianguo Zhang, Darryl Stewart
@@ -16988,13 +14583,6 @@ Belfast BT7 1NN, UK
 330dda431e0343a96f9d630a0b4ee526bd93ad11,Domain Adaptation for Visual Applications: A Comprehensive Survey,"Domain Adaptation for Visual Applications: A Comprehensive
 Survey
 Gabriela Csurka"
-334166a942acb15ccc4517cefde751a381512605,Facial Expression Analysis using Deep Learning,"International Research Journal of Engineering and Technology (IRJET)       e-ISSN: 2395-0056
-Volume: 04 Issue: 10 | Oct -2017                     www.irjet.net                                                                 p-ISSN: 2395-0072
-Facial Expression Analysis using Deep Learning
-Hemanth Singh1, Raman Patel2
-,2 M.Tech Student, SSG Engineering College, Odisha, India
----------------------------------------------------------------------***---------------------------------------------------------------------
-examination structures need to analyse the facial exercises"
 3369692338841f14ce032fc5d0b5b4fe7cc79f1a,Visualising mental representations : A primer on noise-based reverse correlation in social psychology,"European Review of Social Psychology
 ISSN: 1046-3283 (Print) 1479-277X (Online) Journal homepage: http://www.tandfonline.com/loi/pers20
 Visualising mental representations: A primer
@@ -17020,13 +14608,6 @@ Illumination for Human Computer Interaction Aplications
 S L Happy, Anirban Dasgupta, Anjith George, and Aurobinda Routray
 Department of Electrical Engineering
 Indian Institute of Technology Kharagpur"
-33a1a049d15e22befc7ddefdd3ae719ced8394bf,An Efficient Approach to Facial Feature Detection for Expression Recognition,"FULL PAPER
-International Journal of Recent Trends in Engineering, Vol 2, No. 1, November 2009
-An Efficient Approach to Facial Feature Detection
-for Expression Recognition
-S.P. Khandait1, P.D. Khandait2 and Dr.R.C.Thool2
-Deptt. of Info.Tech., K.D.K.C.E., Nagpur, India
-2Deptt.of Electronics Engg., K.D.K.C.E., Nagpur, India, 2Deptt. of Info.Tech., SGGSIET, Nanded"
 33e7bc26047de3c1b607f04a644c2c03920201fd,Learning to Navigate Autonomously in Outdoor Environments : MAVNet,"Learning to Navigate Autonomously in Outdoor Environments :
 MAVNet
 Saumya Kumaar2, Arpit Sangotra3, Sudakshin Kumar3, Mayank Gupta3, Navaneethkrishnan B2 and S N Omkar1"
@@ -17048,12 +14629,6 @@ The Faces of Engagement: Automatic
 Recognition of Student Engagement from Facial
 Expressions
 Jacob Whitehill, Zewelanji Serpell, Yi-Ching Lin, Aysha Foster, and Javier R. Movellan"
-333aa36e80f1a7fa29cf069d81d4d2e12679bc67,Suggesting Sounds for Images from Video Collections,"Suggesting Sounds for Images
-from Video Collections
-Matthias Sol`er1, Jean-Charles Bazin2, Oliver Wang2, Andreas Krause1 and
-Alexander Sorkine-Hornung2
-Computer Science Department, ETH Z¨urich, Switzerland
-Disney Research, Switzerland"
 33691b7e8c980ea2dea5b5d3d7bee661e9623715,Probabilistic Semi-Dense Mapping from Highly Accurate Feature-Based Monocular SLAM,"Probabilistic Semi-Dense Mapping from Highly
 Accurate Feature-Based Monocular SLAM
 Ra´ul Mur-Artal and Juan D. Tard´os
@@ -17100,13 +14675,6 @@ Berlin 2007"
 33a9076d5d48208960feebff9d5efdaa2203f872,Face De-Identification,"Face De-identiﬁcation
 Ralph Gross, Latanya Sweeney, Jeffrey Cohn, Fernando de la Torre
 nd Simon Baker"
-336b2ae3e4db996538f930b754f7d233af56a628,Learning local descriptors by optimizing the keypoint-correspondence criterion,"Learning Local Descriptors by Optimizing the
-Keypoint-Correspondence Criterion: Applications to
-Face Matching, Learning from Unlabeled Videos
-nd 3D-Shape Retrieval
-Nenad Markuˇs†, Igor S. Pandˇzi´c†, and J¨orgen Ahlberg‡
-University of Zagreb, Faculty of Electrical Engineering and Computing, Unska 3, 10000 Zagreb, Croatia
-Computer Vision Laboratory, Dept. of Electrical Engineering, Link¨oping University, SE-581 83 Link¨oping, Sweden"
 33ae696546eed070717192d393f75a1583cd8e2c,Subspace selection to suppress confounding source domain information in AAM transfer learning,
 8d9067da4ba5c57643ee7a84cd5c5d5674384937,Sorting out Lipschitz function approximation,"SORTING OUT LIPSCHITZ FUNCTION APPROXIMATION
 Cem Anil ∗
@@ -17131,24 +14699,12 @@ Austin, TX 78701"
 8d384e8c45a429f5c5f6628e8ba0d73c60a51a89,Temporal Dynamic Graph LSTM for Action-Driven Video Object Detection,"Temporal Dynamic Graph LSTM for Action-driven Video Object Detection
 Yuan Yuan1 Xiaodan Liang2 Xiaolong Wang2 Dit-Yan Yeung1 Abhinav Gupta2
 The Hong Kong University of Science and Technology 2 Carneige Mellon University"
-8def62fd86b5ea0a41fd9f892bd95b01bf072e88,A hybrid approach to content based image retrieval using visual features and textual queries,"Proceedings of the 2013 International Conference on Information, Operations Management and Statistics (ICIOMS2013),
-Kuala Lumpur, Malaysia, September 1-3, 2013
-A Hybrid Approach to Content-based Image Retrieval
-Smarajit Bosea, Amita Pala*, Jhimli Mallickb , Sunil Kumarc
-Applied Statistics Division, Indian Statistical Institute, Kolkata, India
-TechBLA Solutions, Kolkata, India
-ETH, Zurich, Switzerland"
 8d44861cfcb5159e0a1afb9d50f3d2c6083f605a,3 D SUPER-RESOLUTION APPROACH FOR SPARSE LASER SCANNER DATA,"D SUPER-RESOLUTION APPROACH FOR SPARSE LASER SCANNER DATA
 S. Hosseinyalamdarya∗, A. Yilmaza
 Photogrammetric Computer Vision (PCV) Lab
 070 Neil avenue, Columbus, OH 43212,
 Commission VI, WG VI/4
 KEY WORDS: 3D Super-resolution, Geometric Surface Reconstruction, Diffusion Equations, isotropic and anisotropic"
-8d19cfe643582fae03ce024efaf117d1efef5e58,A Robust Likelihood Function for 3D Human Pose Tracking,"This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication.
-The final version of record is available at http://dx.doi.org/10.1109/TIP.2014.2364113
-A Robust Likelihood Function for 3D Human Pose
-Tracking
-Weichen Zhang, Student Member, IEEE, Lifeng Shang, Member, IEEE, Antoni B. Chan, Member, IEEE,"
 8de2dbe2b03be8a99628ffa000ac78f8b66a1028,Action Recognition in Videos,"´Ecole Nationale Sup´erieure dInformatique et de Math´ematiques Appliqu´ees de Grenoble
 INP Grenoble – ENSIMAG
 UFR Informatique et Math´ematiques Appliqu´ees de Grenoble
@@ -17181,42 +14737,6 @@ Received: 30 September 2008 / Accepted: 14 September 2009 / Published online: 25
 8d6d0fdf4811bc9572326d12a7edbbba59d2a4cc,SchiNet: Automatic Estimation of Symptoms of Schizophrenia from Facial Behaviour Analysis,"SchiNet: Automatic Estimation of Symptoms of
 Schizophrenia from Facial Behaviour Analysis
 Mina Bishay, Petar Palasek, Stefan Priebe, and Ioannis Patras"
-8d4f2339fcadc2d1ef2126a11dce08ce7cb75bdd,Subspace Clustering via Optimal Direction Search,"Subspace Clustering via Optimal Direction Search
-Mostafa Rahmani, Student Member, IEEE and George K. Atia, Member, IEEE"
-8d646ac6e5473398d668c1e35e3daa964d9eb0f6,Memory-efficient Global Refinement of Decision-Tree Ensembles and its Application to Face Alignment.,"MEMORY-EFFICIENT GLOBAL REFINEMENT OF DECISION-TREE ENSEMBLES AND
-ITS APPLICATION TO FACE ALIGNMENT
-Nenad Markuˇs†
-Ivan Gogi´c†
-Igor S. Pandˇzi´c†
-J¨orgen Ahlberg‡
-University of Zagreb, Faculty of Electrical Engineering and Computing, Unska 3, 10000 Zagreb, Croatia
-Computer Vision Laboratory, Dept. of Electrical Engineering, Link¨oping University, SE-581 83 Link¨oping, Sweden"
-8d156f3b4f1ad5d041ae9f50a0b879e25c80749e,THE HIT OR MISS COUNT OF PROBE IMAGES FOR TEN TIMES S,"International Journal of Scientific & Engineering Research, Volume 4, Issue 6, June 2013
-ISSN 2229-5518
-A New Approach for Face Recognition and Age
-Classification using LDP
-M Rama Bai
-Professor, Dept of CSE, M.G.I.T, JNTUH, Hyderabad, Andhra Pradesh, INDIA"
-8dbbaacb2585c9f06306601a81eef2c53e565ad1,Visual Systems for Interactive Exploration and Mining of Large-Scale Neuroimaging Data Archives,"NEUROINFORMATICS
-METHODS ARTICLE
-published: 23 April 2012
-doi: 10.3389/fninf.2012.00011
-Visual systems for interactive exploration and mining of
-large-scale neuroimaging data archives
-Ian Bowman, Shantanu H. Joshi and John D. Van Horn*
-Laboratory of Neuro Imaging, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
-Edited by:
-Ulla Ruotsalainen, Tampere University
-of Technology, Finland
-Reviewed by:
-Stephen C. Strother, University of
-Toronto, Canada
-Chung-Chuan Lo, National Tsing Hua
-University, Taiwan
-*Correspondence:
-John D. Van Horn, Laboratory of
-Neuro Imaging, Department of
-Neurology, David Geffen School of"
 8d3fbdb9783716c1832a0b7ab1da6390c2869c14,Discriminant Subspace Analysis for Uncertain Situation in Facial Recognition,"Discriminant Subspace Analysis for Uncertain
 Situation in Facial Recognition
 Pohsiang Tsai, Tich Phuoc Tran, Tom Hintz and Tony Jan
@@ -17261,27 +14781,9 @@ will help to push the frontiers of 3D face recognition.
 Three dimensional face recognition is an active research
 topic in biometrics [2, 3]. While 2D pictures can be cap-
 tured quickly, non-intrusively, and easily by widely avail-"
-8de7c496c1dac3be5fa55de72867325153b119bd,Robust Face Recognition using Key-point Descriptors,"Robust Face Recognition using Key-point Descriptors
-Soeren Klemm, Yasmina Andreu, Pedro Henriquez and Bogdan J. Matuszewski
-Robotics and Computer Vision Research Laboratory, School of Computing Engineering and Physical Sciences,
-University of Central Lancashire, Preston, U.K.
-Keywords:
-Face Recognition, SIFT, SURF, ORB, Feature Matching, Face Occlusions."
 8db43d306a70e23e2a0e6eb2fda60f14b73f65d0,Multi-Commodity Network Flow for Tracking Multiple People,"Multi-Commodity Network Flow
 for Tracking Multiple People
 Horesh Ben Shitrit, J´erˆome Berclaz, Franc¸ois Fleuret, and Pascal Fua, Fellow, IEEE"
-8dfdfcc3f34263779871d023fad973f4a1966ec0,Internet of vehicles in big data era,"Internet of Vehicles in Big Data Era
-Wenchao Xu, Haibo Zhou, Member, IEEE, Nan Cheng, Member, IEEE, Feng Lyu, Weisen Shi, Jiayin Chen,
-Xuemin (Sherman) Shen, Fellow, IEEE"
-8d5998cd984e7cce307da7d46f155f9db99c6590,ChaLearn looking at people: A review of events and resources,"ChaLearn Looking at People:
-A Review of Events and Resources
-Sergio Escalera1,2, Xavier Bar´o2,3, Hugo Jair Escalante4,5, Isabelle Guyon4,6,
-Dept. Mathematics and Computer Science, UB, Spain,
-Computer Vision Center, UAB, Barcelona, Spain,
-EIMT, Open University of Catalonia, Barcelona, Spain,
-ChaLearn, California, USA, 5 INAOE, Puebla, Mexico,
-6 Universit´e Paris-Saclay, Paris, France,
-http://chalearnlap.cvc.uab.es"
 8d2459ada191d496eeee70f1e817d0ba92075160,The evaluation of different approaches towards using Kinect sensor as a Laser scanner,"The evaluation of different approaches towards using
 Kinect sensor as a Laser scanner
 Bachelor of Science Thesis Software Engineering and Management
@@ -17321,11 +14823,6 @@ Laure"
 Event-based Dynamic Face Detection and
 Tracking Based on Activity
 Gregor Lenz, Sio-Hoi Ieng and Ryad Benosman"
-8d8461ed57b81e05cc46be8e83260cd68a2ebb4d,Age identification of Facial Images using Neural Network,"Age identification of Facial Images using Neural
-Network
-Sneha Thakur, Ligendra Verma
-CSE Department,CSVTU
-RIT, Raipur, Chhattisgarh , INDIA"
 8d97e0102b5d89c62e5c6697eeaaefc82b36c809,Bottom-up attention orienting in young children with autism.,"J Autism Dev Disord (2014) 44:664–673
 DOI 10.1007/s10803-013-1925-5
 O R I G I N A L P A P E R
@@ -17354,33 +14851,11 @@ tasks. [1].
 We  trained  our  classifier  on  three  databases:  the
 Cohn-Kanade Extended Database (CK+) [2], the Japanese
 Female  Facial Expression  Database (JAFFE) [3], and the"
-8d559aeefb291d5b017c263a49f38e8a28439344,Visually-Driven Semantic Augmentation for Zero-Shot Learning,"VDSA: VISUALLY-DRIVEN SEMANTIC AUGMENTATION FOR ZSL
-Visually-Driven Semantic Augmentation for
-Zero-Shot Learning
-Abhinaba Roy1,2
-Jacopo Cavazza1
-Vittorio Murino1,3
-Pattern Analysis and Computer Vision
-Istituto Italiano di Tecnologia
-Genova, Italy
-Department of Naval, Electrical,
-Electronic and Telecommunications
-Engineering
-University of Genova, Italy
-Department of Computer Science
-University of Verona, Italy"
 8d8afef13a8f6195d3b874231e5e767cf62f3c50,Deep Ranking for Person Re-Identification via Joint Representation Learning,"Deep Ranking for Person Re-identiﬁcation via
 Joint Representation Learning
 Shi-Zhe Chen, Chun-Chao Guo, Student Member, IEEE, and Jian-Huang Lai, Senior Member, IEEE"
 8d1adf0ac74e901a94f05eca2f684528129a630a,Facial Expression Recognition Using Facial Movement Features,"Facial Expression Recognition Using Facial
 Movement Features"
-8de065f412a7d739dff40044212c8506b5c52bf7,Multi-Person Pose Estimation for PoseTrack with Enhanced Part Affinity Fields,"Multi-Person Pose Estimation for PoseTrack with
-Enhanced Part Affinity Fields
-Xiangyu Zhu, Yingying Jiang, and Zhenbo Luo
-Machine Learning Lab
-Samsung R&D Institute of China, Beijing
-Beijing, China
-{xiangyu.zhu, yy.jiang}"
 8df3bef321cd1b259cf6fb1ef264a2e885610044,Interactively Learning Visually Grounded Word Meanings from a Human Tutor,"Proceedings of the 5th Workshop on Vision and Language, pages 48–53,
 Berlin, Germany, August 12 2016. c(cid:13)2016 Association for Computational Linguistics"
 8d7a55d184659ac97d02061a660ae4e30604185b,Penalizing Top Performers: Conservative Loss for Semantic Segmentation Adaptation,"Penalizing Top Performers: Conservative Loss
@@ -17394,15 +14869,6 @@ Francesco Puja, Simone Grazioso, Antonio Tammaro, Valsmis Ntouskos, Marta Sanzar
 Speed, Flexibility, and Quality in Neural Style Transfer
 Chi Zhang and Yixin Zhu and Song-Chun Zhu
 International Center for AI and Robot Autonomy (CARA)"
-4a64b020c72db15a729939a2c041ef4f5830f0f7,Challenges of Ground Truth Evaluation of Multi-target Tracking,"Challenges of Ground Truth Evaluation of Multi-Target Tracking
-Anton Milan1
-Konrad Schindler2
-Stefan Roth1
-Department of Computer Science, TU Darmstadt
-Photogrammetry and Remote Sensing Group, ETH Z¨urich"
-4a0f98d7dbc31497106d4f652968c708f7da6692,Real-time eye gaze direction classification using convolutional neural network,"Real-time Eye Gaze Direction Classiﬁcation Using
-Convolutional Neural Network
-Anjith George, Member, IEEE, and Aurobinda Routray, Member, IEEE"
 4a303369828d9334022a0f5e8ad2b1a715d1c0c9,Deep Metric Learning by Online Soft Mining and Class-Aware Attention,"Deep Metric Learning by Online Soft Mining and Class-Aware Attention
 Xinshao Wang1,2, Yang Hua1,2, Elyor Kodirov2, Guosheng Hu1,2, Neil M. Robertson1,2
 School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, UK
@@ -17482,29 +14948,6 @@ Alexander Kolesnikov 1 Christoph H. Lampert 1"
 using Hand-Centric Features and Script Data
 Marcus Rohrbach · Anna Rohrbach · Michaela Regneri ·
 Sikandar Amin · Mykhaylo Andriluka · Manfred Pinkal · Bernt Schiele"
-4a19f6545473363b16d4a10ed13fef29b38856d3,What is a Salient Object? A Dataset and a Baseline Model for Salient Object Detection,"What is a salient object? A dataset and
-baseline model for salient object detection
-Ali Borji, Member, IEEE"
-4af997701ce14ba689f7f964a72bcae0a2432435,The role of gaze direction in face memory in autism spectrum disorder.,"RESEARCH ARTICLE
-The Role of Gaze Direction in Face Memory in Autism
-Spectrum Disorder
-Safa R. Zaki and Shannon A. Johnson
-We tested the hypothesis that the direction of gaze of target faces may play a role in reported face recognition deﬁcits
-in those with an autism spectrum disorder (ASD). In previous studies, typically developing children and adults better
-remembered faces in which the eyes were gazing directly at them compared with faces in which the eyes were averted.
-In the current study, high-functioning children and adolescents with an ASD and age- and IQ-matched typically
-developing controls were shown a series of pictures of faces in a study phase. These pictures were of individuals whose
-gaze was either directed straight ahead or whose gaze was averted to one side. We tested the memory for these study faces
-in a recognition task in which the faces were shown with their eyes closed. The typically developing group better
-remembered the direct-gaze faces, whereas the ASD participants did not show this effect. These results imply that there
-may be an important link between gaze direction and face recognition abilities in ASD. Autism Res 2013, (cid:129)(cid:129): (cid:129)(cid:129)–(cid:129)(cid:129).
-© 2013 International Society for Autism Research, Wiley Periodicals, Inc.
-Keywords: autism spectrum disorder; face recognition; eye-contact; face-processing; gaze
-Face processing is a pivotal component of human
-ommunication and interaction. There is evidence that
-people with an autism spectrum disorder (ASD), a disor-
-der characterized by impairments in social interaction
-nd communication as well as restricted range of interests"
 4af25075729aa4d0fa4ecf6c948f59ec15bf9565,Analysis and Evaluation of Alternatives and Advanced Solutions for System Elements Contractual Document Evolution Executive Summary,"Project N° IST-2002-507634 - BioSecure
 D 9.1.2 - Revision: b3
 4 June 2005
@@ -17574,23 +15017,6 @@ institutional repository. Authors requiring further information
 regarding Elsevier’s archiving and manuscript policies are
 encouraged to visit:
 http://www.elsevier.com/copyright"
-4ac4b0a2d06ff5df1cc4941f8ae47843b4593bba,American Sign Language fingerspelling recognition from video: Methods for unrestricted recognition and signer-independence,"American Sign Language ﬁngerspelling recognition
-from video: Methods for unrestricted recognition
-nd signer-independence
-Taehwan Kim
-A thesis submitted
-in partial fulﬁllment of the requirements for
-the degree of
-Doctor of Philosophy in Computer Science
-t the
-Toyota Technological Institute at Chicago
-Chicago, Illionois
-August 2016
-Thesis Committee:
-Vassilis Athitsos
-Karen Livescu (Thesis Advisor)
-Greg Shakhnarovich
-Yisong Yue"
 4ac3cd8b6c50f7a26f27eefc64855134932b39be,Robust Facial Landmark Detection via a Fully-Convolutional Local-Global Context Network,"Robust Facial Landmark Detection
 via a Fully-Convolutional Local-Global Context Network
 Daniel Merget
@@ -17731,18 +15157,6 @@ Application to Facial Expression
 Recognition
 Dissertation
 Matthias Wimmer"
-4a9afcc6ba45c0ff05ea93d306ff73ede32f7ed4,Multiple-shot People Re-identify based on Feature Selection with Sparsity,"International Journal of Hybrid Information Technology
-Vol.8, No.1 (2015), pp.27-34
-http://dx.doi.org/10.14257/ijhit.2015.8.1.03
-Multiple-shot People Re-identify based on Feature Selection with
-Sparsity
-Dongping Zhang, Yanjie Li, Jiao Xu and Ye Shen
-College of Information Engineering, China Jiliang University, Hangzhou 310018,
-China"
-4abaebe5137d40c9fcb72711cdefdf13d9fc3e62,Dimension Reduction for Regression with Bottleneck Neural Networks,"Dimension Reduction for Regression
-with Bottleneck Neural Networks
-Elina Parviainen
-BECS, Aalto University School of Science and Technology, Finland"
 4aa18f3a1c85f7a09d3b0d6b28c0339199892d60,The Application of Neural Networks for Facial Landmarking on Mobile Devices,
 4a45b8f8decc178305af06d758ac7428a9070fad,Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data,"Augmented CycleGAN: Learning Many-to-Many Mappings
 from Unpaired Data
@@ -17912,17 +15326,6 @@ Mohsen Hejrati
 UC Irvine
 Deva Ramanan
 UC Irvine"
-1b55a0ad1d4738a7d46ed787542991d4a05ae27e,Accurate Object Detection and Semantic Segmentation using Gaussian Mixture Model and CNN,"IJARCCE
-ISSN (Online) 2278-1021
-ISSN (Print) 2319 5940
-International Journal of Advanced Research in Computer and Communication Engineering
-Vol. 4, Issue 11, November 2015
-Accurate Object Detection and Semantic
-Segmentation using Gaussian Mixture Model and
-Sakshi Jain1, Satish Dehriya2, Yogendra Kumar Jain3
-Research Scholar, Computer Science & Engg, Samrat Ashok Technological Institute, Vidisha (M.P.), India1
-Assist. Professor, Computer Science & Engg, Samrat Ashok Technological Institute, Vidisha (M.P.), India 2
-Head of the Department, Computer Science & Engg, Samrat Ashok Technological Institute, Vidisha (M.P.), India3"
 1b457646a300c744bf098f0bfde641042602262a,Holistic and Gabor-local Feature-fusion for Face Recognition using Canonical Correlation Analysis ( CCA ),"Holistic and Gabor-local Feature-fusion for Face Recognition
 using Canonical Correlation Analysis (CCA)
 Hendra Kusuma1), Wirawan2), Adi Soeprijanto3)
@@ -18109,17 +15512,6 @@ IBM China Research Lab, PRC
 fminliml,baoshhua,qianwh,
 Nalini K. Ratha
 IBM Watson Research Center, USA"
-1b6afc2cdf931a02df46d5052b4409c770ef8660,An Approach to Analyse Facial Expression from Videos using Pyramid Histogram of Orientation Gradients,"International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622
-International Conference on Industrial Automation and Computing (ICIAC- 12-13th April 2014)
-RESEARCH ARTICLE
-OPEN ACCESS
-An Approach to Analyse Facial Expression from Videos using
-Pyramid Histogram of Orientation Gradients
-Ashish D. Lonare1, Shweta V. Jain2
-Department of Computer Science and Engineering,  Shri Ramdeobaba College of Engineering and
-Management Nagpur, India
-Department of Computer Science and Engineering,  Shri Ramdeobaba College of Engineering and
-Management Nagpur, India"
 1be18a701d5af2d8088db3e6aaa5b9b1d54b6fd3,ENHANCEMENT OF FAST FACE DETECTION ALGORITHM BASED ON A CASCADE OF DECISION TREES,"ENHANCEMENT OF FAST FACE DETECTION ALGORITHM BASED ON A CASCADE OF
 DECISION TREES
 V. V. Khryashchev a, *, A. A. Lebedev a, A. L. Priorov a
@@ -18159,11 +15551,6 @@ Farzaneh Mahdisoltani1,2, Guillaume Berger2, Waseem Gharbieh2
 David Fleet1, Roland Memisevic2
 {farzaneh,
 University of Toronto1, Twenty Billion Neurons2"
-1b71e4b59358ed7ecf6117e19fc944307e58a7af,3 D Spectral Nonrigid Registration of Facial Expression Scans,"IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
-D Spectral Nonrigid Registration of
-Facial Expression Scans
-Gabriel L. Cuendet, Student member, IEEE, Christophe Ecabert, Marina Zimmermann, Student
-member, IEEE, Hazım K. Ekenel, and Jean-Philippe Thiran, Senior Member, IEEE"
 1b3505018e39a794eab032e7e313784b21be42e9,Saliency based Person Re-Identification in Video using Colour Features,"GRD Journals- Global Research and Development Journal for Engineering | Volume 1 | Issue 10 | September 2016
 ISSN: 2455-5703
 Saliency based Person Re-Identification in Video
@@ -18193,12 +15580,6 @@ Face Detection Evaluation: A New Approach Based on
 the Golden Ratio (cid:8)
 M. Hassaballah (cid:1) Kenji Murakami (cid:1) Shun Ido
 Received: 1 Jan. 2011 /Revised: 9 March 2011/ Accepted: date"
-1bbd83aeccae06f7d1b048f12566943ac824a490,Low-level multimodal integration on Riemannian manifolds for automatic pedestrian detection,"Low-level Multimodal Integration on Riemannian
-Manifolds for Automatic Pedestrian Detection
-Marco San-Biagio∗, Marco Crocco∗, Marco Cristani∗†, Samuele Martelli∗ and Vittorio Murino∗
-Pattern Analysis & Computer Vision (PAVIS), Istituto Italiano di Tecnologia (IIT), Genova - Italy
-Dipartimento di Informatica, University of Verona, Verona - Italy
-Email: and"
 1b7b95ee13d91e9c768de6417a8919f2a3384599,A Probabilistic U-Net for Segmentation of Ambiguous Images,"A Probabilistic U-Net for Segmentation of Ambiguous
 Images
 Simon A. A. Kohl1∗,2,, Bernardino Romera-Paredes1, Clemens Meyer1, Jeffrey De Fauw1,
@@ -18273,26 +15654,6 @@ DOI: 10.5829/idosi.mejsr.2014.20.01.11434
 A Comparative Analysis of Gender Classification Techniques
 Sajid Ali Khan, Maqsood Ahmad, Muhammad Nazir and Naveed Riaz
 Shaheed Zulfikar Ali Bhutto Institute of Science and Technology, Islamabad, Pakistan"
-d493288998422ee30fe67370497a8a35108f81e7,"Key words- Face Detection, Eigenface, Feature","Shishir Kumar et. al. / (IJCSE) International Journal on Computer Science and Engineering
-Vol. 02, No. 03, 2010, 889-894
-Architecture for Mobile based Face Detection / Recognition
-Shishir Kumar, Priyank Singh, Vivek Kumar
-Department of CSE, Jaypee Institute of Engineering & Technology
-Guna, India
-transferring an image from the client side to the server
-side.
-The client-server architecture can be implemented in
-two ways:
-)  Client-Server architecture using Bluetooth.
-)  Client-Server
-protocol.
-rchitecture
-using  HTTP
-rates
-recognition  and
-detection framework
-Each  of  the  two  approaches  has  its  advantages  and
-disadvantages,  usage  area  and  is  complementary  to"
 d4ced2086ccd9259ade8fabdba14e0e4d9fc0c40,A Mobile Imaging System for Medical Diagnostics,"A Mobile Imaging System for Medical
 Diagnostics
 Sami Varjo and Jari Hannuksela
@@ -18303,11 +15664,6 @@ d48bd355d091e7ae75ade4e878fe346741e7da1a,Can You Spot the Semantic Predicate in
 Christopher Reale, Claire Bonial, Heesung Kwon and Clare R. Voss
 U.S. Army Research Lab, Adelphi, Maryland 20783
 {claire.n.bonial.civ, heesung.kwon.civ,"
-d40c4e370d35264e324e4e3d5df59e51518c9979,A Transfer Learning based Feature-Weak-Relevant Method for Image Clustering,"A Transfer Learning based Feature-Weak-Relevant Method for
-Image Clustering
-Bo Dong, Xinnian Wang
-Dalian Maritime University
-Dalian, China"
 d41c11ebcb06c82b7055e2964914b9af417abfb2,CDI-Type I : Unsupervised and Weakly-Supervised Discovery of Facial Events 1,"CDI-Type I: Unsupervised and Weakly-Supervised
 Introduction
 Discovery of Facial Events
@@ -18328,11 +15684,6 @@ expression recognition and analysis is slowed. For the most detailed and compreh
 systems, such as Facial Action Coding System (FACS), three to four months is typically required to train
 coder (’coding’ refers to the labeling of video using behavioral descriptors). Once trained, each minute
 of video may require 1 hour or more to code [9]. No wonder relatively few databases are yet available,"
-d40bd8d44fe78952769a9bb04fe74ce38ef07534,Locally Adaptive Learning Loss for Semantic Image Segmentation,"Locally Adaptive Learning Loss for Semantic Image Segmentation
-Jinjiang Guo1,2, Pengyuan Ren1, Aiguo Gu1, Jian Xu1, Weixin Wu1
-Beijing NetPosa Technologies Co., Ltd. Beijing, China
-Institut National des Sciences Appliqu´ees de Lyon, Lyon, France
-{renpengyuan, guaiguo, xujian,"
 d42142285c46207a16bd4294e437d504e419a9b7,Varying image description tasks : spoken versus written descriptions,"Varying image description tasks: spoken versus written descriptions
 Emiel van Miltenburg
 Vrije Universiteit Amsterdam
@@ -18340,14 +15691,6 @@ Ruud Koolen
 Tilburg University
 Emiel Krahmer
 Tilburg University"
-d4885ca24189b4414031ca048a8b7eb2c9ac646c,"Efficient Facial Representations for Age, Gender and Identity Recognition in Organizing Photo Albums using Multi-output CNN","Ef‌f‌icient Facial Representations for Age, Gender
-nd Identity Recognition in Organizing Photo
-Albums using Multi-output CNN
-Andrey V. Savchenko
-Samsung-PDMI Joint AI Center, St. Petersburg Department of Steklov Institute of
-Mathematics
-National Research University Higher School of Economics
-Nizhny Novgorod, Russia"
 d44ca9e7690b88e813021e67b855d871cdb5022f,"Selecting, Optimizing and Fusing `Salient' Gabor Features for Facial Expression Recognition","QUT Digital Repository:
 http://eprints.qut.edu.au/
 Zhang, Ligang and Tjondronegoro, Dian W. (2009) Selecting, optimizing and
@@ -18375,14 +15718,6 @@ Ki-Young Moon
 Information Security
 Research Division, ETRI
 S. Korea"
-d4e669d5d35fa0ca9f8d9a193c82d4153f5ffc4e,A Lightened CNN for Deep Face Representation,"A Lightened CNN for Deep Face Representation
-Xiang Wu
-School of Computer and Communication Engineering
-University of Science and Technology Beijing, Beijing, China
-Ran He, Zhenan Sun
-National Laboratory of Pattern Recognition
-Institute of Automation Chinese Academy of Sciences, Beijing, China
-{rhe,"
 d497b9e50dc2aacfb1693ca4de6ebf904404d98d,Patch Based Approaches for the Recognition of Visual Object Classes - A Survey,"ALBERT-LUDWIGS-UNIVERSIT ¨AT FREIBURG
 INSTITUT F ¨UR INFORMATIK
 Lehrstuhl f¨ur Mustererkennung und Bildverarbeitung
@@ -18393,41 +15728,6 @@ Alexandra Teynor
 November, 2006"
 d444368421f456baf8c3cb089244e017f8d32c41,CNN for IMU assisted odometry estimation using velodyne LiDAR,"CNN for IMU Assisted Odometry Estimation using Velodyne LiDAR
 Martin Velas, Michal Spanel, Michal Hradis, and Adam Herout"
-d4c657ce3b7e47237201393aa6bba0e19442bfd2,Interpolation Based Tracking for Fast Object Detection in Videos,"Interpolation Based Tracking for Fast Object
-Detection In Videos
-Rahul Jain, Pramod Sankar K.*, C. V. Jawahar
-Center for Visual Information Technology
-pramod
-IIIT-Hyderabad, INDIA"
-d45dc3546702db7fcef8d4863db319ca84cc8d3d,How emotional are you? Neural Architectures for Emotion Intensity Prediction in Microblogs,"How emotional are you? Neural Architectures for Emotion Intensity
-Prediction in Microblogs
-Devang Kulshreshtha∗, Pranav Goel∗, and Anil Kumar Singh
-Indian Institute of Technology (Banaras Hindu University) Varanasi
-{devang.kulshreshtha.cse14, pranav.goel.cse14,
-Varanasi, Uttar Pradesh, India"
-d4fc055aa72b71397bdd223af212a632c026246e,Reimagining Health Data Exchange: An Application Programming Interface–Enabled Roadmap for India,"JOURNAL OF MEDICAL INTERNET RESEARCH
-Balsari et al
-Policy Proposal
-Reimagining Health Data Exchange: An Application Programming
-Interface–Enabled Roadmap for India
-Satchit  Balsari1,2,  MD,  MPH;  Alexander  Fortenko3,  MD,  MPH;  Joaquín  A  Blaya4,  PhD;  Adrian  Gropper5,  MD;
-Malavika Jayaram6, LLM; Rahul Matthan7, LLM; Ram Sahasranam8; Mark Shankar9, MD; Suptendra N Sarbadhikari10,
-PhD; Barbara E Bierer11, MD; Kenneth D Mandl12,13, MD; Sanjay Mehendale14, MD, MPH; Tarun Khanna9, PhD
-Beth Israel Deaconess Medical Center, Harvard Medical School, Department of Emergency Medicine, Boston, MA, United States
-Harvard FXB Center for Health and Human Rights, Boston, MA, United States
-NewYork-Presyterian Hospital, Emergency Medicine, New York, NY, United States
-The Human Diagnosis Project, Washington DC, DC, United States
-5Patient Privacy Rights, Boston, MA, United States
-6Digital Asia Hub, Hong Kong, China
-7TriLegal, Bangalore, India
-8Athenahealth, San Francisco, CA, United States
-9Harvard Business School, Boston, MA, United States
-0International Institute of Health Management Research, New Delhi, India
-1Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
-2Boston Children's Hospital, Computational Health Informatics Program, Boston, MA, United States"
-d497543834f23f72f4092252b613bf3adaefc606,Density-Adaptive Kernel based Re-Ranking for Person Re-Identification,"Density-Adaptive Kernel based Re-Ranking for
-Person Re-Identiﬁcation
-Ruopei Guo, Chun-Guang Li, Member, IEEE, Yonghua Li, Jiaru Lin, and Jun Guo"
 d4f8168242f688af29bcbbe1cc5aec7cd12a601c,Edinburgh Research Explorer Visually Grounded Meaning Representations,"Visually Grounded Meaning Representations
 Citation for published version:
 Silberer, C, Ferrari, V & Lapata, M 2016, 'Visually Grounded Meaning Representations' IEEE Transactions
@@ -18482,40 +15782,6 @@ proposed changes to the DSM-5 and ICD-11. Differences across development are inc
 new classiﬁcation frameworks. Conclusions: It is crucial to balance the needs of clinical practice in
 ASD diagnostic systems, with neurobiologically based theories that address the associations between
 social-communication and restricted/repetitive dimensions in individuals. Clarifying terminology,"
-d47a2c0828bcfa4ebe0b7831f0b389ea385a8ce9,Local descriptors based random forests for human detection,"TAÏP CHÍ PHAÙT TRIEÅN KH&CN, TAÄP 18, SOÁ K6- 2015
-Local descriptors based random forests for
-human detection
-  Van-Dung Hoang
-Quang Binh University, Vietnam
-  My-Ha Le
-University of Technical Education Ho Chi Minh City, Vietnam
-  Hyun-Deok Kang
-Ulsan National Institute of Science and Technology, Korea
-  Kang-Hyun Jo
-University of Ulsan, Korea
-(Manuscript Received on July 15, 2015, Manuscript Revised August 30, 2015)
-local
-forest  using"
-d82681348489f4f04690e65b9ffe21b68c89b5ff,Cross-Subject EEG Feature Selection for Emotion Recognition Using Transfer Recursive Feature Elimination,"ORIGINAL RESEARCH
-published: 10 April 2017
-doi: 10.3389/fnbot.2017.00019
-Cross-Subject EEG Feature Selection
-for Emotion Recognition Using
-Transfer Recursive Feature
-Elimination
-Zhong Yin 1*, Yongxiong Wang 1*, Li Liu 1, Wei Zhang 1 and Jianhua Zhang 2
-Shanghai Key Lab of Modern Optical System, Engineering Research Center of Optical Instrument and System, Ministry of
-Education, University of Shanghai for Science and Technology, Shanghai, China, 2 Department of Automation, East China
-University of Science and Technology, Shanghai, China
-Using machine-learning methodologies to analyze EEG signals becomes increasingly
-ttractive for recognizing human emotions because of the objectivity of physiological
-data and the capability of the learning principles on modeling emotion classiﬁers from
-heterogeneous features. However, the conventional subject-speciﬁc classiﬁers may
-induce additional burdens to each subject for preparing multiple-session EEG data
-s training sets. To this end, we developed a new EEG feature selection approach,
-transfer recursive feature elimination (T-RFE), to determine a set of the most robust EEG
-indicators with stable geometrical distribution across a group of training subjects and
-speciﬁc testing subject. A validating set is introduced to independently determine"
 d8af6a45eaea68adda8597ae65f91ece152f7b21,Sparse and Dense Data with CNNs: Depth Completion and Semantic Segmentation,"Sparse and Dense Data with CNNs:
 Depth Completion and Semantic Segmentation
 Maximilian Jaritz1, 2, Raoul de Charette1, Emilie Wirbel2, Xavier Perrotton2, Fawzi Nashashibi1
@@ -18531,14 +15797,6 @@ Using  Advanced  Correlation
 Filters
 Chee  Kiat  Ng
 Advisor:  Prof.  Khosla/Reviere"
-d82b93f848d5442f82154a6011d26df8a9cd00e7,NEURAL NETWORK BASED AGE CLASSIFICATION USING LINEAR WAVELET TRANSFORMS,"NEURAL NETWORK BASED AGE CLASSIFICATION USING
-LINEAR WAVELET TRANSFORMS
-NITHYASHRI JAYARAMAN1 & G.KULANTHAIVEL2
-Department of Computer Science & Engineering,
-Sathyabama University Old Mamallapuram Road, Chennai, India
-Electronics Engineering, National Institute of  Technical Teachers
-Training & Research, Taramani, Chennai, India
-E-mail :"
 d850aff9d10a01ad5f1d8a1b489fbb3998d0d80e,Recognizing and Segmenting Objects in the Presence of Occlusion and Clutter,"UNIVERSITY OF CALIFORNIA,
 IRVINE
 Recognizing and Segmenting Objects in the Presence of Occlusion and Clutter
@@ -18552,24 +15810,6 @@ Dissertation Committee:
 Professor Charless Fowlkes, Chair
 Professor Deva Ramanan
 Professor Alexander Ihler"
-d8e061960423a17748dedbcfe4b6a6918f79c262,Fast Prototyping and Computationally Intensive Experiments,"Armadillo: An Open Source C++ Linear Algebra Library for
-Fast Prototyping and Computationally Intensive Experiments
-Conrad Sanderson
-http://conradsanderson.id.au
-Technical Report, NICTA, Australia
-http://nicta.com.au
-September 2010
-(revised December 2011)"
-d8cf6b19c75489dd7a5f4107e2e3ec494274da41,Partial Relevance in Interactive Facial Image Retrieval,"Partial Relevance in Interactive
-Facial Image Retrieval
-Zhirong Yang and Jorma Laaksonen(cid:1)
-Laboratory of Computer and Information Science,
-Helsinki University of Technology,
-P.O. Box 5400, FI-02015 HUT, Espoo, Finland
-{zhirong.yang,"
-d8d1fb804d1f4760393c6fd70c9072fa1b39f02c,An Efficient Approach to Onboard Stereo Vision System Pose Estimation,"An Efﬁcient Approach to Onboard Stereo
-Vision System Pose Estimation
-Angel Domingo Sappa, Member, IEEE, Fadi Dornaika, Daniel Ponsa, David Gerónimo, and Antonio López"
 d8b3bebe39f5f69d68cdb5c04b44aba3f9b5ae02,Active Vision System with Human Detection Using RGB-D images and machine learning algorithms,"Active Vision System with Human Detection
 Using RGB-D images and machine learning algorithms
 Master’s thesis in Applied Physics and in Biomedical Engineering
@@ -18611,25 +15851,10 @@ d813ec3a3442f2885b76ac0133c4c5d76f9f8065,Panoptic Studio: A Massively Multiview
 for Social Interaction Capture
 Hanbyul Joo, Tomas Simon, Xulong Li, Hao Liu, Lei Tan, Lin Gui, Sean Banerjee, Timothy Godisart,
 Bart Nabbe, Iain Matthews, Takeo Kanade, Shohei Nobuhara, and Yaser Sheikh"
-d86fabd4498c8feaed80ec342d254fb877fb92f5,Region-Object Relevance-Guided Visual Relationship Detection,"Y. GOUTSU: REGION-OBJECT RELEVANCE-GUIDED VRD
-Region-Object Relevance-Guided
-Visual Relationship Detection
-Yusuke Goutsu
-National Institute of Informatics
-Tokyo, Japan"
 d88eb94d7054d2668b1a8dfa311721f37ae1f059,Straight to the Facts: Learning Knowledge Base Retrieval for Factual Visual Question Answering,"Straight to the Facts: Learning Knowledge Base
 Retrieval for Factual Visual Question Answering
 Medhini Narasimhan, Alexander G. Schwing
 University of Illinois Urbana-Champaign"
-d806790866ab9bad77f60436fe77232db8e0c1ba,Deep Directional Network for Object Tracking,"Article
-Deep Directional Network for Object Tracking
-Zhaohua Hu 1,2,* and Xiaoyi Shi 1
-School of Electronic & Information Engineering, Nanjing University of Information Science & Technology,
-Nanjing 210044, China;
-Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology,
-Nanjing University of Information Science & Technology, Nanjing 210044, China
-* Correspondence: Tel.: +86-025-58731196
-Received: 10 October 2018; Accepted: 1 November 2018; Published: 5 November 2018"
 d8b8e165279ca2091d5af1440ed974db4792250f,Mean Response-Time Minimization of a Soft-Cascade Detector,
 d83ae5926b05894fcda0bc89bdc621e4f21272da,Frugal Forests : Learning a Dynamic and Cost Sensitive Feature Extraction Policy for Anytime Activity Classification,"The Thesis committee for Joshua Allen Kelle certiﬁes that this is the approved
 version of the following thesis:
@@ -18701,33 +15926,6 @@ Hui Ding1, Kumar Saketh2, and Jin Sun1
 Interactive and Analytics Lab, Palo Alto Research Center, Palo Alto, CA
 Verizon Labs, Palo Alto, CA
 August 22, 2017"
-d8029237cde893218d21ba551fd127d045ae3422,Eye-Strip based Person Identification based on Non-Subsampled Contourlet Transform,"International Journal of Computer Applications (0975 – 8887)
-Volume 121 – No.12, July 2015
-Eye-Strip based Person Identification based on
-Non-Subsampled Contourlet Transform
-Hemprasad Y. Patil
-Dept. of ECE
-Visvesvaraya National Institute
-of Technology, Nagpur, India
-Ashwin G. Kothari
-Dept. of ECE
-Visvesvaraya National Institute
-of Technology, Nagpur, India
-Kishor M. Bhurchandi
-Dept. of ECE
-Visvesvaraya National Institute
-of Technology, Nagpur, India
-transform
-sub-band"
-d8391151d6e43d8e4ea0d8206a5acb7f9be7439f,Face Fusion Recognition Based on Bit-Plane Image,"The Open Automation and Control Systems Journal, 2015, 7, 835-841
-Send Orders for Reprints to
-Open Access
-Face Fusion Recognition Based on Bit-Plane Image
-Xiaopu Ma1,*, Changwang Liu2 and Li Zhao1
-School of Computer and Information Technology, Nanyang Normal University, Wolong Road 1638, Wolong District,
-73061, Nanyang, Henan, China
-School  of  Software,  Nanyang  Normal  University,  Wolong  Road  1638,  Wolong  District,  473061,  Nanyang,  Henan,
-China"
 d8cfc7d9b13a5e1b21fc81e9f14697ac445c3698,Dynamic and Robust Object Tracking for Activity Recognition. (Suivi dynamique et robuste d'objets pour la reconnaissance d'activités),"Dynamic and Robust Object Tracking for Activity
 Recognition
 Duc Phu Chau
@@ -18872,34 +16070,11 @@ Recognition ?
 Marcelo Armengot, Francesc J. Ferri, and Wladimiro D´ıaz
 Dept. d’Inform`atica, Universitat de Val`encia
 Dr Moliner, 50 46100 Burjassot, Spain"
-5b33a220defa5362e7e1f1b664ad18e466b0515a,Pedestrian Detection for Android Mobile Devices,"017 International Conference on Computer Science and Application Engineering (CSAE 2017)
-ISBN: 978-1-60595-505-6
-Pedestrian Detection for Android Mobile Devices
-Jing Li, Fang Qu and Yingdong Ma*
-Inner Mongolia University, No.235, Daxue west road, Saihan District,
-Hohhot,Inner Mongolia Autonomous Region, China"
 5b25b9053ceafe1cf8258d8daa818a2da80c800f,Assigning affinity-preserving binary hash codes to images,"Assigning af‌f‌inity-preserving
 inary hash codes to images
 Jason Filippou
 Varun Manjunatha
 June 10, 2014"
-5bb24d1250df62a56cab1445f1d8c5c61269b785,Measuring the Temporal Behavior of Real-World Person Re-Identification,"Measuring the Temporal Behavior of Real-World
-Person Re-Identiﬁcation
-Meng Zheng, Student Member, IEEE, Srikrishna Karanam, Member, IEEE,
-nd Richard J. Radke, Senior Member, IEEE"
-5b721f86f4a394f05350641e639a9d6cb2046c45,Detection under Privileged Information,"A short version of this paper is accepted to ACM Asia Conference on Computer and Communications Security (ASIACCS) 2018
-Detection under Privileged Information (Full Paper)∗
-Z. Berkay Celik
-Pennsylvania State University
-Patrick McDaniel
-Pennsylvania State University
-Rauf Izmailov
-Vencore Labs
-Nicolas Papernot,
-Ryan Sheatsley, Raquel Alvarez
-Pennsylvania State University
-Ananthram Swami
-Army Research Laboratory"
 5bb87c7462c6c1ec5d60bde169c3a785ba5ea48f,Targeting Ultimate Accuracy: Face Recognition via Deep Embedding,"Targeting Ultimate Accuracy: Face Recognition via Deep Embedding
 Jingtuo Liu     Yafeng Deng     Tao Bai     Zhengping Wei     Chang Huang
 Baidu Research – Institute of Deep Learning"
@@ -18939,14 +16114,6 @@ global face transformation may be too complex to be modeled directly, it is appr
 tions with a constraint that imposes consistency between neighboring transformations. Local transformations and neighborhood
 onstraints are embedded within a probabilistic framework using two-dimensional hidden Markov models (2D HMMs). We fur-
 ther introduce a new ef‌f‌icient technique, called turbo-HMM (T-HMM) for approximating intractable 2D HMMs. Experimental"
-5b10fa6b4c0921af7b36a58f4fd2d8fca6e3c9b1,Low-Rank Multi-View Learning in Matrix Completion for Multi-Label Image Classification,"Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence
-Low-Rank Multi-View Learning
-in Matrix Completion for Multi-Label Image Classiﬁcation
-Meng Liu†, Yong Luo†§, Dacheng Tao‡, Chao Xu†, and Yonggang Wen§
-Key Laboratory of Machine Perception (MOE), School of EECS, PKU, Beijing 100871, China
-Center for Quantum Computation and Intelligent Systems, UTS, Sydney, NSW 2007, Australia
-§Division of Networks and Distributed Systems School of Computer Engineering, NTU, 639798, Singapore
-{lemolemac,"
 5bcff482bd9652420f8f6b0e6e58ab59a562046e,Bit-Scalable Deep Hashing With Regularized Similarity Learning for Image Retrieval and Person Re-Identification,"Bit-Scalable Deep Hashing with Regularized
 Similarity Learning for Image Retrieval and Person
 Re-identiﬁcation
@@ -18998,10 +16165,6 @@ Gilles Celeux
 INRIA
 Co-directeur de thèse : William Triggs CNRS
 Institut National Recherche en Informatique et Automatique"
-5b1b90a0a6d491b26f427824985d69d5d0693220,Human gender classification: a review,"IEEE SENSORS JOURNAL, VOL. X, NO. X, XXXXXXX 2015
-Human Gender Classiﬁcation: A Review
-Yingxiao Wu, Member, IEEE, Yan Zhuang, Student Member, IEEE, Xi Long, Member, IEEE,
-Feng Lin, Member, IEEE, and Wenyao Xu, Member, IEEE"
 5bf9493564d1ed173aee4dc701d4e62d5f926fe3,Bonnet: An Open-Source Training and Deployment Framework for Semantic Segmentation in Robotics using CNNs,"Bonnet: An Open-Source Training and Deployment Framework
 for Semantic Segmentation in Robotics using CNNs
 Andres Milioto
@@ -19053,21 +16216,6 @@ Transform and optimised feature selection using Ant
 Colony Optimisation in Support Vector Machine
 Sanjay Kumar Pal1, Uday Chourasia 2 and Manish Ahirwar3
 Department of CSE, University Institute of Technology, RGPV, Bhopal, India1,2,3"
-5b6bed112e722c0629bcce778770d1b28e42fc96,Can Your Eyes Tell Me How You Think? A Gaze Directed Estimation of the Mental Activity,"FLOREA ET AL.:CANYOUREYESTELLMEHOWYOUTHINK?
-Can Your Eyes Tell Me How You Think? A
-Gaze Directed Estimation of the Mental
-Activity
-Laura Florea
-http://alpha.imag.pub.ro/common/staff/lflorea
-Corneliu Florea
-http://alpha.imag.pub.ro/common/staff/cflorea
-Ruxandra Vrânceanu
-Constantin Vertan
-http://alpha.imag.pub.ro/common/staff/vertan
-Image Processing and Analysis
-Laboratory, LAPI
-University “Politehnica” of Bucharest
-Bucharest, Romania"
 5b1d78b160560db5f581e65289ce5e2f99eb9b1f,Twitter100k: A Real-World Dataset for Weakly Supervised Cross-Media Retrieval,"Twitter100k: A Real-world Dataset for Weakly
 Supervised Cross-Media Retrieval
 Yuting Hu, Liang Zheng, Yi Yang, and Yongfeng Huang"
@@ -19192,11 +16340,6 @@ Google Research
 Mountain View, CA"
 f5770dd225501ff3764f9023f19a76fad28127d4,Real Time Online Facial Expression Transfer with Single Video Camera,"Real Time Online Facial Expression Transfer
 with Single Video Camera"
-f59ac278349083a50871822ea08172258030265a,Large-Scale Fiber Tracking Through Sparsely Sampled Image Sequences of Composite Materials,"Large-Scale Fiber Tracking Through Sparsely
-Sampled Image Sequences of Composite Materials
-Youjie Zhou, Student Member, IEEE, Hongkai Yu, Student Member, IEEE, Jeff Simmons, Member, IEEE,
-Craig P. Przybyla, and Song Wang, Senior Member, IEEE
-nd accurate"
 f5748711db00d82469ff60e05f62319f1eac90c5,Comparing Apples and Oranges: Off-Road Pedestrian Detection on the NREC Agricultural Person-Detection Dataset,"Comparing Apples and Oranges:
 Off-Road Pedestrian Detection on the NREC Agricultural
 Person-Detection Dataset
@@ -19249,10 +16392,6 @@ Pamela M. Pallett • Shereen J. Cohen •
 Karen R. Dobkins
 Ó Springer Science+Business Media New York 2013
 faces, yet"
-f5a52b69dde106cb69cb7c35dd8ca23071966876,Nonparametric Scene Parsing via Label Transfer,"Nonparametric Scene Parsing
-via Label Transfer
-Ce Liu, Member, IEEE, Jenny Yuen, Student Member, IEEE, and
-Antonio Torralba, Member, IEEE"
 f5adb841e30eb635b91e95c03575f3b8767c9ed5,Learning Optimal Parameters For Multi-target Tracking,"WANG, FOWLKES: LEARNING MULTI-TARGET TRACKING
 Learning Optimal Parameters
 For Multi-target Tracking
@@ -19329,14 +16468,6 @@ Objects with Deep Neural Networks
 Pavel Haluza
 Supervisor: Ing. Tomáš Hodaň
 May 2017"
-f558af209dd4c48e4b2f551b01065a6435c3ef33,AN ENHANCED ATTRIBUTE RERANKING DESIGN FOR WEB IMAGE SEARCH,"International Journal of Emerging Technology in Computer Science & Electronics (IJETCSE)
-ISSN: 0976-1353 Volume 23 Issue 1 –JUNE 2016.
-AN ENHANCED ATTRIBUTE
-RERANKING DESIGN FOR WEB IMAGE
-SEARCH
-Sai Tejaswi Dasari#1 and G K Kishore Babu*2
-#Student,Cse, CIET, Lam,Guntur, India
-* Assistant Professort,Cse, CIET, Lam,Guntur , India"
 f5c99652c4c89e56156faf2bed361a15de6162d5,Towards Large-Scale Multimedia Retrieval Enriched by Knowledge about Human Interpretation Retrospective Survey,"Noname manuscript No.
 (will be inserted by the editor)
 Towards Large-Scale Multimedia Retrieval Enriched
@@ -19386,19 +16517,6 @@ b87eeb3b873d27c68a5a1cdfd9409c14db352d92,Hierarchical Cellular Automata for Visu
 Hierarchical Cellular Automata for Visual Saliency
 Yao Qin* · Mengyang Feng* · Huchuan Lu · Garrison W. Cottrell
 Received: date / Accepted: date"
-b8cd49bfe1bdee9b8e76f3a9521f45a7b6f71dd2,Impact Factor : 4 . 116 IC TM Value : 3 . 00 CODEN : IJESS,"[Lakshmi* et al., 6(2): February, 2017]
-IC™ Value: 3.00
-ISSN: 2277-9655
-Impact Factor: 4.116
-CODEN: IJESS7
-IJESRT
-INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH
-TECHNOLOGY
-VIDEO BASED EMOTION RECOGNITION
-Vijaya Lakshmi R*, Dr. S. Palanivel, Professor
-* M.E II Year Computer Science & Engineering, Annamalai University, Annamalai Nagar-608 002
-Computer Science & Engineering, Annamalai University, Annamalai Nagar-608 002
-DOI: 10.5281/zenodo.268690"
 b8abc0573208786550e0bfbce4bbcac9d048537e,Context-Patch for Difficult Face Recognition Anonymous ICB 2012 submission,"CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE.
 Context-Patch for Difﬁcult Face Recognition
 Anonymous ICB 2012 submission"
@@ -19479,15 +16597,6 @@ Liangchen Song12∗ Cheng Wang23∗ Lefei Zhang1 Bo Du1
 Qian Zhang2 Chang Huang2 Xinggang Wang3
 Wuhan University 2Horizon Robotics
 Huazhong Univ. of Science and Technology"
-b831a08a7098b64485587541485859c9213e6dc2,Applications of 3 D morphable models for faces with expressions,"Applications of 3D morphable models for faces with expressions
-B. Chu1,2, S. Romdhani1 et L. Chen2
-Morpho, SAFRAN Group
-1 boulevard Galliéni 92130 Issy-Les-Moulineaux - France
-{baptiste.chu,
-Université de Lyon, CNRS
-Ecole Centrale de Lyon, LIRIS UMR5205, F-69134
-Lyon, France
-{baptiste.chu,"
 b86bcc153e097838fdb31ffa6c363f1d883512ae,ON-LINE UNSUPERVISED ADAPTATION FOR FACE VERIFICATION USING GAUSSIAN MIXTURE MODELS WITH MULTIPLE USER MODELS,"ON-LINE UNSUPERVISED ADAPTATION FOR
 FACE VERIFICATION USING GAUSSIAN
 MIXTURE MODELS WITH MULTIPLE USER
@@ -19528,12 +16637,6 @@ nxiety using human neuroimaging and behavioral approaches. Each of these
 pproaches alone provides only limited information on genetic and environ-
 mental influences on complex human behavior across development. Together,
 they reflect an emerging field of translational developmental neuroscience in"
-b82a4a0457170258aaf622b81e6f739a220398eb,Probe Strongly Similar Neutral Strongly Dissimilar Quasi-similar Quasi-dissimilar Push Pull,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TMM.2016.2605058, IEEE
-Transactions on Multimedia
-Person Re-identiﬁcation via Ranking Aggregation
-of Similarity Pulling and Dissimilarity Pushing
-Mang Ye, Chao Liang(cid:3), Yi Yu, Zheng Wang, Qingming Leng,
-Chunxia Xiao, Member, IEEE, Jun Chen, Ruimin Hu, Senior Member, IEEE"
 b856c0eb039effce7da9ff45c3f5987f18928bef,Pedestrian Alignment Network for Large-scale Person Re-identification,"Noname manuscript No.
 (will be inserted by the editor)
 Pedestrian Alignment Network for
@@ -19589,24 +16692,6 @@ No Institute Given"
 b8a829b30381106b806066d40dd372045d49178d,A Probabilistic Framework for Joint Pedestrian Head and Body Orientation Estimation,"A Probabilistic Framework for Joint Pedestrian Head
 nd Body Orientation Estimation
 Fabian Flohr, Madalin Dumitru-Guzu, Julian F. P. Kooij, and Dariu M. Gavrila"
-b88e0c3a6a95e5193085a258cd281802852e5a4a,Progression in large Age-gap face verification,"International Research Journal of Engineering and Technology (IRJET)       e-ISSN: 2395-0056
-Volume: 04 Issue: 09 | Sep -2017                     www.irjet.net                                                                 p-ISSN: 2395-0072
-Progression in large Age-gap face verification
-Neha Rahman1, Ankit Chaora2
-,2 Dept. of Electronics and Telecommunication Engineering, Rungta College of Engineering and Technology
-M.tech Scholar, Digital Electronics, 2Assistant Professor
-Bhilai, India
-techniques,  database,  machine
-research projects.
-.  The
-increasing  need  for  surveillance  related
-pplications  due  to  drug  trafficking  and  terrorist
-ctivities etc.
-.  The availability of real time hardware.
-.  The re-emergence of neural network classifiers with
-emphasis on real time computation and adaptation.
----------------------------------------------------------------------***---------------------------------------------------------------------
-.  The increase in emphasis on civilian or commercial"
 b871d1b8495025ff8a6255514ed39f7765415935,Application of Completed Local Binary Pattern for Facial Expression Recognition on Gabor Filtered Facial Images,"Application of Completed Local Binary Pattern for Facial Expression
 Recognition on Gabor Filtered Facial Images
 Tanveer Ahsan, 2Rifat Shahriar, *3Uipil Chong
@@ -19711,16 +16796,6 @@ http://hdl.handle.net/10072/56813
 Link to published version
 http://www.aprs.org.au/dicta13/
 Griffith Research Online"
-4183d1b79d54f5638063e6c59a2a873ee2cd1bed,Multi-cue pedestrian classification with partial occlusion handling,"Multi-Cue Pedestrian Classiﬁcation With Partial Occlusion Handling
-Markus Enzweiler1
-Angela Eigenstetter2
-Bernt Schiele2,3
-Dariu M. Gavrila4,5
-Image & Pattern Analysis Group, Univ. of Heidelberg, Germany
-Computer Science Department, TU Darmstadt, Germany
-MPI Informatics, Saarbr¨ucken, Germany
-Environment Perception, Group Research, Daimler AG, Ulm, Germany
-5 Intelligent Autonomous Systems Group, Univ. of Amsterdam, The Netherlands"
 41de109bca9343691f1d5720df864cdbeeecd9d0,Facial Emotion Recognition: A Survey and Real-World User Experiences in Mixed Reality,"Article
 Facial Emotion Recognition: A Survey and
 Real-World User Experiences in Mixed Reality
@@ -19761,11 +16836,6 @@ PROJECT DESCRIPTION
 Project Overview
 The computer vision research problem of human re-identification or “re-id” is generally posed as follows:
 Given a cropped rectangle of pixels representing a human in one view, a re-id algorithm produces a similarity"
-41decbe12a8aa7996163636e09d1ce1372c271cd,Attentive Fashion Grammar Network for Fashion Landmark Detection and Clothing Category Classification,"Attentive Fashion Grammar Network for
-Fashion Landmark Detection and Clothing Category Classiﬁcation
-Wenguan Wang∗1,2, Yuanlu Xu∗2, Jianbing Shen†1, and Song-Chun Zhu2
-Beijing Lab of Intelligent Information Technology, School of Computer Science, Beijing Institute of Technology, China
-Department of Computer Science and Statistics, University of California, Los Angeles, USA"
 4189aa74550c1761dd5927442d0a98ff3d3d1134,Residual Conv-Deconv Grid Network for Semantic Segmentation,"FOURURE ET AL.: RESIDUAL CONV-DECONV GRIDNET
 Residual Conv-Deconv Grid Network for
 Semantic Segmentation
@@ -19787,12 +16857,6 @@ Christian Wolf2"
 Kaiming He Ross Girshick
 Piotr Doll´ar
 Facebook AI Research (FAIR)"
-4192454749b4fc4a95348e7260c2f5c56a06cafd,Image retrieval using efficient feature vectors generated from compressed domain,"IMAGE RETRIEVAL USING EFFICIENT FEATURE VECTORS
-GENERATED FROM COMPRESSED DOMAIN
-Daidi Zhong, Irek Defée
-Department of Information Technology, Tampere University of Technology.
-P.O. Box 553, FIN-33101 Tampere, Finland
-{daidi.zhong,"
 41fafb5392ad5e33e5169d870812ab5edca301a1,Tree-Structured Stick Breaking Processes for Hierarchical Data,"TREE-STRUCTURED STICK BREAKING PROCESSES
 FOR HIERARCHICAL DATA
 By Ryan P. Adams, Zoubin Ghahramani and Michael I. Jordan
@@ -19865,15 +16929,6 @@ Yang-Ting Chou, Shih-Ming Huang and Jar-Ferr Yang*"
 4196e0b77f88ea01cd868c535befb52c2722454f,3D Facial similarity: Automatic assessment versus perceptual judgments,"D Facial Similarity: Automatic Assessment versus Perceptual
 Judgments
 Anush K. Moorthy, Anish Mittal, Sina Jahanbin, Kristen Grauman and Alan C. Bovik"
-41c1b8f319e27be0c77c3b33cf877c29b1676501,"Face Recognition based on Radon Transform , PCA , LDA using KNN and SVM","I.J. Computer Network and Information Security, 2014, 7, 36-43
-Published Online June 2014 in MECS (http://www.mecs-press.org/)
-DOI: 10.5815/ijcnis.2014.07.05
-D Face Recognition based on Radon Transform,
-PCA, LDA using KNN and SVM
-P. S. Hiremath and Manjunatha Hiremath
-Department of Computer Science, Gulbarga University, Gulbarga – 585106
-e-mail: and
-Karnataka, India"
 41308edf82ae645923efea2d6979d076b975ee25,Convolutional Scale Invariance for Semantic Segmentation,"Convolutional Scale Invariance
 for Semantic Segmentation
 Ivan Kre(cid:20)so, Denis (cid:20)Cau(cid:20)sevi(cid:19)c, Josip Krapac and Sini(cid:20)sa (cid:20)Segvi(cid:19)c
@@ -19910,9 +16965,6 @@ processing based on the structure of the face, the complementary Data-Driven Fac
 project is directed toward deriving models of facial movement (including non-speech gestures)
 directly from data.
 Discussion of Methodology Used"
-4188bd3ef976ea0dec24a2512b44d7673fd4ad26,Nonlinear Non-Negative Component Analysis Algorithms,"Nonlinear Non-Negative Component
-Analysis Algorithms
-Stefanos Zafeiriou, Member, IEEE, and Maria Petrou, Senior Member, IEEE"
 41690be86b39c55a26ea056261513ddd726d6601,Heterogeneous microarchitectures trump voltage scaling for low-power cores,"Heterogeneous Microarchitectures Trump Voltage Scaling
 for Low-Power Cores
 Andrew Lukefahr, Shruti Padmanabha, Reetuparna Das, Ronald Dreslinski Jr.,
@@ -20123,23 +17175,6 @@ Department of Computer Engineering, Faculty of Engineering,
 Prince of Songkla University, Hat Yai, Songkhla, 90112 Thailand
 Telephone: (66)080-7045015, (66)074-287-357
 E-mail:"
-84b451a5749837d28af5e96fd3349d852fefe4f2,A Robust Face Recognition Approach through Different Local Features,"[Yohanu, 4(9): September 2017]                                                                                        ISSN 2348 – 8034
-DOI- 10.5281/zenodo.888845                                                                                     Impact Factor- 4.022
-GLOBAL JOURNAL OF ENGINEERING SCIENCE AND RESEARCHES
-A ROBUST FACE RECOGNITION APPROACH THROUGH DIFFERENT LOCAL
-*1PG Student, ECE Department, Indira Institute of Technology & Sciences, Markapur, A.P, India,
-Assistant Professor, ECE Department Indira Institute of Technology & Sciences, Markapur, A.P, India
-FEATURES
-K.Yohanu*1 & M.Pradeep2"
-846f3857976ba437e0592a848e47f6a3370880a3,SERSC 3 D Face Recognition Based on Depth and Intensity Gabor Features using Symbolic PCA and AdaBoost,"International Journal of Signal Processing, Image Processing and Pattern Recognition
-Vol.6, No.5 (2013), pp.1-12
-http://dx.doi.org/10.14257/ijsip.2013.6.5.01
-D Face Recognition Based on Depth and Intensity Gabor
-Features using Symbolic PCA and AdaBoost
-P. S. Hiremath and Manjunatha Hiremath
-Department of Computer Science
-Gulbarga University, Gulbarga – 585106
-Karnataka, India,"
 8411fe1142935a86b819f065cd1f879f16e77401,Facial Recognition using Modified Local Binary Pattern and Random Forest,"International Journal of Artificial Intelligence & Applications (IJAIA), Vol. 4, No. 6, November 2013
 Facial Recognition using Modified Local Binary
 Pattern and Random Forest
@@ -20162,10 +17197,6 @@ weak supervision
 Steven Hickson, Anelia Angelova, Irfan Essa, Rahul Sukthankar
 Google Brain / Google Research
 (shickson, anelia, irfanessa,"
-841a5de1d71a0b51957d9be9d9bebed33fb5d9fa,PCANet: A Simple Deep Learning Baseline for Image Classification?,"PCANet: A Simple Deep Learning Baseline for
-Image Classiﬁcation?
-Tsung-Han Chan, Member, IEEE, Kui Jia, Shenghua Gao, Jiwen Lu, Senior Member, IEEE,
-Zinan Zeng, and Yi Ma, Fellow, IEEE"
 84187adc5e6412123405102bb3c2f0428713593c,Quad-Tree based Image Encoding Methods for Data-Adaptive Visual Feature Learning,"IPSJ SIG Technical Report
 Quad-Tree based Image Encoding Methods for
 Data-Adaptive Visual Feature Learning
@@ -20186,12 +17217,6 @@ CVC and DCC, UAB
 Germ´an Ros
 CVC and DCC, UAB
 December 30, 2016"
-84eb543a649f7331403caef6aaf96177c6cf5571,Automatic Rank Determination in Projective Nonnegative Matrix Factorization,"Automatic Rank Determination in Projective
-Nonnegative Matrix Factorization
-Zhirong Yang, Zhanxing Zhu, and Erkki Oja
-Department of Information and Computer Science(cid:2)
-Aalto University School of Science and Technology
-P.O.Box 15400, FI-00076, Aalto, Finland"
 84c35fc21db3bcd407a4ffb009912b6ac5a47e3c,MGAN: TRAINING GENERATIVE ADVERSARIAL NETS,"Under review as a conference paper at ICLR 2018
 MGAN: TRAINING GENERATIVE ADVERSARIAL NETS WITH
 MULTIPLE GENERATORS
@@ -20226,25 +17251,6 @@ into  multi-resolution  sub"
 84fa126cb19d569d2f0147bf6f9e26b54c9ad4f1,Improved Boosting Performance by Explicit Handling of Ambiguous Positive Examples,"Improved Boosting Performance by Explicit
 Handling of Ambiguous Positive Examples
 Miroslav Kobetski and Josephine Sullivan"
-8408f4b1193e8db25fec818a989d9fe3194d5ea6,Face Recognition using Radon Transform and Symbolic LDA,"International Journal of Computer Applications (0975 - 8887)
-Volume 67 - No. 4, April 2013
-D Face Recognition using Radon Transform and
-Symbolic LDA
-P. S. Hiremath
-Department of Computer Science
-Gulbarga University, Gulbarga-585106
-Karnataka, India
-Manjunatha Hiremath
-Department of Computer Science
-Gulbarga University, Gulbarga-585106
-Karnataka, India"
-84af83ff6412a756df58b6436f0d2e3c049e1f12,Abnormality Detection with Improved Histogram of Oriented Tracklets,"Abnormality Detection with Improved
-Histogram of Oriented Tracklets
-Hossein Mousavi1, Moin Nabi1 , Hamed Kiani Galoogahi1
-Alessandro Perina1 and Vittorio Murino1,2
-Pattern Analysis and Computer Vision Department (PAVIS)
-Istituto Italiano di Tecnologia (IIT) Genova, Italy
-Dipartimento di Informatica,University of Verona, Italy"
 84be05dd82a7208a6e7b3d238df27b123cc917ce,Revisiting Visual Question Answering Baselines,"Revisiting Visual Question Answering Baselines
 Allan Jabri, Armand Joulin, and Laurens van der Maaten
 Facebook AI Research"
@@ -20253,26 +17259,11 @@ Lei Zhang and Dimitris Samaras
 Department of Computer Science,
 SUNY at Stony Brook, NY, 11790
 {lzhang,"
-422fc05b3ef72e96c87b9aa4190efa7c7fb8c170,Preprocessing Technique for Face Recognition Applications under Varying Illumination Conditions By,"Global Journal of Computer Science and Technology
-Graphics & Vision
-Volume 12 Issue 11 Version 1.0 Year 2012
-Type: Double Blind Peer Reviewed International Research Journal
-Publisher: Global Journals Inc. (USA)
-Online ISSN: 0975-4172 & Print ISSN: 0975-4350
-Preprocessing  Technique  for  Face  Recognition  Applications
-under Varying Illumination Conditions
-By S.Anila & Dr.N.Devarajan
-Sri Ramakrishna Institute of Technology, Coimbatore-10, Tamil Nadu, India"
 42b56c77e4b154364763d4024baa8129da75151f,Deep Detection of People and their Mobility Aids for a Hospital Robot,"Deep Detection of People and their Mobility Aids for a Hospital Robot
 Andres Vasquez
 Marina Kollmitz
 Andreas Eitel
 Wolfram Burgard"
-423e0f595365640b653c1195749e01394cbcd937,Web-Scale Responsive Visual Search at Bing,"Web-Scale Responsive Visual Search at Bing
-Houdong Hu, Yan Wang, Linjun Yang, Pavel Komlev, Li Huang,
-Xi (Stephen) Chen, Jiapei Huang, Ye Wu, Meenaz Merchant, Arun Sacheti
-Microsoft
-Redmond, Washington"
 42f4653f0693f16e087e4b913407d9b0278154c9,3D Human Action Recognition with Siamese-LSTM Based Deep Metric Learning,"D Human Action Recognition with Siamese-
 LSTM Based Deep Metric Learning
 VisLab, Department of Computer Engineering, Gebze Technical University, Kocaeli, Turkey
@@ -20367,12 +17358,6 @@ Luis Patino*, Tom Cane**, Alain Vallee*** and James Ferryman*
 429b8d5bb05e1a580fad0222b9e9496985465e40,"See No Evil, Say No Evil: Description Generation from Densely Labeled Images","Proceedings of the Third Joint Conference on Lexical and Computational Semantics (*SEM 2014), pages 110–120,
 Dublin, Ireland, August 23-24 2014.
 (Count:3) Isa: ride, vehicle,… Doing: parking,… Has: steering wheel,… Attrib: black, shiny,… children (Count:2) Isa: kids, children … Doing: biking, riding … Has: pants, bike … Attrib: young, small … bike (Count:1) Isa: bike, bicycle,… Doing: playing,… Has: chain, pedal,… Attrib: silver, white,… women(Count:3) Isa: girls, models,… Doing: smiling,...  Has: shorts, bags,… Attrib: young, tan,… purses(Count:3) Isa: accessory,… Doing: containing,… Has: body, straps,… Attrib: black, soft,… sidewalk(Count:1) Isa: sidewalk, street,… Doing: laying,… Has: stone, cracks,… Attrib: flat, wide,… woman(Count:1) Isa: person, female,… Doing: pointing,… Has: nose, legs,… Attrib: tall, skinny,… tree(Count:1) Isa: plant,… Doing: growing,… Has: branches,… Attrib: tall, green,… kids(Count:5) Isa: group, teens,… Doing: walking,… Has: shoes, bags,… Attrib: young,… Fiveyoungpeopleonthestreet,twosharingabicycle.Severalyoungpeoplearewalkingnearparkedvehicles.Threegirlswithlargehandbagswalkingdownthesidewalk.Threewomenwalkdownacitystreet,asseenfromabove.Threeyoungwomanwalkingdownasidewalklookingup.Figure1:Anannotatedimagewithhumangeneratedsen-tencedescriptions.Eachboundingpolygonencompassesoneormoreobjectsandisassociatedwithacountandtextla-bels.Thisimagehas9highlevelobjectsannotatedwithover250textuallabels.tomuchofthevisualcontentneededtogeneratecomplete,human-likesentences.Inthispaper,weinsteadstudygenerationwithmorecompletevisualsupport,asprovidedbyhu-manannotations,allowingustodevelopmorecomprehensivemodelsthanpreviouslyconsid-ered.Suchmodelshavethedualbeneﬁtof(1)providingnewinsightsintohowtoconstructmorehuman-likesentencesand(2)allowingustoper-formexperimentsthatsystematicallystudythecontributionofdifferentvisualcuesingeneration,suggestingwhichautomaticdetectorswouldbemostbeneﬁcialforgeneration.Inanefforttoapproximaterelativelycompletevisualrecognition,wecollectedmanuallylabeledrepresentationsofobjects,parts,attributesandac-tivitiesforabenchmarkcaptiongenerationdatasetthatincludesimagespairedwithhumanauthored"
-4244d3340304b114e5c00e7b5797d2338a5c2b82,Face Recognition Using Local Texture Feature,"International Journal of Computer Engineering and Applications,
-Volume XII, Issue I, Jan. 18, www.ijcea.com ISSN 2321-3469
-FACE RECOGNITION USING LOCAL TEXTURE FEATURE
-Pavan.M 1, Sayed Aftab Ahamed 2
-Dept. of Information Science & engineering, J.N.N.C.E
-Shimoga, Karnataka, India"
 4263630a35c5ee34ccf9dbd81c0541d92d0c7d5b,Shape Variation-Based Frieze Pattern for Robust Gait Recognition,"Shape Variation-Based Frieze Pattern for Robust Gait Recognition
 Seungkyu Lee*                    Yanxi Liu*                     Robert Collins
 Dept. of Computer Science and Eng. *Dept. of Electrical Eng.
@@ -20393,12 +17378,6 @@ Sciences, Vanderbilt University Medical Center, and 3Department of Psychology an
 Vanderbilt University, Nashville, TN 37203, USA
 Correspondence should be addressed to Alexandra P. Key, Vanderbilt Kennedy Center, Peabody Box 74, Vanderbilt University, Nashville, TN 37203, USA.
 E-mail:"
-42e3dac0df30d754c7c7dab9e1bb94990034a90d,PANDA: Pose Aligned Networks for Deep Attribute Modeling,"PANDA: Pose Aligned Networks for Deep Attribute Modeling
-Ning Zhang1,2, Manohar Paluri1, Marc’Aurelio Ranzato1, Trevor Darrell2, Lubomir Bourdev1
-EECS, UC Berkeley
-{mano, ranzato,
-Facebook AI Research
-{nzhang,"
 421b3a33ec70af2d733310f6c83ad713a314951d,Using nasal curves matching for expression robust 3D nose recognition,"Emambakhsh, M., Evans, A. and Smith, M. (2013) Using nasal curves
 matching for expression robust 3D nose recognition. In: IEEE Con-
 ference on Biometrics: Theory, Applications and Systems (BTAS2013),
@@ -20453,10 +17432,6 @@ October 17, 2012"
 422d352a7d26fef692a3cd24466bfb5b4526efea,Pedestrian interaction in tracking : the social force model and global optimization methods,"Pedestrian interaction in tracking: the social
 force model and global optimization methods
 Laura Leal-Taix´e and Bodo Rosenhahn"
-42350e28d11e33641775bef4c7b41a2c3437e4fd,Multilinear Discriminant Analysis for Face Recognition,"Multilinear Discriminant Analysis
-for Face Recognition
-Shuicheng Yan, Member, IEEE, Dong Xu, Qiang Yang, Senior Member, IEEE, Lei Zhang, Member, IEEE,
-Xiaoou Tang, Senior Member, IEEE, and Hong-Jiang Zhang, Fellow, IEEE"
 42d8a6b1ef5acaaf4640a8974c6f99d60b56090c,Markerless Motion Capture of Multiple Characters Using Multiview Image Segmentation,"SUBMIT TO IEEE TRANS. PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. XX, NO. XX, AUGUST 2012
 Markerless Motion Capture of Multiple Characters
 Using Multi-view Image Segmentation
@@ -20668,16 +17643,6 @@ extracted from a face are decomposed in a sparse manner onto this dictionary. We
 that play a crucial role in the final identification rates. Applied to various databases and modalities, we show that this approach"
 fab0d19c58815eccb0db7215fe45d6a32066ca1c,Inferring Human Attention by Learning Latent Intentions,"Proceedings of the Twenty-Sixth International Joint Conference on Artiﬁcial Intelligence (IJCAI-17)
 the mug's statuschecking the book's statuslocating the dispenserFigure1:Humanattentionandintentionsina3Dscene.thedispenser,hisattentionsweepsfromthetabletothedis-penser;whilefetchingwaterfromthedispenser,hisintentionistocheckifthemugisfullandhisattentionsteadilyfocusesonthemug.Thedrivingrulesofintentionsactingonattentioncanbeindependentofactivitycategories.Forexample,inFigure1,theattentiondrivenbytheintentioncheckingstatusalwayspresentsassteadilyfocusing,evenindifferentactivities.Thisphenomenonmakesitpossibletoinfertheattentionwiththesamerulesacrossdifferentactivities.However,thesedrivingrulesarehiddenandshouldbelearnedfromdata.Thispaperproposesaprobabilisticmethodtoinfer3Dhu-manattentionbyjointlymodelingattention,intentions,andtheirinteractions.Theattentionandintentionarerepresent-edwithfeaturesextractedfromhumanskeletonsandscenevoxels.Humanintentionsaretakenaslatentvariableswhichguidethemotionsandformsofhumanattention.Conversely,thehumanattentionrevealstheintentionfeatures.Attentioninferenceismodeledasajointoptimizationwithlatenthu-manintentions.WeadoptanEM-based[Bishop,2006]approachtolearnthemodelparametersandminethelatentintentions.Giv-enanRGB-DvideowithhumanskeletonscapturedbytheKinectcamera,ajoint-statedynamicprogrammingalgorithm"
-fa24a04f1e8095d47e2d2ce0076bf47bdd6f997a,Wavelet Based Face Recognition for Low Quality Images,"International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering
-Vol. 2, Issue 1, January  2013
-Wavelet Based Face Recognition for Low
-ISSN: 2278 – 8875
-Quality Images
-M.Karthika, 2K.Shanmugapriya, 3Dr.S.Valarmathy,  4M.Arunkumar
-PG Scholar, Department of ECE, Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu,India
-PG Scholar, Department of ECE, Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu,India
-Professor and Head, Department of ECE, Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu, India
-Assistant Professor, Department of ECE, Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu, India"
 fa08a4da5f2fa39632d90ce3a2e1688d147ece61,Supplementary material for “ Unsupervised Creation of Parameterized Avatars ” 1 Summary of Notations,"Supplementary material for
 “Unsupervised Creation of Parameterized Avatars”
 Summary of Notations
@@ -20763,26 +17728,7 @@ Rui Guo2
 UC San Diego
 Toyota InfoTechnology Center
 {yum107, yol070, amraj, ssunarjo, tjavidi,"
-fa356a677a4258408f6d3901ef7b450ad1ad9edf,A Review of Numerous Facial Recognition Techniques in Image Processing,"A.Swaminathan et al, International Journal of Computer Science and Mobile Computing, Vol.3 Issue.1, January- 2014, pg. 233-243
-Available Online at www.ijcsmc.com
-International Journal of Computer Science and Mobile Computing
-A Monthly Journal of Computer Science and Information Technology
-ISSN 2320–088X
-IJCSMC, Vol. 3, Issue. 1, January 2014, pg.233 – 243
-REVIEW ARTICLE
-A Review of Numerous Facial Recognition
-Techniques in Image Processing
-A.Swaminathan1, N.Kumar2, M.Ramesh Kumar3
-M.E Student, 2,3Asst Professor,
-, 2, 3 Department of Computer Science & Engineering,
-, 2, 3 Veltech Multitech Dr.Rangarajan Dr.Sakunthala Engineering College, Chennai, India
-, 2, 3"
 fabbc7f921d77b5aa9157310df29ad81367fe92d,Efficient Image and Video Representations for Retrieval,
-fa83597bf71dbeb606bca6593bcef8ecd51e8661,MULTIPLE TARGET TRACKING USING COST MINIMIZATION TECHNIQUES,"MICHAEL KAMARAJ AND G. BALAKRISHNAN: MULTIPLE TARGET TRACKING USING COST MINIMIZATION TECHNIQUES
-MULTIPLE TARGET TRACKING USING COST MINIMIZATION TECHNIQUES
-Department of Computer Applications, Pavendar Bharathidasan College of Engineering and Technology, India
-Department of Computer Science and Engineering, Indra Ganesan College of Engineering, India
-Michael Kamaraj1 and G. Balakrishnan2"
 fad895771260048f58d12158a4d4d6d0623f4158,Audio-visual emotion recognition for natural human-robot interaction,"Audio-Visual Emotion
 Recognition For Natural
 Human-Robot Interaction
@@ -20848,15 +17794,6 @@ Universitat Aut`onoma de Barcelona, Spain"
 fa2603efaf717974c77162c93d800defae61a129,Face recognition/detection by probabilistic decision-based neural network,"Face Recognition/Detection by Probabilistic
 Decision-Based Neural Network
 Shang-Hung Lin, Sun-Yuan Kung, Fellow, IEEE, and Long-Ji Lin"
-fa8c73899c22b461cc062a10b6df20fccb18800c,A Novel Framework for Face Recognition in Real-Time Environments Tmt .,"International Journal of Scientific and Research Publications, Volume 3, Issue 8, August 2013
-ISSN 2250-3153
-A Novel Framework for Face Recognition in Real-Time
-Environments
-Tmt.Maithili Easwaran*, Dr.B.Poorna**
-*Department of Computer Applications, S.A.Engineering College, TN, INDIA
-** Department of Computer applications, Shankarlal Sundarbai Shasun Jain College for Women, TN, INDIA
-i.e.,
-(PCA)-based"
 faca1c97ac2df9d972c0766a296efcf101aaf969,Sympathy for the Details: Dense Trajectories and Hybrid Classification Architectures for Action Recognition,"Sympathy for the Details: Dense Trajectories and Hybrid
 Classification Architectures for Action Recognition
 C´esar Roberto de Souza1,2, Adrien Gaidon1, Eleonora Vig3, Antonio Manuel L´opez2
@@ -20908,12 +17845,6 @@ Department of Electrical and Electronics Engineering, M.E.T.U.
 Graduate School of Informatics, M.E.T.U.
 {hakan.sevimli, ersin.esen, tugrul.ates, ezgican.ozan, mashar.tekin, berker.logoglu,
 muge.sevinc,"
-fa1b849697115ceede0a08ac552ea25ce2bf33a1,A N APPROACH TO F ACE R ECOGNITION OF 2-D IMAGES USING E IGEN F ACES AND PCA,"Signal & Image Processing : An International Journal (SIPIJ) Vol.3, No.2, April 2012
-AN APPROACH TO FACE RECOGNITION OF 2-D
-IMAGES USING EIGEN FACES AND PCA
-Annapurna Mishra1, Monorama Swain2 and Bodhisattva Dash3
-Department of Electronics & Telecommunication Engineering
-Silicon Institute of Technology, Bhubaneswar, India"
 faa111d749eb228c686643e4667dd1bc21c724f2,Condensed from Video Sequences for Place Recognition,"Boosting Descriptors Condensed from Video Sequences for Place Recognition
 Tat-Jun Chin, Hanlin Goh and Joo-Hwee Lim
 Institute for Infocomm Research
@@ -20947,17 +17878,6 @@ GIT Vision Lab∗, Department of Computer Engineering, Gebze Institute of Techno
 Keywords:
 Age Estimation, Age Classiﬁcation, Geometric Features, LBP, Gabor, LGBP, Cross Ratio, FGNET, MORPH."
 fa4ff855ca125b986bcb2bc6b71bef2ae8fde1cf,"3d Integral Invariant Signatures and Their Application on Face Recognition Dedication I Am Grateful for the Support and Guidance I Have Received from Dr. Irina A. Kogan, and I Also Express My Gratitude To",
-fab60b3db164327be8588bce6ce5e45d5b882db6,Maximum A Posteriori Estimation of Distances Between Deep Features in Still-to-Video Face Recognition,"Maximum A Posteriori Estimation of Distances
-Between Deep Features in Still-to-Video Face
-Recognition
-Andrey V. Savchenko
-National Research University Higher School of Economics
-Laboratory of Algorithms and Technologies for Network Analysis,
-6 Rodionova St., Nizhny Novgorod, Russia
-Natalya S. Belova
-National Research University Higher School of Economics
-0 Myasnitskaya St., Moscow, Russia
-September 2, 2018"
 fa4544e5dce135c3d0517304ec9e620c78267891,LIDAR-based driving path generation using fully convolutional neural networks,"LIDAR-based Driving Path Generation
 Using Fully Convolutional Neural Networks
 Luca Caltagirone∗, Mauro Bellone, Lennart Svensson, Mattias Wahde"
@@ -21026,10 +17946,6 @@ UPMC – Sorbonne Universit´es, Paris, France
 Joo-Hwee Lim†
 Institute for Infocomm Research
 A*STAR, Singapore"
-6742c0a26315d7354ab6b1fa62a5fffaea06da14,What does 2 D geometric information really tell us about 3 D face shape ?,"BAS AND SMITH: WHAT DOES 2D GEOMETRIC INFORMATION REALLY TELL US ABOUT 3D FACE SHAPE?
-What does 2D geometric information
-really tell us about 3D face shape?
-Anil Bas and William A. P. Smith, Member, IEEE"
 6740f4918d594094f5eca3c0c65006c9c6d6c1d4,Class Room Attendance System Using Facial Recognition System,"The International Journal of Mathematics, Science, Technology and Management
 (ISSN : 2319-8125) Vol. 2 Issue 3
 Class Room Attendance System Using Facial
@@ -21049,29 +17965,6 @@ Guilhem Chéron∗ 1 2
 Jean-Baptiste Alayrac∗ 1
 Ivan Laptev1
 Cordelia Schmid2"
-679136c2844eeddca34e98e483aca1ff6ef5e902,Scene-Specific Pedestrian Detection Based on Parallel Vision,"Scene-Speciﬁc Pedestrian Detection Based on
-Parallel Vision
-Wenwen Zhang, Kunfeng Wang, Member, IEEE, Hua Qu, Jihong Zhao, and Fei-Yue Wang, Fellow, IEEE"
-6775c818b26263c885b0ce85c224dfd942c9652e,PEDESTRIAN AND OBJECT DETECTION USING LEARNED CONVOLUTIONAL FILTERS,"U.P.B. Sci. Bull., Series C, Vol. 77, Iss. 2, 2015
-ISSN 2286-3540
-PEDESTRIAN AND OBJECT DETECTION USING LEARNED
-CONVOLUTIONAL FILTERS
-Anamaria R ˘ADOI1 , Dan Alexandru STOICHESCU2
-Object detection is still a very active ﬁeld in Computer Vision. Until now, part
-ased models proved to be one of the most interesting and successful approaches
-in object and pedestrian detection. The method applies a machine learning ap-
-proach not to the input images themselves, but to histograms of gradients. How-
-ever, its performances are still limited when compared to what humans can do.
-The purpose of the present paper is to show that sparse representations can be
-successfully used in object detection. The main advantage of using this method is
-related to the possibility of learning only those ﬁlters that are able to express the
-most frequent patterns that appear in the analyzed images. The experiments are
-arried out on two widely used datasets, namely VOC2007 and INRIA Person.
-Keywords: learned ﬁlterbanks, stochastic gradient descent, pedestrian detection,
-object detection, Histogram of Oriented Gradients.
-. Introduction
-Object detection is a major challenge for many areas of research, starting
-from medicine and going to applications such as street surveillance or video appli-"
 67126ad0af544740c455311d08cb180aec830a6c,Generating Descriptions of Spatial Relations between Objects in Images,"Proceedings of the 15th European Workshop on Natural Language Generation (ENLG), pages 100–104,
 Brighton, September 2015. c(cid:13)2015 Association for Computational Linguistics"
 67484723e0c2cbeb936b2e863710385bdc7d5368,Anchor Cascade for Efficient Face Detection,"Anchor Cascade for Efﬁcient Face Detection
@@ -21111,21 +18004,6 @@ Susanna Ricco∗
 Rahul Sukthankar∗
 Cordelia Schmid† ∗
 Jitendra Malik‡ ∗"
-676c76c4e3ac2f91a2209ecdae8d20be4de7c9c0,Performance of Gabor mean Feature Extraction Techniques for Ear Biometrics Recognition System,"International Journal of Computer Applications (0975 – 8887)
-Volume 168 – No.12, June 2017
-Performance of Gabor mean Feature Extraction
-Techniques for Ear Biometrics Recognition System
-Bhanu Vadhwani
-Rajasthan College of Engg.
-for Women, India
-Vineet Khanna
-JaipuRajasthan College of
-Engg. for Women
-Shubhlakshmi Agarwal
-The ICFAI University, Jaipur, India
-Sandeep Kumar Gupta
-Machine Learning Research
-Lab, Jaipur, India"
 679aded003bce19aa7821295117693b9a5b4f0ef,Fluid Annotation: A Human-Machine Collaboration Interface for Full Image Annotation,"Fluid Annotation: A Human-Machine Collaboration Interface
 for Full Image Annotation
 Mykhaylo Andriluka∗
@@ -21159,19 +18037,6 @@ Anguelos Nicolaou∗, Andrew D. Bagdanov∗, Marcus Liwicki†, and Dimosthenis
 Computer Vision Center, Ediﬁci O, Universitad Autonoma de Barcelona,Bellaterra, Spain
 DIVA research group, Department of Informatics, University of Fribourg, Switzerland
 Email:"
-6789bddbabf234f31df992a3356b36a47451efc7,Unsupervised Generation of Free-Form and Parameterized Avatars.,"Unsupervised Generation of Free-Form and
-Parameterized Avatars
-Adam Polyak, Yaniv Taigman, and Lior Wolf, Member, IEEE"
-67e488d4d31d65a31d4bc2a3337c587720af2a12,Cross-Class Sample Synthesis for Zero-shot Learning,"LIU, LI, YANG: CROSS-CLASS SAMPLE SYNTHESIS FOR ZERO-SHOT LEARNING
-Cross-Class Sample Synthesis
-for Zero-shot Learning
-Jinlu Liu
-Xirong Li
-Gang Yang*
-School of Information
-Renmin University of China
-Beijing, China
-*Corresponding author"
 67bee729d046662c6ebd9d3d695823c9d820343a,Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus,"Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, pages 588–598,
 Berlin, Germany, August 7-12, 2016. c(cid:13)2016 Association for Computational Linguistics"
 674fcadf1b895e3a79380d3ac5afb43d406fd31a,Facial Asymmetry Assessment from 3D Shape Sequences: The Clinical Case of Facial Paralysis,
@@ -21258,9 +18123,6 @@ of hip motion) under three attack scenarios, we revealed that a minimal effort m
 hances of impostors. However, impostors who know their closest person in the database or the genders of the users can be a
 threat to gait-based authentication. We also provide some new insights toward the uniqueness of gait in case of foot motion. In
 particular, we revealed the following: a sideway motion of the foot provides the most discrimination, compared to an up-down or"
-67fd4f209aa6e8359fc86bdc12c62bbdb0529077,Scalable Nearest Neighbor Algorithms for High Dimensional Data,"Scalable Nearest Neighbor Algorithms
-for High Dimensional Data
-Marius Muja, Member, IEEE and David G. Lowe, Member, IEEE"
 67a56dd94906a5460c263e1a1b87fa3a52c4b453,FACE ANALYSIS BY LOCAL DIRECTIONAL NUMBER PATTERN,"International Journal of Engineering Research and General Science Volume 3, Issue 1,  January-February, 2015
 ISSN 2091-2730
 FACE ANALYSIS BY LOCAL DIRECTIONAL NUMBER PATTERN
@@ -21278,18 +18140,6 @@ Nenad Markuˇs*, Miroslav Frljak*, Igor S. Pandˇzi´c*, J¨orgen Ahlberg†, an
 * University of Zagreb, Faculty of Electrical Engineering and Computing, Unska 3, 10000 Zagreb, Croatia
 Link¨oping University, Department of Electrical Engineering, SE-581 83 Link¨oping, Sweden
 March 28, 2014"
-eb044760b6502431da6b6f3d5ad11aaab851a1ff,Video Storytelling,"A SUBMISSION TO IEEE TRANSACTIONS ON MULTIMEDIA
-Video Storytelling
-Junnan Li, Yongkang Wong, Member, IEEE, Qi Zhao, Member, IEEE, Mohan S. Kankanhalli, Fellow, IEEE"
-ebb7cc67df6d90f1c88817b20e7a3baad5dc29b9,Fast algorithms for Higher-order Singular Value Decomposition from incomplete data,"Journal of Computational Mathematics
-Vol.xx, No.x, 200x, 1–25.
-http://www.global-sci.org/jcm
-doi:??
-Fast algorithms for Higher-order Singular Value Decomposition
-from incomplete data*
-Department of Mathematics, University of Alabama, Tuscaloosa, AL
-Yangyang Xu
-Email:"
 eb33adf3f8eb5c07b58a1433734ab1fee5d77c93,"Singleton, C. J., Ashwin, C. and Brosnan, M. (2014) Physiological Responses to Social and Nonsocial Stimuli in Neurotypical Adults With High and Low Levels of Autistic Traits:Implications for Understanding Nonsocial Drive in Autism Spectrum","Singleton, C. J., Ashwin, C. and Brosnan, M. (2014) Physiological
 Responses to Social and Nonsocial Stimuli in Neurotypical
 Adults With High and Low Levels of Autistic Traits:Implications
@@ -21332,46 +18182,12 @@ t the University of Central Florida
 Orlando, Florida
 Spring Term
 Major Professor: Mubarak Shah"
-ebe95ea3d1568c70ae49e19428be1cb401fb3df2,Multi-feature Fusion Face Recognition Based on Kernel Discriminate Local Preserve Projection Algorithm under Smart Environment,"Multi-feature Fusion Face Recognition Based on
-Kernel Discriminate Local Preserve Projection
-Algorithm under Smart Environment
-.College of Electrical and Information Engineering, Lanzhou University of  Technology, Lanzhou,China
-.Key Laboratory of Gansu Advanced Control for Industrial Processes,Lanzhou,China
-.Manufacturing Engineering Technology Research Center of Gansu,Lanzhou,China
-Di Wu1,2,3
-Email:
-Jie Cao1,2,3,4 , Jinhua Wang1,2,3,,Wei Li2,3,4
-4.  College of Computer and Communication, Lanzhou University  of  Technology, Lanzhou ,China
-Email:
-local
-kernel
-discriminate"
 eb0e0a40372db32d30ceaefad046b213fac977f4,SCENE UNDERSTANDING USING BACK PROPAGATION BY NEURAL NETWORK,"Scene Understanding Using Back Propagation by Neural Network
 SCENE UNDERSTANDING USING BACK PROPAGATION BY
 NEURAL NETWORK
 ARTI TIWARI1 & JAGVIR VERMA2
 ,2Department of Elex & Telecomm. Engg.Chouksey Engg. College,Bilaspur
 intelligent  human-computer"
-eb6243b1c9506f9450dab2a09db9c17fc2c2d364,D Face Recognition system Based on Texture Gabor Features using PCA and Support Vector Machine as a Classifier,"ISSN(Online): 2319-8753
-ISSN (Print):   2347-6710
-International Journal of Innovative Research in Science,
-Engineering and Technology
-(An ISO 3297: 2007 Certified Organization)
-Vol. 5, Issue 8, August 2016
-D Face Recognition system Based on Texture
-Gabor Features using PCA and Support
-Vector Machine as a Classifier
-Rajesh Yadav 1, Dr. Chandra kumarJha 2
-Assistant Professor, Department of Computer Science, Gurgaon Institute of Technology &Management, Gurgaon,
-Haryana, India1
-Associate Professor, Department of Computer Science &Engineering, AIM & ACT, Banasthali University, Jaipur,
-Rajasthan, India2"
-ebabd1f7bc0274fec88a3dabaf115d3e226f198f,Driver Drowsiness Detection System Based on Feature Representation Learning Using Various Deep Networks,"Driver drowsiness detection system based on feature
-representation learning using various deep networks
-Sanghyuk Park, Fei Pan, Sunghun Kang and Chang D. Yoo
-School of Electrical Engineering, KAIST,
-Guseong-dong, Yuseong-gu, Dajeon, Rep. of Korea
-{shine0624, feipan, sunghun.kang, cd"
 eb526174fa071345ff7b1fad1fad240cd943a6d7,Deeply vulnerable: a study of the robustness of face recognition to presentation attacks,"Deeply Vulnerable – A Study of the Robustness of Face Recognition to
 Presentation Attacks
 Amir Mohammadi, Sushil Bhattacharjee, and S´ebastien Marcel ∗†"
@@ -21419,11 +18235,6 @@ Wushan Road, Tianhe District, Guangzhou 510640, China; (J.S.); (J.Y.)
 * Correspondence:
 Academic Editor: Willy Susilo
 Received: 6 February 2017; Accepted: 5 April 2017; Published: 11 April 2017"
-ebd36259defde84deb0d4c09695b54befe538ac8,Robust Generalized Low Rank Approximations of Matrices,"RESEARCH ARTICLE
-Robust Generalized Low Rank
-Approximations of Matrices
-Jiarong Shi*, Wei Yang, Xiuyun Zheng
-School of Science, Xi'an University of Architecture and Technology, Xi'an, China"
 ebf204e0a3e137b6c24e271b0d55fa49a6c52b41,Visual Tracking Using Deep Motion Features,"Master of Science Thesis in Electrical Engineering
 Department of Electrical Engineering, Linköping University, 2016
 Visual Tracking Using
@@ -21432,26 +18243,6 @@ Susanna Gladh"
 eb4edbec8cb122de07951e3cf54c33fc30dd1c19,Examining the Effects of Supervision for Transfer from Synthetic to Real Driving Domains Vashisht Madhavan,"Examining the Effects of Supervision for Transfer from Synthetic to Real
 Driving Domains
 Vashisht Madhavan"
-eb7e40aab49fdda492bb8aac02f520013931144b,Restricted Nearest Feature Line with Ellipse for Face Recognition,"Journal of Information Hiding and Multimedia Signal Processing
-Ubiquitous International
-⃝2012 ISSN 2073-4212
-Volume 3, Number 3, July 2012
-Restricted Nearest Feature Line with Ellipse for Face
-Recognition
-Qingxiang Feng1, Jeng-Shyang Pan2;∗
-, and Lijun Yan3
-Department of Computer Science and Technology
-Harbin Institute of Technology Shenzhen Graduate School
-Shenzhen, China
-Department of Computer Science and Technology
-Harbin Institute of Technology Shenzhen Graduate School
-Corresponding Author
-Shenzhen, China
-(cid:3)
-Department of Computer Science and Technology
-Harbin Institute of Technology Shenzhen Graduate School
-Shenzhen, China
-Received January 2012; revised June 2012"
 eb3f47ed113752eaa4c989bb92aa0e3e4e0bf339,Tracking of dolphins in a basin using a constrained motion model,"Tracking of Dolphins in a Basin Using a
 Constrained Motion Model
 Clas Veibäck, Gustaf Hendeby and Fredrik Gustafsson
@@ -21517,12 +18308,6 @@ in Web of Science™ Core Collection (BKCI)
 Interested in publishing with us?
 Contact
 Numbers displayed above are based on latest data collected."
-529e2ce6fb362bfce02d6d9a9e5de635bde81191,Normalization of Face Illumination Based on Large-and Small-Scale Features,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication.
-> TIP-05732-2009<
-Normalization of Face Illumination Based
-on Large- and Small- Scale Features
-Xiaohua Xie, Wei-Shi Zheng, Member, IEEE, Jianhuang Lai*, Member, IEEE
-Pong C. Yuen, Member, IEEE, Ching Y. Suen, IEEE Fellow"
 520e4b21302b99e5f289075541f9fe4959a639a4,Framewise approach in multimodal emotion recognition in OMG challenge,"Framewise approach in multimodal emotion
 recognition in OMG challenge
 Grigoriy Sterling1, 2, Andrey Belyaev1, 3, and Maxim Ryabov1
@@ -21555,30 +18340,9 @@ Ayeni Olaniyi Abiodun 1, Alese Boniface Kayode1, Dada Olabisi Matemilayo2
 . Department of computer science, Kwara state polytechnic Ilorin, Kwara-State, Nigeria.
 . *Corresponding author:  Ayeni Olaniyi Abiodun  Mail Id:
 Received:    September 22, 2015, Accepted: December 14, 2015, Published: December 14, 2015."
-523abe29cc278f9daf03fe74d1e09d9e2711b73e,Facial Recognition System : A Review,"Debolina S. De, International Journal of Computer Science and Mobile Computing, Vol.4 Issue.10, October- 2015, pg. 7-11
-Available Online at www.ijcsmc.com
-International Journal of Computer Science and Mobile Computing
-A Monthly Journal of Computer Science and Information Technology
-ISSN 2320–088X
-IJCSMC, Vol. 4, Issue. 10, October 2015, pg.7 – 11
-REVIEW ARTICLE
-Facial Recognition System: A Review
-Debolina S. De
-Computer Engineering Department, Mukesh Patel School of Technology Management and Engineering, India"
 5265be9c7b8b22f4e06a01736bbedf171caee74e,Covariance of Motion and Appearance Featuresfor Spatio Temporal Recognition Tasks,"Covariance of Motion and Appearance Features
 for Human Action and Gesture Recognition
 Subhabrata Bhattacharya, Nasim Souly and Mubarak Shah"
-526ce11a6c80716fca69bdc111f32dfbe045e400,A Survey on Dataset Recognition of 3 D Face with Missing Parts,"International Journal of Science and Research (IJSR)
-ISSN (Online): 2319-7064
-Index Copernicus Value (2013): 6.14 | Impact Factor (2014): 5.611
-A Survey on Dataset Recognition of 3D Face with
-Missing Parts
-Madhura Patil
-ME Student, Department of Computer Engineering, Sinhgad Academy of Engg. Pune, Maharashtra, India
-possibly
-recognition.3D
-recognization
-methodology"
 5223f3485b96bffe7dd4b3aa71e63fd2b049fcf0,Is the Pedestrian going to Cross? Answering by 2D Pose Estimation,"Is the Pedestrian going to Cross? Answering by 2D Pose Estimation
 Zhijie Fang and Antonio M. L´opez"
 5251cb5349e37495b3ca29b06e6ed7422f12d126,A Pedestrian Detector Using Histograms of Oriented Gradients and a Support Vector Machine Classifier,"Proceedings of the 2007 IEEE
@@ -21682,22 +18446,6 @@ broad, or from public or private research centers.
 L’archive ouverte pluridisciplinaire HAL, est
 destin´ee au d´epˆot et `a la diffusion de documents
 scientiﬁques de niveau recherche, publi´es ou non,"
-52d9ad99874f6b76184ad9abe45e824a6568617b,Large-Scale Active Learning with Approximations of Expected Model Output Changes,"C. K¨ading, A. Freytag, E. Rodner, A. Perino, J. Denzler
-Large-scale Active Learning with Approximations of Expected Model Output Changes GCPR 2016
-(cid:13) Copyright by Springer. The ﬁnal publication will be available at link.springer.com
-Large-scale Active Learning with Approximations of
-Expected Model Output Changes
-Christoph K¨ading1,2, Alexander Freytag1,2, Erik Rodner1,2, Andrea Perino3,4, and
-Joachim Denzler1,2,3
-Computer Vision Group, Friedrich Schiller University Jena, Germany
-Michael Stifel Center Jena, Germany
-German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Germany
-Institute of Biology, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany"
-5239001571bc64de3e61be0be8985860f08d7e7e,Deep Appearance Models: A Deep Boltzmann Machine Approach for Face Modeling,"SUBMITTED TO IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, JUNE 2016
-Deep Appearance Models: A Deep Boltzmann
-Machine Approach for Face Modeling
-Chi Nhan Duong, Student, IEEE, Khoa Luu, Member, IEEE,
-Kha Gia Quach, Student, IEEE, Tien D. Bui, Senior Member, IEEE"
 52cd3eb77a5e259289d2442205f1731eafd581f9,Human Detection Based on the Generation of a Background Image and Fuzzy System by Using a Thermal Camera,"Article
 Human Detection Based on the Generation of
 Background Image and Fuzzy System by Using
@@ -21744,18 +18492,6 @@ J. Fierrez-Aguilar, J. Ortega-Garcia, D. Garcia-Romero and J. Gonzalez-Rodriguez
 www.atvs.diac.upm.es
 Universidad Politecnica de Madrid, Spain
 Biometrics Research Lab., ATVS"
-52144c6d20ddea70e59514c2aa9ec7dc801e5c5e,An Investigation of Face Recognition Characteristics Using PCA and ICA,"Yundi Fu et al, International Journal of Computer Science and Mobile Computing, Vol.3 Issue.2, February- 2014, pg. 110-123
-Available Online at www.ijcsmc.com
-International Journal of Computer Science and Mobile Computing
-A Monthly Journal of Computer Science and Information Technology
-ISSN 2320–088X
-IJCSMC, Vol. 3, Issue. 2, February 2014, pg.110 – 123
-RESEARCH ARTICLE
-An Investigation of Face Recognition
-Characteristics Using PCA and ICA
-Yundi Fu1, Yongli Cao1, Arun Kumar Sangaiah2
-Department of Software Engineering, University of Electronic Science and Technology, China
-School of Computing Science and Engineering, VIT University, Vellore, India"
 5232a1ab263e4feaa4989b8b257830650403dfa5,On Finding Differences Between Faces,"On Finding Differences Between Faces
 Manuele Bicego1, Enrico Grosso1, and Massimo Tistarelli2
 DEIR - University of Sassari, via Sardegna 58 - 07100 Sassari - Italy
@@ -21775,13 +18511,6 @@ Yi Yang1, Heng Tao Shen1, Zhigang Ma2, Zi Huang1, Xiaofang Zhou1
 School of Information Technology & Electrical Engineering, The University of Queensland.
 Department of Information Engineering & Computer Science, University of Trento.
 yangyi {huang,"
-527cc8cd2af06a9ac2e5cded806bab5c3faad9cf,Abnormal Event Detection in Videos Using Spatiotemporal Autoencoder,"Abnormal Event Detection in Videos
-using Spatiotemporal Autoencoder
-Yong Shean Chong
-Yong Haur Tay
-Lee Kong Chian Faculty of Engineering Science,
-Universiti Tunku Abdul Rahman, 43000 Kajang, Malaysia.
-January 9, 2017"
 52a723061175ad141d73cb3979788e8afb7291db,Canonical Correlation Analysis of Datasets With a Common Source Graph,"Canonical Correlation Analysis of Datasets
 with a Common Source Graph
 Jia Chen, Gang Wang, Student Member, IEEE,
@@ -21797,11 +18526,6 @@ Lisa Brown
 IBM Watson
 Sharath Pankanti
 IBM Watson"
-bdbf414a2059d542f501ad9b1d21eacc9831082b,Two-Layer Mixture Network Ensemble for Apparel Attributes Classification,"Two-Layer Mixture Network Ensemble for Apparel
-Attributes Classification
-Tianqi Han, Zhihui Fu, and Hongyu Li*
-AI Lab, ZhongAn Information Technology Service Co., Ltd.
-Shanghai, China"
 bd96c3af9c433b4eaf95c8a28f072e1b0fc2de1a,A Study on Facial Expression Recognition Model using an Adaptive Learning Capability,"We are IntechOpen,
 the world’s leading publisher of
 Open Access books
@@ -21844,19 +18568,6 @@ Anupam Garg
 Assistant Professor
 BGIET, Sangrur
 Punjab (India)"
-bdf64dd341925ea7b9b3abbb49cab3cf978f8e21,PROBABLE ETIOPATHOGENESIS ( SAMPRAPTI ) OF AUTISM IN FRAME OF AYURVEDA IN RELATION TO INTENSE WORLD THEORY,"Global J Res. Med. Plants & Indigen. Med. | Volume 2, Issue 6 | June 2013 | 448–459
-ISSN 2277-4289 | www.gjrmi.com | International, Peer reviewed, Open access, Monthly Online Journal
-Review article
-PROBABLE ETIOPATHOGENESIS (SAMPRAPTI) OF AUTISM IN FRAME
-OF AYURVEDA IN RELATION TO INTENSE WORLD THEORY
-Yadav Deepmala1*, Behera Banshidhar2, Kumar Abhimanyu3
-Asst.Professor, Dept. of Kaumarbhritya, M.S.M. Institute of Ayurveda, Khanpur kalan, Haryana-131305,
-India
-Lecturer, Dept. of Dravyaguna, Gaur Brahman Ayurvedic College, Rohtak, Haryana – 124001, India
-Director, All India Institute of Ayurveda, Gautampuri, Mathura road, Sarita Vihar, New Delhi-110076,
-India
-*Corresponding Author: E-mail: Mob +919414893921, +919414458895
-Received: 10/05/2013; Revised: 26/05/2013; Accepted: 30/05/2013"
 bd76a71c6b1f414ada026ba82726024fbd58e9fe,DEEPSTEREOBRUSH : INTERACTIVE DEPTH MAP CREATION,"DEEPSTEREOBRUSH: INTERACTIVE DEPTH MAP CREATION
 Sebastian Knorr1,3,∗, Matis Hudon1,∗, Julian Cabrera2,∗, Thomas Sikora3, Aljosa Smolic1 †
 Trinity College Dublin, 2Universidad Polit´ecnica de Madrid, 3Technische Universit¨at Berlin"
@@ -21980,9 +18691,6 @@ Yutaka Matsuo5, Helmut Prendinger6
 Technical University of Munich, Munich, 2KTH Royal Institute of Technology, Stockholm,
 Polytechnic University of Catalonia, Barcelona, 4National Taiwan University, Taipei, 5University of
 Tokyo, Tokyo, 6National Institute of Informatics, Tokyo"
-a577eefb31ba63baa087f321537b0be2784ec013,Security Event Recognition for Visual Surveillance,"Security Event Recognition for Visual Surveillance
-Michael Ying Yang∗, Senior Member, IEEE, Wentong Liao, Chun Yang, Yanpeng Cao, Member, IEEE and Bodo
-Rosenhahn Member, IEEE"
 a56c1331750bf3ac33ee07004e083310a1e63ddc,Efficient Point-to-Subspace Query in ℓ1 with Application to Robust Object Instance Recognition,"Vol. xx, pp. x
 (cid:13) xxxx Society for Industrial and Applied Mathematics
 Ef‌f‌icient Point-to-Subspace Query in (cid:96)1 with Application to Robust Object
@@ -22016,9 +18724,6 @@ Bahria  University
 Islamabad,  Pakistan"
 a5006c29b0609296b5c1368ff1113eeb12b119ad,In-flight launch of unmanned aerial vehicles,"In-flight launch of unmanned aerial vehicles
 Niels Nauwynck, Haris Balta, Geert De Cubber, and Hichem Sahli"
-a5c63f38e2e6ca7fff48fc5cd1dbdb8f6362c99f,A Neural Approach to Blind Motion Deblurring,"A Neural Approach to Blind Motion Deblurring
-Ayan Chakrabarti
-Toyota Technological Institute at Chicago"
 a588d38ec81c0337b445931eadf6f443aea13380,Functional Map of the World,"Functional Map of the World
 Gordon Christie1
 Neil Fendley1
@@ -22135,16 +18840,6 @@ Physics Department, CFSL,
 Sec-36, Chandigarh - 160036
 to:  (a)
 potential  method"
-a5fcb663bffdd39523964e3e958566f4dfbfae90,Günther Palm Towards Robust Speech Acquisition using Sensor Arrays,"Abteilung Neuroinformatik
-Universit¨at Ulm
-Prof. Dr. G¨unther Palm
-Towards Robust Speech Acquisition
-using Sensor Arrays
-Dissertation zur Erlangung des Doktorgrades
-Dr.rer.nat. der Fakult¨at f¨ur Ingenieurwissenschaften und Informatik der Universit¨at Ulm
-Hari Krishna Maganti
-us Hyderabad, India
-UNIVERSITÄ(cid:13)TULM·(cid:13)SCIENDO·(cid:13)DOCENDO·(cid:13)CURANDO·(cid:13)"
 a546fd229f99d7fe3cf634234e04bae920a2ec33,Fast Fight Detection,"RESEARCH ARTICLE
 Fast Fight Detection
 Ismael Serrano Gracia1*, Oscar Deniz Suarez1*, Gloria Bueno Garcia1*, Tae-Kyun Kim2
@@ -22170,8 +18865,6 @@ Visual Behavior in Public Speaking
 Rahul Sharma, Tanaya Guha and Gaurav Sharma
 IIT Kanpur
 {rahus, tanaya,"
-a52d6c456122007f10c90989a1e81dc8e1c599da,Query-Adaptive Image Search With Hash Codes,"Query-Adaptive Image Search with Hash Codes
-Yu-Gang Jiang, Jun Wang, Member, IEEE, Xiangyang Xue, Member, IEEE, Shih-Fu Chang, Fellow, IEEE"
 a59e338fec32adee012e31cdb0513ec20d6c8232,Phase Retrieval Under a Generative Prior,"Phase Retrieval Under a Generative Prior
 Paul Hand∗, Oscar Leong∗, and Vladislav Voroninski†
 July 12, 2018"
@@ -22182,39 +18875,11 @@ JIRI STASTNY*, VLADISLAV SKORPIL**
 Brno University of Technology,
 Purkynova 118,  612 00 Brno,
 CZECH  REPUBLIC,"
-e0dedb6fc4d370f4399bf7d67e234dc44deb4333,Material : MultiTask Video Captioning with Video and Entailment Generation,"Supplementary Material: Multi-Task Video Captioning with Video and
-Entailment Generation
-Ramakanth Pasunuru and Mohit Bansal
-UNC Chapel Hill
-{ram,
-Experimental Setup
-.1 Datasets
-.1.1 Video Captioning Datasets
-YouTube2Text or MSVD The Microsoft Re-
-search Video Description Corpus (MSVD) or
-YouTube2Text (Chen and Dolan, 2011) is used
-for our primary video captioning experiments. It
-has 1970 YouTube videos in the wild with many
-diverse captions in multiple languages for each
-video. Caption annotations to these videos are
-ollected using Amazon Mechanical Turk (AMT).
-All our experiments use only English captions. On
-verage, each video has 40 captions, and the over-
-ll dataset has about 80, 000 unique video-caption
-pairs. The average clip duration is roughly 10 sec-"
 e0181f7596b475f7c7d31fd1eccad8e9b7379180,Facial Expression Recognition for Traumatic Brain Injured Patients,
 e076f818b090e42036821c69727cfa3b7da49373,Social Groups Detection in Crowd through Shape-Augmented Structured Learning,"Social Groups Detection in Crowd Through
 Shape-Augmented Structured Learning
 Francesco Solera and Simone Calderara
 DIEF University of Modena and Reggio Emilia, Italy"
-e0e8c7145c9b389dad2f4e1982f2b9c31b766503,Augmenting Crowd-Sourced 3 D Reconstructions using Semantic Detections,"Augmenting Crowd-Sourced 3D Reconstructions using Semantic Detections
-True Price1
-Department of Computer Science, UNC Chapel Hill
-Johannes L. Sch¨onberger2
-Zhen Wei1 Marc Pollefeys2
-Department of Computer Science, ETH Z¨urich
-Jan-Michael Frahm1
-Microsoft"
 e000dd1aec1c7b1e9e781ec7ea66f2bde72faa5e,Ear Recognition : A Complete System,"Ear Recognition: A Complete System
 Ayman Abazaa,b and MaryAnn F. Harrisona
 West Virginia High Tech Foundation, 1000 Technology Drive, Fairmont, USA;
@@ -22300,13 +18965,6 @@ Marcin Mo˙zejko, Mateusz Susik & Rafał Karczewski
 Sigmoidal"
 e0ad3408ed47261a9d0fbc2f037b395fb41b88bf,MOTION VECTOR FIELD ESTIMATION USING BRIGHTNESS CONSTANCY ASSUMPTION AND EPIPOLAR GEOMETRY CONSTRAINT,"ISPRS Technical Commission I Symposium, Sustaining Land Imaging: UAVs to Satellites
 7 – 20 November 2014, Denver, Colorado, USA, MTSTC1-109"
-e054291cbf250592d032722b99c414c2e4741c03,A Fast Fixed-Point Algorithm for Two-Class Discriminative Feature Extraction,"A Fast Fixed-Point Algorithm for Two-Class
-Discriminative Feature Extraction
-Zhirong Yang and Jorma Laaksonen
-Laboratory of Computer and Information Science ⋆
-Helsinki University of Technology
-P.O. Box 5400, FI-02015 HUT, Espoo, Finland
-{zhirong.yang,"
 e0e511a5d58a8d090ad169be4fcfdbeaef097a70,Leveraging Cognitive Computing for Gender and Emotion Detection,"Leveraging Cognitive Computing for Gender and
 Emotion Detection
 Andrea Corriga1, Simone Cusimano1, Francesca M. Malloci1, Lodovica
@@ -22414,11 +19072,6 @@ Erica Gessaroli1,2, Erica Santelli3, Giuseppe di Pellegrino1,4*, Francesca Frass
 Department of Psychology, University of Bologna, Bologna, Italy, 2 Fondazione Salvatore Maugeri, Clinica del Lavoro e della Riabilitazione, Istituto di Ricovero
 e  Cura  a  Carattere  Scientifico,  Mantova,  Castel  Goffredo,  Italy,  3  Centro  Autismo,  Reggio  Emilia,  Italy,  4  Center  for  Studies  and  Research  in  Cognitive
 Neuroscience, Cesena, Italy"
-e0d2a28bdcb1996f9659ce2d5fcdace3d369cff6,Fusion Scheme for Semantic and Instance-level Segmentation,"Fusion Scheme for Semantic and Instance-level Segmentation
-Arthur Daniel Costea ∗, Andra Petrovai ∗ and Sergiu Nedevschi
-Image Processing and Pattern Recognition Research Center
-Technical University of Cluj-Napoca, Romania
-{arthur.costea, andra.petrovai,"
 6898b0934d2bc34acc61a3c63fbb20337d7b9a95,Learning Styles and Emotion Recognition in a Fuzzy Expert System,"Learning Styles and Emotion Recognition in a Fuzzy
 Expert System
 Ramón Zatarain-Cabada, M. Lucía Barrón-Estrada, Rosalío Zatarain-Cabada
@@ -22429,15 +19082,6 @@ Instituto Tecnológico de Culiacán, Juan de Dios Bátiz s/n, Col. Guadalupe, Cu
 nd Dominance Underlie Perceptions of Criminality?
 Heather D. Flowe*
 College of Medicine, Biological Sciences and Psychology, University of Leicester, Leicester, United Kingdom"
-68a2ee5c5b76b6feeb3170aaff09b1566ec2cdf5,AGE CLASSIFICATION BASED ON SIMPLE LBP TRANSITIONS,"AGE CLASSIFICATION BASED ON
-SIMPLE LBP TRANSITIONS
-Research Scholar & Assoc Professor, Aditya institute of Technology and Management, Tekkalli-532 201, A.P.,
-Gorti Satyanarayana Murty
-India,
-Dr. V.Vijaya Kumar
-A. Obulesu
-Dean-Computer Sciences (CSE & IT), Anurag Group of Institutions, Hyderabad – 500088, A.P., India.,
-3Asst. Professor, Dept. Of CSE, Anurag Group of Institutions, Hyderabad – 500088, A.P., India."
 683260bf133c282439b91ac4427d42d73a5988b5,"Optimizing Program Performance via Similarity, Using Feature-aware and Feature-agnostic Characterization Approaches","UNIVERSITY OF CALIFORNIA,
 IRVINE
 Optimizing Program Performance via Similarity,
@@ -22605,44 +19249,6 @@ Danielle Bons & Egon van den Broek & Floor Scheepers &
 Pierre Herpers & Nanda Rommelse & Jan K. Buitelaaar
 Published online: 25 October 2012
 # Springer Science+Business Media New York 2012"
-6826ae2e1598be376f5b64f302172bebc57b64cb,Foreground Object Segmentation with Objectness Measure,"Foreground Object Segmentation with Objectness
-Measure
-Junguang Zhu1
-National Digital Switching System Engineering & Technological Research Center
-Zhengzhou, 450002,China
-E-mail:
-lixin Ji2
-National Digital Switching System Engineering & Technological Research Center
-Zhengzhou, 450002, China
-E-mail:
-hengqiu xiao3
-Troop 75753, People's Liberation Army
-Guangzhou, 510600, China
-E-mail:
-This   paper   proposes   a   novel   model   to   address   the   problem   of   image   segmentation   with
-objectness measure. Recently, many objectness measures are proposed, which aims to generate
-andidate windows to localize the possible objects in the image. Consider to combine this useful
-object location piror into a foreground segment model. Specifically, a Conditional Random Filed
-model is constructed on superpixels graph, and it efficiently incorporates objectness measure,
-olor distribution and appearance similarity. Expermental results on a extended GrabCut dataset"
-680402e42c874c14a32146865d985588985744a4,DETECTION AND TRACKING OF MULTIPLE HUMANS IN HIGH-DENSITY CROWDS,"DETECTION AND TRACKING OF MULTIPLE HUMANS IN
-HIGH-DENSITY CROWDS
-Irshad Ali
-A research study submitted in partial fulﬁllment of the requirements for the
-degree of Master of Engineering in
-Computer Science
-Examination Committee: Dr. Matthew N. Dailey (Chairperson)
-Dr. Manukid Parnichkun (Member)
-Dr. Nitin V. Afzulpurkar (Member)
-Nationality: Pakistani
-Previous Degree: Bachelor of Science in Computer Engineering
-Samara State Technical University, Russia
-Scholarship Donor: Higher Education Commission (HEC), Pakistan - AIT
-Fellowship
-Asian Institute of Technology
-School of Engineering and Technology
-Thailand
-May 2009"
 68df1f746a3434ee8bcc8918d46809ddaad38b12,Subspace learning in minimax detection,"014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP)
 978-1-4799-2893-4/14/$31.00 ©2014 IEEE
 Email: {raja.fazliza, david.mary,
@@ -22653,18 +19259,6 @@ Laboratoire J.-L. Lagrange, UMR7293,
 . INTRODUCTION AND PRIOR WORKS
 (cid:26) H0"
 68caf5d8ef325d7ea669f3fb76eac58e0170fff0,Long-term face tracking in the wild using deep learning,
-68003e92a41d12647806d477dd7d20e4dcde1354,Chapter-4 FUZZY BASED IMAGE DIMENSIONALITY REDUCTION USING SHAPE PRIMITIVES FOR EFFICIENT FACE RECOGNITION,"ISSN: 0976-9102 (ONLINE)
-DOI: 10.21917/ijivp.2013.0101
-ICTACT JOURNAL ON IMAGE AND VIDEO PROCESSING, NOVEMBER 2013, VOLUME: 04, ISSUE: 02
-FUZZY BASED IMAGE DIMENSIONALITY REDUCTION USING SHAPE
-PRIMITIVES FOR EFFICIENT FACE RECOGNITION
-P. Chandra Sekhar Reddy1, B. Eswara Reddy2 and V. Vijaya Kumar3
-Deprtment of Computer Science and Engineering, Nalla Narasimha Reddy Education Society’s Group of Institutions, India
-E-Mail:
-Deprtment of Computer Science and Engineering, JNTUA College of Engineering, India
-Deprtment of Computer Science and Engineering, Anurag Group of Institutions, India
-E-mail:
-E-mail:"
 68d4056765c27fbcac233794857b7f5b8a6a82bf,Example-Based Face Shape Recovery Using the Zenith Angle of the Surface Normal,"Example-Based Face Shape Recovery Using the
 Zenith Angle of the Surface Normal
 Mario Castel´an1, Ana J. Almaz´an-Delf´ın2, Marco I. Ram´ırez-Sosa-Mor´an3,
@@ -22673,25 +19267,6 @@ CINVESTAV Campus Saltillo, Ramos Arizpe 25900, Coahuila, M´exico
 Universidad Veracruzana, Facultad de F´ısica e Inteligencia Artiﬁcial, Xalapa 91000,
 ITESM, Campus Saltillo, Saltillo 25270, Coahuila, M´exico
 Veracruz, M´exico"
-684f5166d8147b59d9e0938d627beff8c9d208dd,Discriminative Block-Diagonal Representation Learning for Image Recognition,"IEEE TRANS. NNLS, JUNE 2017
-Discriminative Block-Diagonal Representation
-Learning for Image Recognition
-Zheng Zhang, Yong Xu, Senior Member, IEEE, Ling Shao, Senior Member, IEEE, Jian Yang, Member, IEEE"
-68415682aa3e25178c9504866f64cf4b2a32273e,Capturing Complex 3D Human Motions with Kernelized Low-Rank Representation from Monocular RGB Camera,"Article
-Capturing Complex 3D Human Motions with
-Kernelized Low-Rank Representation from
-Monocular RGB Camera
-Xuan Wang 1,2,3,4, Fei Wang 1,2,3,4,* and Yanan Chen 1,2,3,4
-The Institute of Artiﬁcial Intelligence and Robotics, Xi’an Jiaotong University, No.28 Xianning West Road,
-Xi’an 710048, China; (X.W.); (Y.C.)
-The School of Software Engineering, Xi’an Jiaotong University, No.28 Xianning West Road,
-Xi’an 710048, China
-National Engineering Laboratory for Visual Information Processing and Application, Xi’an Jiaotong
-University, No.28 Xianning West Road, Xi’an 710048, China
-Shaanxi Digital Technology and Intelligent System Key Laboratory, Xi’an Jiaotong University, No.28
-Xianning West Road, Xi’an 710048, China
-* Correspondence:
-Received: 5 July 2017; Accepted: 24 August 2017; Published: 3 September 2017"
 683fbd7593cf5c22ef54004bb89c469eab2f656e,URJC&UNED at ImageCLEF 2013 Photo Annotation Task,"URJCyUNED at ImageCLEF 2012 Photo
 Annotation task⋆
 Jes´us S´anchez-Oro1, Soto Montalvo1, Antonio S. Montemayor1, Ra´ul Cabido1,
@@ -22886,21 +19461,10 @@ Multi-Speaker Spontaneous Conversations – EVA Corpus
 IZIDOR MLAKAR, ZDRAVKO KAČIČ, MATEJ ROJC
 Faculty of Electrical Engineering and Computer Science, University of Maribor
 SLOVENIA"
-c95ad088c9d96c7e94428b7e90ea8bf547cd9e42,Human Identification using Face and Voice Recognition,", 2 Department of Electronics & Telecommunication Engineering, Sant Gadge Baba Amravati University, Amravati,
-Ishwar S. Jadhav, 2V. T. Gaikwad, 3Gajanan U. Patil
-Department of Electronics & Communication Engineering, North Maharashtra University, Jalgaon,
-Recognition
-Maharashtra, India
-Maharashtra, India
-Human Identification using Face and Voice"
 c93996cb126589b30c04bf1256c97a4431c0e8b6,Robustness Analysis of Pedestrian Detectors for Surveillance,"Robustness Analysis of Pedestrian Detectors
 for Surveillance
 Yuming Fang, Senior Memmber, IEEE, Guanqun Ding, Yuan Yuan, Weisi Lin, Fellow, IEEE,
 nd Haiwen Liu, Senior Memmber, IEEE"
-c97cd49536fcec5b50962eaf4658a973cd85bba0,Semantic Segmentation of 3D LiDAR Data in Dynamic Scene Using Semi-supervised Learning,"Semantic Segmentation of 3D LiDAR Data in
-Dynamic Scene Using Semi-supervised Learning
-Jilin Mei, Member, IEEE, Biao Gao, Member, IEEE, Donghao Xu, Member, IEEE, Wen Yao, Member, IEEE,
-Xijun Zhao, Member, IEEE, and Huijing Zhao, Member, IEEE,"
 c924137ca87e8b4e1557465405744f8b639b16fc,Seeding Deep Learning using Wireless Localization,"ADDRESSING TRAINING BIAS VIA AUTOMATED IMAGE ANNOTATION
 Zhujun Xiao 1 Yanzi Zhu 2 Yuxin Chen 1 Ben Y. Zhao 1 Junchen Jiang 1 Haitao Zheng 1"
 c91103e6612fa7e664ccbc3ed1b0b5deac865b02,Automatic facial expression recognition using statistical-like moments,"Automatic facial expression recognition using
@@ -22933,16 +19497,6 @@ Copenhagen, Denmark, September 7–11, 2017. c(cid:13)2017 Association for Compu
 c90b109301244e59771fec431a8d50a78e395956,Alternative face models for 3 D face registration,"Alternative face models for 3D face registration
 Albert Ali Salah, Ne¸se Aly¨uz, Lale Akarun
 Bo˘gazi¸ci University, 34342 Bebek, ˙Istanbul, Turkey"
-c9f3a5fe33782dd486cb32d9667fba0514711f04,Face and Expression Recognition Using Local Directional Number Pattern,"International Journal of Science and Research (IJSR)
-ISSN (Online): 2319-7064
-Impact Factor (2012): 3.358
-Face and Expression Recognition Using Local
-Directional Number Pattern
-Gopu Prasoona1, Dasu Vaman Ravi Prasad2
-Computer Science, CVSR College of Engineering, Venkatapur, RR dist, India
-Computer Science and Engineering, CVSR College of Engineering, Venkatapur, RR dist, India
-refers
-to digital"
 c9bbf31afbec278ca735e91cf5e9c70dd3aa41a4,Enhancing 3D Face Recognition By Mimics Segmentation,"Enhancing 3D Face Recognition By Mimics Segmentation
 Boulbaba Ben Amor, Mohsen Ardabilian, and Liming Chen
 MI Department, LIRIS Laboratory, CNRS 5205
@@ -23110,11 +19664,6 @@ lished or not. The documents may come from
 teaching and research institutions in France or
 broad, or from public or private research centers.
 L’archive ouverte pluridisciplinaire HAL, est"
-e8b2a98f87b7b2593b4a046464c1ec63bfd13b51,CMS-RCNN: Contextual Multi-Scale Region-based CNN for Unconstrained Face Detection,"CMS-RCNN: Contextual Multi-Scale
-Region-based CNN for Unconstrained Face
-Detection
-Chenchen Zhu*, Student, IEEE, Yutong Zheng*, Student, IEEE,
-Khoa Luu, Member, IEEE, Marios Savvides, Senior Member, IEEE"
 e819a577c57c83a133a0a0e81180d14dc13b82e9,Pyramid Histogram of Oriented Gradients based Human Ear Identification,"Pyramid Histogram of Oriented Gradients based Human Ear Identification
 Pyramid Histogram of Oriented Gradients based Human
 Ear Identification
@@ -23128,26 +19677,6 @@ Gaithersburg, Md. 20899-8940
 Elaine M. Newton
 01 N. Craig St., Suite 102
 Pittsburgh, Pa. 15213"
-e8ff87c9072d67dcbcd5491b1e5a0cecc2ee309d,A Survey on Gaze Estimation Techniques in Smartphone,"International Research Journal of Engineering and Technology (IRJET)      e-ISSN: 2395 -0056
-Volume: 04 Issue: 04 | Apr -2017                     www.irjet.net                                                                p-ISSN: 2395-0072
-A Survey on Gaze Estimation Techniques in Smartphone
-Akshay A Gawande1, Prof.Gangotri Nathaney2
-M.Tech Scholar, CSE Department, WCOEM, Nagpur, India1
-Assistant Professor, CSE Department, WCOEM, Nagpur, India2
-image  dataset
-interest.  Many  of
-field  mobile  technology  and  digital
-The  goal  of  this  system  to  get  correct  gaze  point  with
-minimum  of  error  rate  and  allow  handicap  people  to
-operate  mobile  easily  by  eyes  .The  proposed  system
-onsist  of  collecting  some  steps  as:  Collecting  people
-different  position  eye
-,preprocessing,
-feature  extraction,  regression.  This  paper  is  organized  as
-follows:  Section  2  comprises  Previous  Work;  section  3
-omprises Methodology and Conclusion is in section 4.
----------------------------------------------------------------------***---------------------------------------------------------------------
-use  eye  trackers  to  identify  what  customer's  gaze  is"
 e8acbe49ecf7e0a77f4f5874674ac40b1e35bf8a,EXPERIMENTAL EVALUATION OF TEXT-INDEPENDENT SPEAKER VERIFICATION ON LABORATORY AND FIELD TEST DATABASES IN THE M2VTS PROJECT,"EXPERIMENTAL EVALUATION OF TEXT-INDEPENDENT
 SPEAKER VERIFICATION ON LABORATORY AND FIELD
 TEST DATABASES IN THE M2VTS PROJECT
@@ -23195,14 +19724,6 @@ nd J.J. Villanueva
 Signal Theory and Communications Department, University of Vigo, Spain
 Centre de Visio per Computador, Universitat Autonoma de Barcelona, Spain
 Digital Pointer MVT"
-e85b6f50b14014ee4a9212de4716031e21e92a89,Multiple Sensor Fusion for Moving Object Detection and Tracking,"International Research Journal of Engineering and Technology (IRJET)      e-ISSN: 2395-0056
-Volume: 04 Issue: 07 | July -2017                     www.irjet.net                                                                p-ISSN: 2395-0072
-Multiple Sensor Fusion  for Moving Object Detection and Tracking
-Khan Rabiya Yunus1, Prof : M. A. Mechkul2
-,2 Dept. Of Electronics and Telecommunication, SNJB’s COE, Chandwad, Maharashtra, India
-type  of  sensors  can
-improve
----------------------------------------------------------------------***--------------------------------------------------------------------"
 e8867f819f39c1838bba7d446934258035d4101c,Face recognition performance with superresolution.,"Face recognition performance with superresolution
 Shuowen Hu,1,* Robert Maschal,1 S. Susan Young,1 Tsai Hong Hong,2
 nd P. Jonathon Phillips2
@@ -23223,18 +19744,6 @@ perimental setup consistent with real world settings at multiple subject-to-came
 that superresolution image reconstruction improves face recognition performance considerably at the
 examined midrange and close range.
 OCIS codes:"
-e8d1d2a61c5a259440ef9fcd301093b43e87efa1,Periocular Biometrics in the Visible Spectrum,"Periocular Biometrics in the Visible Spectrum
-Unsang Park, Member, IEEE, Raghavender Reddy Jillela, Student Member, IEEE, Arun Ross, Senior Member, IEEE,
-nd Anil K. Jain, Fellow, IEEE"
-e8d2d991dcfb12b287ab06d282a86802e565780c,Inducing Behavior Change in Children with Autism Spectrum Disorders by Monitoring their Attention,"Inducing behavior change in children with autism spectrum disorders by
-monitoring their attention
-Margarida Lucas da Silva12, Hugo Silva3 and Daniel Gonc¸alves12
-Instituto Superior T´ecnico, Av. Rovisco Pais, 1, 1049-001, Lisboa, Portugal
-INESC-ID, R. Alves Redol, 9, 1000-029 Lisboa, Portugal
-Instituto de Telecomunicac¸ ˜oes, Instituto Superior T´ecnico, Av. Rovisco Pais, 1, Torre Norte - Piso 10, 1049-001, Lisboa,
-Portugal
-Keywords:
-Human Behavior Analysis, Autism Spectrum Disorders, Inducing Behavior Change."
 e8ffef3d4d74720e766e506e175e533bdc8ee705,Object Detection Networks on Convolutional Feature Maps,"Object Detection Networks on
 Convolutional Feature Maps
 Shaoqing Ren, Kaiming He, Ross Girshick, Xiangyu Zhang, and Jian Sun"
@@ -23244,20 +19753,6 @@ Face Recognition using Neural Network
 nd Eigenvalues with Distinct Block
 Processing
 Prashant Sharma, Amil Aneja, Amit Kumar, Dr.Shishir Kumar"
-e8baf6ddd2e651350b843fedfe58f761848d3524,Design And Implementation Of Multiposes Face Recognization System Ms .,"Pritika V.Mamankar et al, International Journal of Computer Science and Mobile Computing, Vol.4 Issue.4, April- 2015, pg. 387-394
-Available Online at www.ijcsmc.com
-International Journal of Computer Science and Mobile Computing
-A Monthly Journal of Computer Science and Information Technology
-IJCSMC, Vol. 4, Issue. 4, April 2015, pg.387 – 394
-RESEARCH ARTICLE
-ISSN 2320–088X
-Design And Implementation Of Multiposes Face
-Recognization System
-Ms. Pritika V.Mamankar
-Master of Engineering Scholar, Information Technology Department, Sipna College of Engg. and Technology, Amravati, India
-Assistant Professor of CSE Department, Computer Science and Engineering Department, Sipna College of Engg. and
-Prof. H R. Vyawahare
-Technology, Amravati, India"
 e80635b9b48df5ad263c51ecec62d7d4bd7327fd,"Playful Robot for Research , Therapy , and Entertainment","Int J Soc Robot (2009) 1: 3–18
 DOI 10.1007/s12369-008-0009-8
 O R I G I N A L PA P E R
@@ -23267,17 +19762,6 @@ Hideki Kozima · Marek P. Michalowski ·
 Cocoro Nakagawa
 Accepted: 28 October 2008 / Published online: 19 November 2008
 © Springer 2008"
-e849b9b3e65130712e23afb872ac925e1e9a6b73,"Image denoising with multi-layer perceptrons, part 1: comparison with existing algorithms and with bounds","Journal of Machine Learning Research x (2012) xxx
-Submitted xx/xx; Published xx/xx
-Image denoising with multi-layer perceptrons, part 1:
-omparison with existing algorithms and with bounds
-Harold Christopher Burger
-Christian J. Schuler
-Stefan Harmeling
-Max Planck Institute for Intelligent Systems
-Spemannstr. 38
-72076 T¨ubingen, Germany
-Editor:"
 e81705e6100759b75eb71839ea61abc257b0b6a9,Enhanced Spatial Pyramid Matching Using Log-Polar-Based Image Subdivision and Representation,"Enhanced Spatial Pyramid Matching Using Log-Polar-Based Image Subdivision
 nd Representation
 Edmond Zhang, Michael Mayo
@@ -23356,14 +19840,6 @@ lines and curves in pictures,” Commun. ACM, vol. 15, no. 1, pp. 11–15,
 Jan. 1972.
 [12] F. O’Gorman and M. B. Clowes, “Finding picture edges through collinear-
 ity of feature points,” IEEE Trans. Comput., vol. C-25, no. 4, pp. 449–454,"
-e819d8ec94ff9b07f81bcfcf6eb66301aa271805,OPTIMISED BLURRED OBJECT TRACKING USING ANFIS,"VOL. 11, NO. 13, JULY 2016                                                                                                                   ISSN 1819-6608
-ARPN Journal of Engineering and Applied Sciences
-©2006-2016 Asian Research Publishing Network (ARPN). All rights reserved.
-www.arpnjournals.com
-OPTIMISED BLURRED OBJECT TRACKING USING ANFIS
-Department of Electronics and Communication, Sathyabama University, Chennai, India
-S. Rajaprabha and M. Sugadev
-E-Mail:"
 e8e8f40ceff8b71d5dafa6b680d40690dfae940c,title : Guidelines for studying developmental prosopagnosia in adults and children,"Article	type:		Focus	Article
 Article	title:	Guidelines	for	studying	developmental	prosopagnosia	in	adults
 nd	children
@@ -23387,14 +19863,6 @@ Hartwig Adam
 George Papandreou
 Jonathon Shlens
 Google Inc."
-e8d1b134d48eb0928bc999923a4e092537e106f6,Weighted Multi-region Convolutional Neural Network for Action Recognition with Low-latency Online Prediction,"WEIGHTED MULTI-REGION CONVOLUTIONAL NEURAL NETWORK FOR ACTION
-RECOGNITION WITH LOW-LATENCY ONLINE PREDICTION
-Yunfeng Wang(cid:63), Wengang Zhou(cid:63), Qilin Zhang†, Xiaotian Zhu(cid:63), Houqiang Li(cid:63)
-(cid:63)University of Science and Technology of China, Hefei, Anhui, China
-HERE Technologies, Chicago, Illinois, USA"
-e8e8d8a619eea66c41a1a2bdc0a921a3b6d74836,"Restoring Degraded Face Images: A Case Study in Matching Faxed, Printed, and Scanned Photos","Restoring Degraded Face Images: A Case Study in
-Matching Faxed, Printed, and Scanned Photos
-Thirimachos Bourlai, Member, IEEE, Arun Ross, Senior Member, IEEE, and Anil K. Jain, Fellow, IEEE"
 2a7b7de7488211471a001044a3a249a117af488a,Physical Attribute Prediction Using Deep Residual Neural Networks,"Physical Attribute Prediction Using Deep Residual
 Neural Networks
 st Rashidedin Jahandideh
@@ -23415,10 +19883,6 @@ Jun-Yang Huang1 Shih-Chung Hsu1and Chung-Lin Huang1,2
 .  Department Of Electrical Engineering, National Tsing-Hua University, Hsin-Chu, Taiwan
 .  Department of Applied Informatics and Multimedia, Asia Univeristy, Tai-Chung, Taiwan.
 Email:"
-2ad0ee93d029e790ebb50574f403a09854b65b7e,Acquiring linear subspaces for face recognition under variable lighting,"Acquiring Linear Subspaces for Face
-Recognition under Variable Lighting
-Kuang-Chih Lee, Student Member, IEEE, Jeffrey Ho, Member, IEEE, and
-David Kriegman, Senior Member, IEEE"
 2ad2af8e3bdeb0302de07defc3fec9b387414a27,Don ' t Look Back : Post-hoc Category Detection via Sparse Reconstruction,"Don't Look Back: Post-hoc Category Detection via
 Sparse Reconstruction
 Hyun Oh Song
@@ -23445,26 +19909,6 @@ Interaction and Language (ViGIL), December 2017."
 Anonymous Author 1
 Anonymous Author 2
 Anonymous Author 3"
-2a6327a8bdbd31e2c08863b96c4f09245db8cab7,Targets ' facial width-to-height ratio biases pain judgments ☆,"Journal of Experimental Social Psychology 74 (2018) 56–64
-Contents lists available at ScienceDirect
-Journal of Experimental Social Psychology
-journal homepage: www.elsevier.com/locate/jesp
-Targets' facial width-to-height ratio biases pain judgments☆
-Jason C. Deska⁎, Kurt Hugenberg
-Miami University, 501 East High Street, Oxford, OH 45056, United States
-A R T I C L E I N F O
-A B S T R A C T
-Keywords:
-Facial width-to-height ratio
-Pain judgments
-Pain perception
-The accurate perception of others' pain is important for both perceivers and targets. Yet, like other person
-perception judgments, pain judgments are prone to biases. Although past work has begun detailing character-
-istics of targets that can bias pain judgments (e.g., race, gender), the current work examines a novel source of
-ias inherent to all targets: structural characteristics of the human face. Speciﬁcally, we present four studies
-demonstrating that facial width-to-height ratio, a stable feature of all faces, biases pain judgments. Compared to
-those with low facial width-to-height ratio, individuals with high facial width-to-height ratio are perceived as
-experiencing less pain in otherwise identical situations (Studies 1, 2, & 3), and as needing less pain medication to"
 2a6c7d5aa087233ff8a09bdaa34d5f76f3330a4f,A Survey of Efficient Regression of General-Activity Human Poses from Depth Images,"A Survey of Efﬁcient Regression of General-Activity Hu-
 man Poses from Depth Images
 Wenye He
@@ -23493,9 +19937,6 @@ Samira Ebrahimi Kahou1, Christopher Pal1, Xavier Bouthillier2, Pierre Froumenty1
 Laboratoire d’Informatique des Systèmes Adaptatifs, Université de Montréal, Montréal, Canada
 {samira.ebrahimi-kahou, christopher.pal,
 {bouthilx, gulcehrc, memisevr, vincentp, courvila,"
-2a3227f54286d8a36736663781f194167f2b6582,Nonlinear Dimensionality Reduction for Discriminative Analytics of Multiple Datasets,"Nonlinear Dimensionality Reduction for
-Discriminative Analytics of Multiple Datasets
-Jia Chen, Gang Wang, Member, IEEE, and Georgios B. Giannakis, Fellow, IEEE"
 2a218c17944d72bfdc7f078f0337cab67536e501,Detection bank: an object detection based video representation for multimedia event recognition,"Detection Bank: An Object Detection Based Video
 Representation for Multimedia Event Recognition
 Tim Althoff, Hyun Oh Song, Trevor Darrell
@@ -23560,26 +20001,6 @@ Facial Scans
 Maxim Bazik1 and Daniel Crispell2"
 2a067874fc1ec318b6d23f34bdb13ea4e95d5ca6,An Evaluation of Image-Based Verb Prediction Models against Human Eye-Tracking Data,"New Orleans, Louisiana, June 1 - 6, 2018. c(cid:13)2018 Association for Computational Linguistics
 Proceedings of NAACL-HLT 2018, pages 758–763"
-2a12c72b0328a23b0d7ea63db1f93abf3054beec,Extended Feature Descriptor and Vehicle Motion Model with Tracking-by-Detection for Pedestrian Active Safety,"IEICE TRANS. ??, VOL.Exx–??, NO.xx XXXX 200x
-PAPER
-Extended Feature Descriptor and Vehicle Motion Model with
-Tracking-by-detection for Pedestrian Active Safety
-Hirokatsu KATAOKAy;yya), Kimimasa TAMURAy, Nonmembers, Kenji IWATAyyy, Yutaka SATOHyyy, Members,
-Yasuhiro MATSUIyyyy, Nonmember, and Yoshimitsu AOKIy, Member
-SUMMARY
-The percentage of pedestrian deaths in traf‌f‌ic accidents is
-on the rise in Japan. In recent years, there have been calls for measures
-to be introduced to protect vulnerable road users such as pedestrians and
-yclists. In this study, a method to detect and track pedestrians using an
-in-vehicle camera is presented. We improve the technology of detecting
-pedestrians by using the highly accurate images obtained with a monocular
-amera. In the detection step, we employ ECoHOG as the feature descrip-
-tor; it accumulates the integrated gradient intensities. In the tracking step,
-we apply an effective motion model using optical flow and the proposed
-feature descriptor ECoHOG in a tracking-by-detection framework. These
-techniques were veriﬁed using images captured on real roads.
-key words: Pedestrian Active Safety, Tracking-by-detection, ECoHOG,
-Particle Filter, Vehicle Motion Model"
 2a1d3e1baf323e61da517a054b9571559815a651,Temporal normalization of videos using visual speech,"Temporal Normalization of Videos Using Visual Speech
 Usman Saeed
 EURECOM Sophia Antipolis
@@ -23616,29 +20037,12 @@ S.S.114 Km 6,400, 98128 Messina, Italy"
 2a08147bf88041c6e0354e26762b4e4d65d5163f,Trimmed Event Recognition ( Moments in Time ) : Submission to ActivityNet Challenge 2018,"Trimmed Event Recognition (Moments in Time):
 Submission to ActivityNet Challenge 2018
 Dongyang Cai"
-2a40917ef436000b22bc7c6f35400440ef673d36,Learning clustered sub-spaces for sketch-based image retrieval,"Learning Clustered Sub-spaces for Sketch-based Image Retrieval
-Koustav Ghosal Ameya Prabhu
-Riddhiman Dasgupta
-koustav.ghosal∗
-meya.prabhu∗
-riddhiman.dasgupta∗
-Anoop M Namboodiri
-noop†
-Centre for Visual Information Technology, IIIT-Hyderabad, India"
-2ac31bc7a4dd0256166208dcc8d5dfa99347117e,A Window-Based Classifier for Automatic Video-Based Reidentification,"A Window-Based Classiﬁer for Automatic
-Video-Based Reidentiﬁcation
-Dario Figueira, Matteo Taiana, Jacinto C. Nascimento, Member, IEEE, and Alexandre Bernardino, Member, IEEE"
 2a06341b40b3fd27483b2a8d8cbf86fddf45e423,Automatic generation of ground truth for the evaluation of obstacle detection and tracking techniques,"Automatic generation of ground truth for the evaluation of obstacle detection
 nd tracking techniques
 Hatem Hajri∗, Emmanuel Doucet∗†, Marc Revilloud∗, Lynda Halit∗, Benoit Lusetti∗,
 Mohamed-Cherif Rahal∗
 Automated Driving Research Team, Institut VEDECOM, Versailles, France
 InnoCoRe Team, Valeo, Bobigny, France"
-2a86bcdfb1d817ddb76ba202319f8267a36c0f62,PCL: Proposal Cluster Learning for Weakly Supervised Object Detection,"JOURNAL OF LATEX CLASS FILES
-PCL: Proposal Cluster Learning for Weakly
-Supervised Object Detection
-Peng Tang, Xinggang Wang, Member, IEEE, Song Bai, Wei Shen, Xiang Bai, Senior Member, IEEE,
-Wenyu Liu, Senior Member, IEEE, and Alan Yuille, Fellow, IEEE"
 2a1deffc67ccb5f8ca5897ac3f31dac09af70f05,Robust Subspace Clustering via Tighter Rank Approximation,"Robust Subspace Clustering via Tighter Rank
 Approximation
 Zhao Kang
@@ -23681,12 +20085,6 @@ Localization And Mapping: Towards the
 Robust-Perception Age
 Cesar Cadena, Luca Carlone, Henry Carrillo, Yasir Latif,
 Davide Scaramuzza, Jos´e Neira, Ian Reid, John J. Leonard"
-2ade545f25f5ba66295aeab3a89583e7cf6101b3,A Dataset for Airborne Maritime Surveillance Environments,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCSVT.2017.2775524, IEEE
-Transactions on Circuits and Systems for Video Technology
-A Dataset for Airborne Maritime Surveillance
-Environments
-Ricardo Ribeiro, Member, IEEE, Gonc¸alo Cruz, Jorge Matos, Student, IST,
-nd Alexandre Bernardino, Member, IEEE,"
 2a5efa83ea5c4733757b838b84ba6519f873b826,A Continuous Learning for Solving a Face Recognition Problem,"International Journal of Computer Information Systems and Industrial Management Applications.
 ISSN 2150-7988 Volume 4 (2012) pp. 570-577
 © MIR Labs, www.mirlabs.net/ijcisim/index.html
@@ -23717,26 +20115,6 @@ Audience Attention Towards Pervasive Displays
 Florian Alta, Andreas Bullingb, Lukas Meckea, Daniel Buscheka
 LMU Munich
 Munich, Germany"
-ceb4040acf7f27b4ca55da61651a14e3a1ef26a8,Angry Crowds: Detecting Violent Events in Videos,"Angry Crowds:
-Detecting Violent Events in Videos
-Sadegh Mohammadi1, Alessandro Perina1,2, Hamed Kiani1, Vittorio Murino1,3
-Pattern Analysis and Computer Vision (PAVIS),
-Istituto Italiano di Tecnologia, Genova, Italy
-Microsoft Corp,
-WDG Core Data Science, Redmond
-Dept. of Computer Science,
-University of Verona, Italy
-As supplementary material, we selected a few testing video clips from Vio-
-lence in crowds (VIC) [1] dataset to illustrate the effectiveness of the proposed
-Aggression Force compared to the Interaction Force (SFM) [2] and Optical Flow
-for the task of violent detection in video sequences. The scenarios depicted in
-the attached video are captured under very challenging situations including low
-image quality, cluttered background, densely crowded scenes, camera motion,
-occlusions, large scale/illumination variations.
-The qualitative results in video format can be seen in ”video.avi”, highlight-
-ing two major advantages of Aggression Force compared to Social Force and
-Optical Flowing.
-Firstly, the SFM and Optical Flow are very sensitive to footages captured"
 cef6cffd7ad15e7fa5632269ef154d32eaf057af,Emotion Detection Through Facial Feature Recognition,"Emotion Detection Through Facial Feature
 Recognition
 James Pao
@@ -23872,10 +20250,6 @@ Department of Computer Science [1], Department of Science [2], Department of Ele
 OPEN  ACCESS
 Mahatma Gandhi University
 Kerala - India"
-ce85d953086294d989c09ae5c41af795d098d5b2,Bilinear Analysis for Kernel Selection and Nonlinear Feature Extraction,"This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination.
-Bilinear Analysis for Kernel Selection and
-Nonlinear Feature Extraction
-Shu Yang, Shuicheng Yan, Member, IEEE, Chao Zhang, and Xiaoou Tang, Senior Member, IEEE"
 ce13aaf9ab0d3ec3dd9637b2dd5122b4aa711fd7,Local Feature-based Person Re-Identification in Video,"UNIVERSITÄT KARLSRUHE (TH)
 FAKULTÄT FÜR INFORMATIK
 INSTITUT FÜR ANTHROPOMATIK
@@ -23979,34 +20353,12 @@ Youtube-8M Video Understanding
 Fu Li, Chuang Gan, Xiao Liu, Yunlong Bian, Xiang Long, Yandong Li, Zhichao Li, Jie Zhou, Shilei Wen
 Baidu IDL & Tsinghua University"
 cefd107b19201cd9f403e2f9332c690e81f770b5,A Survey on Databases for Facial Expression Analysis,
-ceb02a8f874c84ece88fcc7be1530a581b1cd1b0,A Novel Geometry-based Algorithm for Robust Grasping in Extreme Clutter Environment,"A Novel Geometry-based Algorithm for Robust Grasping in Extreme Clutter
-Environment
-Olyvia Kundua, Swagat Kumara,∗
-TATA Consultancy Services, Bangalore, India 560066"
-ce54dd2b0c6c75208ac77420233419066dd0117f,ISSN 2348-375 X EAR SEGMENTATION USING DIFFERENTIAL BOX COUNTING APPROACH,"Geetha et al. UJEAS 2014, 02 (01): Page 77-78
-ISSN 2348-375X
-Unique Journal of Engineering and Advanced Sciences
-Available online: www.ujconline.net
-Research Article
-EAR SEGMENTATION USING DIFFERENTIAL BOX COUNTING APPROACH
-Geetha Prem P1*, Manikandaprabu N2, Dhivya P3, Deepa A4
-PG Scholar, AVS Engineering College, TN, India
-Lecturer, Senthur Polytechnic College, TN, India
-Asso. Prof/ECE, AVS Engineering College, Salem
-ME (Communication Systems), Sona College of Technology, Salem
-Received: 28-12-2013; Revised: 24-01-2014; Accepted: 20-02-2014
-*Corresponding Author: P. Prem Geetha, PG Scholar, AVS Engineering College, TN, India Email:"
 ced61099a0306d555486162670f1213f2c72b020,Multi-Vehicle Trajectories Generation for Vehicle-to-Vehicle Encounters,"Multi-Vehicle Trajectories Generation for Vehicle-to-Vehicle Encounters
 Wenhao Ding, Wenshuo Wang, and Ding Zhao"
 ceedb191328ac4d968853b948a32b5689c2ac2a2,Semisupervised Dimensionality Reduction and Classification Through Virtual Label Regression,"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 41, NO. 3, JUNE 2011
 Semisupervised Dimensionality Reduction and
 Classiﬁcation Through Virtual Label Regression
 Feiping Nie, Dong Xu, Xuelong Li, Senior Member, IEEE, and Shiming Xiang"
-ce9a61bcba6decba72f91497085807bface02daf,Eigen-harmonics faces: face recognition under generic lighting,"Eigen-Harmonics Faces: Face Recognition under Generic Lighting
-Laiyun Qing1,2, Shiguang Shan2, Wen Gao1,2
-Graduate School, CAS, Beijing, China, 100080
-ICT-ISVISION Joint R&D Laboratory for Face Recognition, CAS, Beijing, China, 100080
-Emails: {lyqing, sgshan, wgao}jdl.ac.cn"
 cebfafea92ed51b74a8d27c730efdacd65572c40,Matching 2.5D face scans to 3D models,"JANUARY 2006
 Matching 2.5D Face Scans to 3D Models
 Xiaoguang Lu, Student Member, IEEE, Anil K. Jain, Fellow, IEEE, and
@@ -24019,14 +20371,6 @@ Review on Computer Vision Techniques in Emergency Situations
 Laura Lopez-Fuentes · Joost van de Weijer · Manuel Gonz´alez-Hidalgo · Harald
 Skinnemoen · Andrew D. Bagdanov
 Received: date / Accepted: date"
-fcc76b1762dbeb49cbfa30ca66bd405e015ca331,Training-Free Synthesized Face Sketch Recognition Using Image Quality Assessment Metrics,"Training-Free Synthesized Face Sketch Recognition
-Using Image Quality Assessment Metrics
-Nannan Wang, Member, IEEE, Jie Li, Leiyu Sun, Bin Song, and Xinbo Gao, Senior Member, IEEE"
-fc6256156fbfdb21221c0aed2719f2b420e9d3b4,Pattern Recognition with Localized Gabor Wavelet Grids,"Pattern Recognition with Localized Gabor Wavelet Grids
-Vinay Kumar B
-Subex Azure Limited, Bangalore, India
-Sai Sharan D R
-Accenture, Bangalore, India"
 fc1e37fb16006b62848def92a51434fc74a2431a,A Comprehensive Analysis of Deep Regression,"DRAFT
 A Comprehensive Analysis of Deep Regression
 St´ephane Lathuili`ere, Pablo Mesejo, Xavier Alameda-Pineda, Member IEEE, and Radu Horaud"
@@ -24066,26 +20410,6 @@ y Ef‌f‌icient Graph Partitioning
 Ratnesh Kumar, Guillaume Charpiat, Monique Thonnat
 STARS Team, INRIA, Sophia Antipolis, France"
 fcb64ef4421cebb80eb33f62c7726f339eb2bb62,Deep View-Aware Metric Learning for Person Re-Identification,Proceedings of the Twenty-Seventh International Joint Conference on Artiﬁcial Intelligence (IJCAI-18)
-fc64f43cdcf4898b15ddce8b441d2ab9daa324f0,GABOR FILTER-BASED FACE RECOGNITION TECHNIQUE,"THE PUBLISHING HOUSE
-OF THE ROMANIAN ACADEMY
-PROCEEDINGS OF THE ROMANIAN ACADEMY, Series A,
-Volume 11, Number 3/2010, pp. 277–283
-GABOR FILTER-BASED FACE RECOGNITION TECHNIQUE
-Tudor BARBU
-Institute of Computer Science, Romanian Academy, Iaşi, Romania
-E-mail:
-We propose a novel human face recognition approach in this paper, based on two-dimensional Gabor
-filtering and supervised classification. The feature extraction technique proposed in this article uses
-D  Gabor  filter  banks  and  produces  robust  3D  face  feature  vectors.  A  supervised  classifier,  using
-minimum average distances, is developed for these vectors. The recognition process is completed by a
-threshold-based  face  verification  method,  also  provided.  A  high  facial  recognition  rate  is  obtained
-using  our  technique.  Some  experiments,  whose  satisfactory  results  prove  the  effectiveness  of  this
-recognition approach, are also described in the paper.
-Key words: Face recognition; Face identification; Feature vector; 2D Gabor filter; Supervised classification;
-Face verification.
-. INTRODUCTION
-This  article  approaches  an  important  biometric  domain,  which  is  human  face  recognition.  Face
-represents  a  physiological  biometric  identifier  that  is  widely  used  in  person  recognition.  During  the  past"
 fc068f7f8a3b2921ec4f3246e9b6c6015165df9a,Beyond Part Models: Person Retrieval with Refined Part Pooling (and A Strong Convolutional Baseline),"Beyond Part Models: Person Retrieval with Reﬁned Part Pooling
 (and A Strong Convolutional Baseline)
 Yifan Sun†, Liang Zheng‡, Yi Yang‡, Qi Tian§, Shengjin Wang†∗
@@ -24173,10 +20497,6 @@ Charmin Asirimath, Jayampathy Ratnayake, and Chathuranga Weeraddana"
 fcc6fd9b243474cd96d5a7f4a974f0ef85e7ddf7,InclusiveFaceNet: Improving Face Attribute Detection with Race and Gender Diversity,"Improving Face Attribute Detection with Race and Gender Diversity
 InclusiveFaceNet:
 Hee Jung Ryu 1 Hartwig Adam * 1 Margaret Mitchell * 1"
-fca6df7d36f449d48a8d1e48a78c860d52e3baf8,Fine-Grained Age Estimation in the wild with Attention LSTM Networks,"Fine-Grained Age Estimation in the wild with
-Attention LSTM Networks
-Ke Zhang, Member, IEEE, Na Liu, Xingfang Yuan, Student Member, IEEE, Xinyao Guo, Ce Gao,
-nd Zhenbing Zhao Member, IEEE,"
 fc5fb5d0fb7c654e8fda140e5bc53f4f422a5d6e,Computationally Efficient Invariant Facial Expression Recognition,"Research Journal of Recent Sciences _________________________________________________ ISSN 2277-2502
 Vol. 3(2), 61-68, February (2014)
 Res.J.Recent Sci.
@@ -24321,11 +20641,6 @@ Received: 11.01.2013
 Accepted/Published Online: 09.11.2013
 (cid:15)
 Final Version: 01.01.2016"
-904b96d0691c62cacd1d9456e623ab24901763a0,Facade Segmentation in the Wild,"Facade Segmentation in the Wild
-John Femiani1 Wamiq Reyaz Para2 Niloy Mitra3
-Peter Wonka2
-Miami University1
-KAUST2"
 90443ec362dc553f29fbf824b4d13fd7f26f2a32,A Vote-and-Verify Strategy for Fast Spatial Verification in Image Retrieval,"A Vote-and-Verify Strategy for Fast Spatial
 Veriﬁcation in Image Retrieval
 Johannes L. Sch¨onberger1(cid:63), True Price2(cid:63), Torsten Sattler1(cid:63),
@@ -24426,10 +20741,6 @@ Mauricio Villegas and Roberto Paredes
 Institut Tecnol`ogic d’Inform`atica
 Universitat Polit`ecnica de Val`encia
 Cam´ı de Vera s/n, 46022 Val`encia (Spain)"
-90863022d8593a70e574816e6a43f1fdab842e27,Two Dimensional Stochastic Configuration Networks for Image Data Analytics,"SUBMITTED TO IEEE TRANSACTIONS ON CYBERNETICS
-Two Dimensional Stochastic Conﬁguration
-Networks for Image Data Analytics
-Ming Li, Member, IEEE, Dianhui Wang*, Senior Member, IEEE"
 9070045c1a9564a5f25b42f3facc7edf4c302483,Everybody needs somebody: Modeling social and grouping behavior on a linear programming multiple people tracker,"Everybody needs somebody: Modeling social and grouping behavior on a linear
 programming multiple people tracker
 Laura Leal-Taix´e, Gerard Pons-Moll and Bodo Rosenhahn
@@ -24449,24 +20760,6 @@ Kittikhun Meethongjan
 Department of Computer Graphic, Faculty of Computer
 Science & Information System, University Technology of
 Malaysia, 81310 Skudai, Johor, Malaysia. +60127204314"
-902114feaf33deac209225c210bbdecbd9ef33b1,Side-Information based Linear Discriminant Analysis for Face Recognition,"KAN et al.: SIDE-INFORMATION BASED LDA FOR FACE RECOGNITION
-Side-Information based Linear
-Discriminant Analysis for Face
-Recognition
-Meina Kan1,2,3
-Shiguang Shan1,2
-Dong Xu3
-Xilin Chen1,2
-Digital Media Research Center,
-Institute of Computing
-Technology, CAS, Beijing, China
-Key Laboratory of Intelligent
-Information Processing, Chinese
-Academy of Sciences, Beijing,
-China
-School of Computer Engineering,
-Nanyang Technological
-University, Singapore"
 902d1b14b076120cb21029b51ed8e63529fe686d,PERFORMANCE ANALYSIS FOR FACIAL EXPRESSION RECOGNITION UNDER SALT AND PEPPER NOISE WITH MEDIAN FILTER APPROACH,"PERFORMANCE ANALYSIS FOR FACIAL EXPRESSION
 RECOGNITION UNDER SALT AND PEPPER NOISE WITH
 MEDIAN FILTER APPROACH
@@ -24490,30 +20783,6 @@ Anonymous Author 3"
 Performance and Energy Modeling of
 Heterogeneous Many-core Architectures
 Rui Pedro Gaspar Pinheiro"
-903a8db7bac7a2826cd98ae5425d839852274f7d,Like at First Sight: Understanding User Engagement with the World of Microvideos,"Like at First Sight: Understanding User
-Engagement with the World of Microvideos
-Sagar Joglekar1(B), Nishanth Sastry1, and Miriam Redi2
-Kings College, London, UK
-Bell Labs, Cambridge, UK"
-90d735cffd84e8f2ae4d0c9493590f3a7d99daf1,Recognition of Faces using Efficient Multiscale Local Binary Pattern and Kernel Discriminant Analysis in Varying Environment,"Original Research Paper
-American Journal of Engineering and Applied Sciences
-Recognition of Faces using Efficient Multiscale Local Binary
-Pattern and Kernel Discriminant Analysis in Varying
-Environment
-Sujata G. Bhele and
-V.H. Mankar
-Department of Electronics Engg, Priyadarshini College of Engg, Nagpur, India
-Department of Electronics Engg, Government Polytechnic, Nagpur, India
-Article history
-Received: 20-06-2017
-Revised: 18-07-2017
-Accepted: 21-08-2017
-Corresponding Author:
-Sujata G. Bhele
-Department of Electronics
-Engg, Priyadarshini College of
-Engg, Nagpur, India
-Email:"
 90e36f66c25a4c73a252102c6c6c329c36d82676,Probably Unknown: Deep Inverse Sensor Modelling In Radar,"Probably Unknown: Deep Inverse Sensor Modelling Radar
 Rob Weston, Sarah Cen, Paul Newman and Ingmar Posner"
 9040fa6a62f6c185473f4043846de3aa7920624b,THERMAL IMAGING AS A BIOMETRICS APPROACH TO FACIAL SIGNATURE AUTHENTICATION 1,"October 2015, Volume 2, Issue 10
@@ -24541,13 +20810,6 @@ Problem using Total Variation
 Yvain Qu´eau1, Fran¸cois Lauze2, and Jean-Denis Durou1
 IRIT, UMR CNRS 5505, Toulouse, France
 Dept. of Computer Science, Univ. of Copenhagen, Denmark"
-90bc77c8eb4cc28520b3fda4f492276602869019,StairNet: Top-Down Semantic Aggregation for Accurate One Shot Detection,"StairNet: Top-Down Semantic Aggregation for Accurate One Shot Detection
-Sanghyun Woo
-KAIST
-Soonmin Hwang
-KAIST
-In So Kweon
-KAIST"
 90c80317fa68784a3fe4fc3136bb188895b09fa4,Sparsity Invariant CNNs,"Sparsity Invariant CNNs
 Jonas Uhrig(cid:63),1,2 Nick Schneider(cid:63),1,3
 Lukas Schneider1,4
@@ -24585,10 +20847,6 @@ discuss multiple approaches we implemented to do the same.
 Background and Related work:"
 361367838ee5d9d5c9a77c69c1c56b1c309ab236,Salient Object Detection: A Survey,"Salient Object Detection: A Survey
 Ali Borji, Ming–Ming Cheng, Huaizu Jiang and Jia Li"
-36cf96fe11a2c1ea4d999a7f86ffef6eea7b5958,RGB-D Face Recognition With Texture and Attribute Features,"RGB-D Face Recognition with Texture and
-Attribute Features
-Gaurav Goswami, Student Member, IEEE, Mayank Vatsa, Senior Member, IEEE, and Richa Singh, Senior
-Member, IEEE"
 363913a335053c837d5fc279032d28c418dda1dc,ECE 533 – Image Processing Project Face Recognition Techniques,"ECE533 – Image Processing Project
 Face Recognition
 Techniques
@@ -24788,10 +21046,6 @@ Computer Vision Group
 Friedrich Schiller University Jena
 Germany
 www.inf-cv.uni-jena.de"
-36c91b1342c1357877e89b4c43f8eadb39755c0b,Recognizing Human-Object Interactions in Still Images by Modeling the Mutual Context of Objects and Human Poses,"Recognizing Human-Object Interactions in
-Still Images by Modeling the Mutual Context
-of Objects and Human Poses
-Bangpeng Yao, Member, IEEE, and Li Fei-Fei, Member, IEEE"
 362cfe79a6822f9e317555c5e3469dd038b9053f,Damped Gauss-Newton algorithm for nonnegative Tucker decomposition,"978-1-4577-0568-7/11/$26.00 ©2011 IEEE
 DY, An	, G (cid:2) (cid:12)Y  G  A	(cid:12)2
 DECOMPOSITION
@@ -24887,9 +21141,6 @@ Albert-Ludwigs-Universität Freiburg
 Department of Computer Science
 Computer Vision Group
 Supervisor: Prof. Dr. Thomas Brox"
-360a590703542f2ba345b432416398b6dad9e3fb,Multimodal Person Reidentification Using RGB-D Cameras,"Multi-modal Person Re-Identiﬁcation
-Using RGB-D Cameras
-Federico Pala, Member, IEEE, Riccardo Satta, Giorgio Fumera, Member, IEEE, and Fabio Roli, Fellow, IEEE"
 36688a79cc8926f489ccb6e6dadba15afbb4b6a4,Linear discriminant analysis for the small sample size problem: an overview,"Int. J. Mach. Learn. & Cyber.
 DOI 10.1007/s13042-013-0226-9
 O R I G I N A L A R T I C L E
@@ -24952,14 +21203,6 @@ http://www.eecs.berkeley.edu/Pubs/TechRpts/2012/EECS-2012-53.html
 May 1, 2012"
 36918b2ef6b20ffb8cffe458c0067742500c6149,"""Look, some Green Circles!"": Learning to Quantify from Images","Proceedings of the 5th Workshop on Vision and Language, pages 75–79,
 Berlin, Germany, August 12 2016. c(cid:13)2016 Association for Computational Linguistics"
-36b27f74b9a7fe12cf6593cc8b73e764efce7dda,A Face ’ s Parent / Offspring Determination using Geometric Features and PCA : A Novel Approach,"A Face’s Parent/Offspring Determination
-using Geometric Features and PCA:
-A Novel Approach
-C. N. Ravi Kumar
-Anil Kumar
-Pramod G
-Dept. of CSE, SJCE
-Mysore, Karnataka, India"
 36119c10f75094e0568cae8256400c94546d973b,The CASIA NIR-VIS 2.0 Face Database,"The CASIA NIR-VIS 2.0 Face Database
 Stan Z. Li, Dong Yi, Zhen Lei and Shengcai Liao
 Center for Biometrics and Security Research & National Laboratory of Pattern Recognition
@@ -25054,12 +21297,6 @@ Carmel Sofer1,2, Ron Dotsch2,3, Daniel H. J. Wigboldus2, and
 Alexander Todorov1,2
 Department of Psychology, Princeton University; 2Behavioural Science Institute, Radboud University
 Nijmegen; and 3Department of Psychology, Utrecht University"
-73764fa9bed84ad2c932dc8089ace7fa8fa7c1d3,"Disparity Statistics for Pedestrian Detection: Combining Appearance, Motion and Stereo","Disparity Statistics for Pedestrian Detection:
-Combining Appearance, Motion and Stereo
-Stefan Walk1, Konrad Schindler1,2, and Bernt Schiele1,3
-Computer Science Department, TU Darmstadt
-Photogrammetry and Remote Sensing Group, ETH Z¨urich
-MPI Informatics, Saarbr¨ucken"
 73bbbfac7b144f835840fe7f7b5139283bf4f3f1,Do we spontaneously form stable trustworthiness impressions from facial appearance?,"ATTITUDES AND SOCIAL COGNITION
 Do We Spontaneously Form Stable Trustworthiness Impressions From
 Facial Appearance?
@@ -25086,11 +21323,6 @@ Transductive Zero-Shot Action Recognition by
 Word-Vector Embedding
 Xun Xu · Timothy Hospedales · Shaogang Gong
 Received: date / Accepted: date"
-7323b594d3a8508f809e276aa2d224c4e7ec5a80,An Experimental Evaluation of Covariates Effects on Unconstrained Face Verification,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015
-An Experimental Evaluation of Covariates
-Effects on Unconstrained Face Veriﬁcation
-Boyu Lu, Student Member, IEEE, Jun-Cheng Chen, Member, IEEE, Carlos D Castillo, Member, IEEE
-nd Rama Chellappa, Fellow, IEEE"
 73be334ecc48751269443b0db2629086125e69f5,Robust Face Recognition under Difficult Lighting Conditions,"International Journal of Technological Exploration and Learning (IJTEL)
 Volume 1 Issue 1 (August 2012)
 Robust Face Recognition under Difficult Lighting
@@ -25176,26 +21408,6 @@ Link to published version
 http://dicta2010.conference.nicta.com.au/
 Griffith Research Online
 https://research-repository.griffith.edu.au"
-735c38361d77e707ac48f0d040493c65ca559d3c,Machine Learning for Simplifying the Use of Cardiac Image Databases. (Apprentissage automatique pour simplifier l'utilisation de banques d'images cardiaques),"N°:  2009 ENAM XXXX
-École doctorale n° 84 :
-Sciences et technologies de l’information et de la communication
-Doctorat ParisTech
-T H È S E
-pour obtenir le grade de docteur délivré par
-l’École nationale supérieure des mines de Paris
-Spécialité “ Contrôle, optimisation et prospective ”
-présentée et soutenue publiquement par
-Ján MARGETA
-le 14 Décembre 2015
-Apprentissage automatique pour simplifier
-l’utilisation de banques d’images cardiaques
-Machine Learning for Simplifying
-the Use of Cardiac Image Databases
-Directeurs de thèse : Nicholas AYACHE et Antonio CRIMINISI
-M. Patrick CLARYSSE, DR, Creatis, CNRS, INSA Lyon
-M. Bjoern MENZE, Professeur, ImageBioComp Group, TU München
-M. Hervé DELINGETTE, DR, Asclepios Research Project, Inria Sophia Antipolis
-M. Antonio CRIMINISI, Chercheur principal, MLP Group, Microsoft Research Cambridge"
 73c9cbbf3f9cea1bc7dce98fce429bf0616a1a8c,Unsupervised Learning of Object Landmarks by Factorized Spatial Embeddings,"imagesViewpoint factorizationLearned landmarksFigure1.Wepresentanovelmethodthatcanlearnviewpointin-variantlandmarkswithoutanysupervision.Themethodusesaprocessofviewpointfactorizationwhichlearnsadeeplandmarkdetectorcompatiblewithimagedeformations.Itcanbeappliedtorigidanddeformableobjectsandobjectcategories.terns.Achievingadeeperunderstandingofobjectsrequiresmodelingtheirintrinsicviewpoint-independentstructure.Oftenthisstructureisdeﬁnedmanuallybyspecifyingen-titiessuchaslandmarks,parts,andskeletons.Givensufﬁ-cientmanualannotations,itispossibletoteachdeepneuralnetworksandothermodelstorecognizesuchstructuresinimages.However,theproblemoflearningsuchstructureswithoutmanualsupervisionremainslargelyopen.Inthispaper,wecontributeanewapproachtolearnviewpoint-independentrepresentationsofobjectsfromim-ageswithoutmanualsupervision(ﬁg.1).Weformulatethistaskasafactorizationproblem,wheretheeffectsofimagedeformations,forexamplearisingfromaviewpointchange,areexplainedbythemotionofareferenceframeattachedtotheobjectandindependentoftheviewpoint.Afterdescribingthegeneralprinciple(sec.3.1),wein-1"
 73866bdb723841da93b6ad93afe3d72817e2b377,Dense and Low-Rank Gaussian CRFs Using Deep Embeddings,"Dense and Low-Rank Gaussian CRFs Using Deep Embeddings
 Siddhartha Chandra1
@@ -25240,49 +21452,7 @@ utism spectrum disorders (ASD) and their
 first-degree relatives: a family study
 Olga V. Sysoeva1,2, John N. Constantino1*
 nd Andrey P. Anokhin1"
-735be89c989ab7819e2f640960a8895e79913e21,A Video-Based Door Monitoring System Using Local Appearance-Based Face Models,"International Journal for Research in Applied Science & Engineering Technology (IJRASET)
-ISSN: 2321-9653; IC Value: 45.98; SJ Impact Factor:6.887
-Volume 5 Issue X, October 2017- Available at www.ijraset.com
-A Video-Based Door Monitoring System Using
-Local Appearance-Based Face Models
-P.G. Student, Department of Electronics & Telecommunications, Zeal College Of Engineering,Pune,Maharashtra,India
-Assistant Professor, Department of Electronics & Telecommunications, Zeal College Of Engineering, Pune ,India
-Tejaswita Wakhure1, Prof.P.A.More2"
-73fa81d2b01c81c6ede71d046f9101440884e604,Fuzzy Based Texton Binary Shape Matrix ( FTBSM ) for Texture Classification,"Global Journal of Computer Science and Technology
-Graphics & Vision
-Volume 12 Issue 15 Version 1.0 Year 2012
-Type: Double Blind Peer Reviewed International Research Journal
-Publisher: Global Journals Inc. (USA)
-Online ISSN: 0975-4172 & Print ISSN: 0975-4350
-Fuzzy  Based  Texton  Binary  Shape  Matrix  (FTBSM)  for  Texture
-Classification
-By P.Chandra Sekhar Reddy & B.Eswara Reddy
-Jntua College of Engineering, Anantapur, A.P, India"
 3e08d000ba3dd382c16e4295435ef8264235ccbc,Multiple People Tracking in Smart Camera Networks by Greedy Joint-Likelihood Maximization,
-3e00dd86c084d8680409c65c1a48f1b3aa864eb7,Deep Crisp Boundaries: From Boundaries to Higher-Level Tasks,"Deep Crisp Boundaries:
-From Boundaries to Higher-level Tasks
-Yupei Wang, Student Member, IEEE, Xin Zhao, Member, IEEE, Yin Li, Member, IEEE,
-nd Kaiqi Huang, Senior Member, IEEE"
-3e4b38b0574e740dcbd8f8c5dfe05dbfb2a92c07,Facial Expression Recognition with Local Binary Patterns and Linear Programming 1,"FACIAL EXPRESSION RECOGNITION WITH LOCAL BINARY PATTERNS
-AND LINEAR PROGRAMMING
-Xiaoyi Feng1, 2, Matti Pietikäinen1, Abdenour Hadid1
-Machine Vision Group, Infotech Oulu and Dept. of Electrical and Information Engineering
-P. O. Box 4500 Fin-90014 University of Oulu, Finland
-2 College of Electronics and Information, Northwestern Polytechnic University
-710072 Xi’an, China
-In  this  work,  we  propose  a  novel  approach  to  recognize  facial  expressions  from  static
-images. First, the Local Binary Patterns (LBP) are used to efficiently represent the facial
-images and then the Linear Programming (LP) technique is adopted to classify the seven
-facial  expressions  anger,  disgust,  fear,  happiness,  sadness,  surprise  and  neutral.
-Experimental results demonstrate an average recognition accuracy of 93.8% on the JAFFE
-database, which outperforms the rates of all other reported methods on the same database.
-Introduction
-Facial  expression  recognition  from  static
-images  is  a  more  challenging  problem
-than  from  image  sequences  because  less
-information  for  expression  actions
-vailable.  However,  information  in  a
-single  image  is  sometimes  enough  for"
 3ed186b4337f48e263ef60acffb49f16d5a85511,Discriminatively learned filter bank for acoustic features,"978-1-4799-9988-0/16/$31.00 ©2016 IEEE
 ICASSP 2016"
 3e2588aaa719c63e48fe599a7f0dbea10a41b4eb,Using Sparse Semantic Embeddings Learned from Multimodal Text and Image Data to Model Human Conceptual Knowledge,"Using sparse semantic embeddings learned from multimodal text and
@@ -25300,12 +21470,6 @@ David Hall1,2, Feras Dayoub1,2, John Skinner1,2, Peter Corke1,2, Gustavo Carneir
 Australian Centre for Robotic Vision
 Queensland University of Technology (QUT), 3University of Adelaide
 {d20.hall, feras.dayoub, j6.skinner, peter.corke,"
-3e6fa6cf1fe2e23fdf7716f89b160333c7a93b26,A Performance Evaluation of Single and Multi-feature People Detection,"A Performance Evaluation of Single and
-Multi-Feature People Detection
-Christian Wojek, Bernt Schiele
-{wojek,
-Computer Science Department
-TU Darmstadt"
 3ec0d2c66ba2f00d90470c03969372e610986833,EEG Data of Face Recognition in Case of Biological Compatible Changes: A Pilot Study on Healthy People,
 3ede3ed28329bf48fbd06438a69c4f855bef003f,Large-scale geo-facial image analysis,"Islam et al. EURASIP Journal on Image and Video Processing  (2015) 2015:17
 DOI 10.1186/s13640-015-0070-9
@@ -25322,15 +21486,6 @@ der Technischen Universit¨at Dortmund
 n der Fakult¨at f¨ur Informatik
 Fabian Naße
 Dortmund"
-3e51988542ced911184bce400a2a4af0b044396b,Face recognition system based on principal components analysis and distance measures,"International Journal of Engineering & Technology, 7 (2.21) (2018) 15-19
-International Journal of Engineering & Technology
-Website: www.sciencepubco.com/index.php/IJET
-Research paper
-Face recognition system based on principal components analysis
-nd distance measures
-T. Meenpal *, Aarti Goyal, Ankita Meenpal
-Department of Electronics and Telecommunication, National Institute of Technology, Raipur, Chhattisgarh, India
-*Corresponding author E-mail:"
 3e67058c6ddd0afae692b7665f82124945ea2c5a,On the Learning of Deep Local Features for Robust Face Spoofing Detection,"On the Learning of Deep Local Features for
 Robust Face Spooﬁng Detection
 Gustavo Botelho de Souza1, Jo˜ao Paulo Papa2 and Aparecido Nilceu Marana2 - in Proc. of SIBGRAPI 2018
@@ -25372,10 +21527,6 @@ Zihang Meng1, Nagesh Adluru1, Hyunwoo J. Kim1⋆,
 Glenn Fung2, and Vikas Singh1
 University of Wisconsin – Madison
 American Family Insurance"
-3e73e1e6530c17244a1bb4e4fa071b4a86757a47,Shape Classification Based on Skeletons,"Shape Classification Based on Skeletons
-Xiang Bai , Xingwei Yang , Deguang Yu  and Longin Jan Latecki2
-) HuaZhong University of Science and Technology, Wuhan, China
-) Temple University, Philadelphia, USA"
 3e4f84ce00027723bdfdb21156c9003168bc1c80,A co-training approach to automatic face recognition,"© EURASIP, 2011  -  ISSN 2076-1465
 9th European Signal Processing Conference (EUSIPCO 2011)
 INTRODUCTION"
@@ -25475,17 +21626,6 @@ y 14 sur. Puebla, Pue. C.P. 72570, México"
 3edf3a996790fef8957e21c68ddf48b52238e662,Product of tracking experts for visual tracking of surgical tools,"Product of Tracking Experts for Visual Tracking of Surgical Tools
 Suren Kumar, Madusudanan Sathia Narayanan, Pankaj Singhal, Jason J. Corso and Venkat Krovi
 State University of New York (SUNY) at Buffalo"
-3e159084e12ece3664a17bf4dd0eed8c5f06a33f,Deep Neural Networks with Inexact Matching for Person Re-Identification,"Deep Neural Networks with Inexact Matching for
-Person Re-Identiﬁcation
-Arulkumar Subramaniam
-Indian Institute of Technology Madras
-Chennai, India 600036
-Moitreya Chatterjee
-Indian Institute of Technology Madras
-Chennai, India 600036
-Anurag Mittal
-Indian Institute of Technology Madras
-Chennai, India 600036"
 3e4a54adb53d69984bb1e113eb1a8184be4abe99,Person Authentication from Video of Faces: A Behavioral and Physiological Approach Using Pseudo Hierarchical Hidden Markov Models,"Person Authentication from Video of Faces: A
 Behavioral and Physiological Approach Using
 Pseudo Hierarchical Hidden Markov Models
@@ -25524,13 +21664,6 @@ Department of Technology
 College of Engineering and
 Technology
 Virginia State University"
-3ee425f59da3c8cb42bbfbc2c80122b767eece5e,A NOVEL APPROACH FOR LEARNED REPRESENTATION ON ROBUST FACE RECOGNITION,"© May 2018  | IJIRT  | Volume  4 Issue  12 | ISSN:  2349-6002
-A NOVEL APPROACH FOR LEARNED
-REPRESENTATION  ON ROBUST FACE RECOGNITION
-Sk.Sharmila  1, Lakshma Nayak.M 2
-Pursuing M.Tech (CE&SP), Dept. of ECE, Loyola Institute of Technology and management, India
-Assistant Professor, Dept. of ECE, Loyola Institute of Technology, India
-techniques"
 3e4acf3f2d112fc6516abcdddbe9e17d839f5d9b,Deep Value Networks Learn to Evaluate and Iteratively Refine Structured Outputs,"Deep Value Networks Learn to
 Evaluate and Iteratively Reﬁne Structured Outputs
 Michael Gygli 1 * Mohammad Norouzi 2 Anelia Angelova 2"
@@ -25597,12 +21730,6 @@ Dilip K. Prasad1,∗, Deepu Rajan2, Lily Rachmawati3, Eshan Rajabally4, and Chai
 3e56a9b6c6aced2cb14f9cd7f89d145851c44113,Zero and Few Shot Learning with Semantic Feature Synthesis and Competitive Learning,"Zero and Few Shot Learning with Semantic
 Feature Synthesis and Competitive Learning
 Zhiwu Lu, Jiechao Guan, Aoxue Li, Tao Xiang, An Zhao, and Ji-Rong Wen"
-3eebe8a5adaa49e54ea909b4e2aeb436025c84d5,3 D Face Recognition Using Radon Transform and Symbolic Factorial Discriminant Analysis,"Proc. of Int. Conf. onMultimedia Processing, Communication and Info. Tech., MPCIT
-D Face Recognition Using Radon Transform and
-Symbolic Factorial Discriminant Analysis
-P. S. Hiremath, Manjunath Hiremath
-Department of Computer Science Gulbarga University, Gulbarga 585106 Karnataka, India
-Email:"
 08ff3e9f5ad47e59592ad993348b817003b9c0e4,A Sequential Classifier for Hand Detection in the Framework of Egocentric Vision,"A Sequential Classiﬁer for Hand Detection in the Framework of Egocentric Vision
 Alejandro Betancourt1,2
 Miriam M. L´opez1
@@ -25673,25 +21800,6 @@ Ismail Ben Ayed
 ÉTS Montreal"
 08030f9d34cc96384f672d9f9f296914d594335b,Multiple Object Tracking: A Review,"Multiple Object Tracking: A Literature Review
 Wenhan Luo, Junliang Xing, Anton Milan, Xiaoqin Zhang, Wei Liu, Xiaowei Zhao and Tae-Kyun Kim"
-08ecc281cdf954e405524287ee5920e7c4fb597e,Computational Assessment of Facial Expression Production in ASD Children,"Article
-Computational Assessment of Facial Expression
-Production in ASD Children
-, Pierluigi Carcagnì 1, Cosimo Distante 1, Paolo Spagnolo 1, Pier Luigi Mazzeo 1,
-, Chiara Pellegrino 4, Annalisa Levante 5
-Marco Leo 1,*
-Anna Chiara Rosato 2 , Serena Petrocchi 3
-Filomena De Lumè 5 and Flavia Lecciso 5
-Institute of Applied Sciences and Intelligent Systems, National Research Council of Italy, via Monteroni,
-73100 Lecce, Italy; (P.C.); (C.D.); (P.S.);
-(P.L.M.)
-Amici di Nico Onlus, Via Campania, 6, 73046 Lecce, Italy;
-USI, Institute of Communication and Health, Via Bufﬁ 6, 6900 Lugano, Switzerland;
-5 Dipartimento di Storia, University of Salento, Società e Studi Sull’ Uomo,
-L’ Adelﬁa Onlus, via S. Sangiovanni, 115-73031 Lecce, Italy;
-Studium 2000-Ediﬁcio 5-Via di Valesio, 73100 Lecce, Italy; (A.L.);
-(F.D.L.); (F.L.)
-* Correspondence:
-Received: 4 October 2018; Accepted: 14 November 2018; Published: 16 November 2018"
 0861f86fb65aa915fbfbe918b28aabf31ffba364,An Efficient Facial Annotation with Machine Learning Approach,"International Journal of Computer Trends and Technology (IJCTT) – volume 22 Number 3–April 2015
 An Efficient Facial Annotation with Machine Learning Approach
 A.Anusha,2R.Srinivas
@@ -25844,14 +21952,6 @@ Cheng Chen
 Jean-Marc Odobez
 Idiap Research Institute – CH-1920, Martigny, Switzerland
 (cid:3)"
-08ca2a2a543ee74e2bd6585e0a059b30aae65d30,Semantic Video Segmentation with Using Ensemble of Particular Classifiers and a Deep Neural Network for Systems of Detecting Abnormal Situations,"IT in Industry, vol. 6, 2018                                                                                                                         Published online 09-Feb-2018
-Semantic Video Segmentation with Using Ensemble
-of Particular Classifiers and a Deep Neural Network
-for Systems of Detecting Abnormal Situations
-O. Amosov, Y. Ivanov, S. Zhiganov
-Department of Industrial Electronics
-Komsomolsk-on-Amur State Technical University
-Komsomolsk-on-Amur, Russia"
 089ad31ad5eef41bd179bb0a142d3386a8de5564,Continuous memories for representing sets of vectors and image collections. (Mémoires continues représentant des ensembles de vecteurs et des collections d'images),"Continuous memories for representing sets of vectors
 nd image collections
 Ahmet Iscen
@@ -25999,10 +22099,6 @@ Petr´opolis, RJ 25651-075
 Email:
 S˜ao Bernardo do Campo, SP 09850-901
 Email:"
-08d625158727bd97ba6fc58992158ee55a53011c,HCLAE: High Capacity Locally Aggregating Encodings for Approximate Nearest Neighbor Search,"HCLAE: High Capacity Locally Aggregating Encodings for Approximate Nearest
-Neighbor Search
-{artheru, yz sjr, Shanghai Jiaotong University
-Liu Shicong, Shao Junru, Lu Hongtao"
 08bbb59036c4b85a2418f9702ccd37929c5dd154,Understanding and Predicting the Memorability of Natural Scene Images,"Understanding and Predicting the Memorability of
 Natural Scene Images
 Jiaxin Lu, Mai Xu, Senior Member, IEEE, Ren Yang and Zulin Wang"
@@ -26189,10 +22285,6 @@ opyright owners and it is a condition of accessing these publications that users
 with these rights.
 Take down policy
 The Research Portal is Queen's institutional repository that provides access to Queen's research output. Every effort has been made to"
-82088af865626e2340db12b2e42f3a258053d593,Learning Generative ConvNets via Multi-grid Modeling and Sampling,"Learning Generative ConvNets via Multi-grid Modeling and Sampling
-Ruiqi Gao1∗, Yang Lu2∗, Junpei Zhou3, Song-Chun Zhu1, Ying Nian Wu1
-University of California, Los Angeles, USA, 2 Amazon, 3 Zhejiang University, China
-{sczhu,"
 829f390b3f8ad5856e7ba5ae8568f10cee0c7e6a,A Robust Rotation Invariant Multiview Face Detection in Erratic Illumination Condition,"International Journal of Computer Applications (0975 – 8887)
 Volume 57– No.20, November 2012
 A Robust Rotation Invariant Multiview Face Detection in
@@ -26202,18 +22294,6 @@ Associate Professor, Department of ECE
 Sona College of Technology
 Salem"
 82f6dad08432a5f1b737ba91dd002ff1f89170f7,c○2013 The Association for Computational Linguistics Order copies of this and other ACL proceedings from:,"ACL201351stAnnualMeetingoftheAssociationforComputationalLinguisticsProceedingsoftheConferenceSystemDemonstrationsAugust4-9,2013Soﬁa,Bulgaria"
-82ff25b6e7749e0210b2f8d5a0666f3499745154,Adaptive Multiple Kernels with SIR-Particle Filter Based Multi Human Tracking for Occluded Environment,"International Journal of Computational Intelligence and Informatics, Vol. 3: No. 4, January - March 2014
-Adaptive Multiple Kernels with SIR-Particle Filter
-Based Multi Human Tracking for Occluded
-Environment
-T Karpagavalli
-Department of Electronics and Communication
-KLN College of Information Technology
-Sivagangai, Tamilnadu, India
-S Appavu alias Balamurugan
-Department of Information Technology
-KLN College of Information Technology
-Sivagangai, Tamilnadu, India"
 82a4a35b2bae3e5c51f4d24ea5908c52973bd5be,Real-time emotion recognition for gaming using deep convolutional network features,"Real-time emotion recognition for gaming using
 deep convolutional network features
 S´ebastien Ouellet"
@@ -26229,16 +22309,6 @@ Reprints and permissions:
 sagepub.co.uk/journalsPermissions.nav
 DOI: 10.1177/1059712316664017
 db.sagepub.com"
-82b8a0c3e8f46ab0af5179a9d9a6b137405096d3,Generalized Low-Rank Approximations of Matrices Revisited,"Generalized Low Rank Approximations
-of Matrices Revisited
-Jun Liu, Songcan Chen∗, Zhi-Hua Zhou, Senior Member, IEEE, and Xiaoyang Tan, Member, IEEE"
-82485c89a6b48077b03b65a774fd5768ea768d4d,Unsupervised Adaptive Re-identification in Open World Dynamic Camera Networks,"Unsupervised Adaptive Re-identiﬁcation in Open World Dynamic Camera
-Networks
-Rameswar Panda1,∗ Amran Bhuiyan2,∗,† Vittorio Murino2 Amit K. Roy-Chowdhury1
-Department of ECE
-Pattern Analysis and Computer Vision (PAVIS)
-UC Riverside
-Istituto Italiano di Tecnologia, Italy"
 8210fd10ef1de44265632589f8fc28bc439a57e6,Single Sample Face Recognition via Learning Deep Supervised Autoencoders,"Single Sample Face Recognition via Learning Deep
 Supervised Auto-Encoders
 Shenghua  Gao,  Yuting  Zhang,  Kui  Jia,  Jiwen  Lu,  Yingying  Zhang"
@@ -26273,26 +22343,6 @@ Institute of Medical Technology, Hamburg University of Technology, Hamburg, Germ
 eemagine Medical Imaging Solutions GmbH, Berlin, Germany
 Both authors contributed equally.
 Contact:"
-82e4ae961dca2693742c7d35b8647243d9083613,Hybrid Primary and Secondary Biometric Fusion,"International Journal of Computer Applications (0975 – 8887)
-National Conference on Electronics and Computer Engineering (NCECE-2016)
-Hybrid Primary and Secondary Biometric Fusion
-Kiran Kulkarni
-Department of Instrumentation
-Hubli (Karnataka)
-India
-Raghavendra Shet
-Department of Instrumentation
-Hubli (Karnataka)
-India
-Nalini Iyer
-Department of Instrumentation
-Hubli (Karnataka)
-India
-Section  4  deals  with  the  conclusions  and  possible  directions
-for future work.
-.  PROPOSED METHODOLOGY
-The proposed work consists of two biometric traits (Face and
-Fingerprint)  and  it  aims  at  fusing  these  two  biometric"
 82fc08f5658e0e37aeb36177717621605e11cda1,CNN-Based Patch Matching for Optical Flow with Thresholded Hinge Embedding Loss,"CNN-based Patch Matching for Optical Flow with Thresholded Hinge
 Embedding Loss
 Christian Bailer1
@@ -26306,15 +22356,6 @@ Anurag Chowdhury*, Yousef Atoum+, Luan Tran*, Xiaoming Liu*, Arun Ross*
 *Michigan State University, USA
 +Yarmouk University, Jordan"
 82ab819815c86e85128a2a055a0c0fcd1146b696,Sampled Image Tagging and Retrieval Methods on User Generated Content,[cs.CV]  23 Nov 2016
-82224858677af47b8c836df701eeea8fffaec924,Paper On Person Identification System Using Multi-Model Biometric Based On Face,"International Journal of Science, Engineering and Technology Research (IJSETR)
-Volume 6, Issue 4, April 2017, ISSN: 2278 -7798
-Review Paper On Person Identification System
-Using Multi-Model Biometric Based On Face
-CHETAN  JAMDAR1, AMOL BOKE2
-Chetan  Jamdar, M. Tech Student, Dept Of ECE, G.H. Raisoni Academy Of Engg. And Technology, Nagpur,
-Maharashtra, India.
-Guide details: Amol Boke,  Assistant Professor, Dept Of ECE, G.H. Raisoni Academy Of Engg. And Technology,
-Nagpur, Maharashtra, India"
 82752700f496d4575163b2c59a547d24eb916baf,Similarity Search on Spatio-Textual Point Sets,"Series ISSN: 2367-2005
 0.5441/002/edbt.2016.31
 o1, {shop,jeans}u2, o2, {football,match,stadium}u3, o3, {shop,market}u2, o5, {hurry, tube, time}u1, o4, {tube,ride}u3, o6, {thames,bridge}u3, o7, {bus,ride}spatial thresholdu2, o8, {football,derby}Figure1:STPSJoinqueryscenario.Multipleobjectsarespatiallyortextuallysimilar,butonlyusersu1andu3haveobjectswhicharemutuallysimilar.dayfrom100millionactiveusers.Useractivitiesintheseplatformsgeneratecontentthathastextualcomponent,e.g.,statusupdates,shortmessages,ortags,and,followingthewidespreadadoptionofGPSinmobiledevices,ageospatialcomponent,e.g.,geotaggedtweets,photos,andusercheck-ins.Thus,theactionsofusersaredocumentedbytheirmessagesinsocialnetworksandassuchgenerate“traces”,whichconsistofspatio-textualobjects.Ef‌f‌icientindexingandqueryingofspatio-textualdatahasreceivedalotofattentionoverthepastyears,duetothehighimportanceofsuchcontentinlocation-basedservices,suchasnearbysearchandrecommendations.Inparticu-lar,multipletypesofspatio-textualquerieshavebeenex-tensivelystudied,includingbooleanrangequeries,top-kqueries,k-nearestneighborqueries,andmorerecently,spatio-textualsimilarityjoins[11,7].Nevertheless,inexistingworks,spatio-textualentitiesaretypicallytreatedasisolatedobservations.Atypicalexamplequeryistoﬁndnearbyrestaurantsorhotelsmatchingcertaincriteria.Theworkin[7]dealswithﬁndingpairsofentitiesthatarebothspatiallycloseandtextuallysimilar.Exampleusecasesarede-duplicatingPoints-of-Interestacrossdatasets,orﬁndingmatchingphotostakenatroughlythesameloca-tionandhavingsimilartags.Nowconsiderlookingforsimilarusersinsocialnetworks.Here,auserischaracterizedbythemessagestheygenerateand,ifavailable,respectivelocationinformation.Assuch,eachmessagecanbeconsideredaspatio-textualobject,e.g.,ageotaggedphotoortweet.Witheachuserbeingcharacter-"
@@ -26544,9 +22585,6 @@ SAP SE, Berlin"
 611f9faa6f3aeff3ccd674d779d52c4f9245376c,Multiresolution models for object detection,"Multiresolution models for object detection
 Dennis Park, Deva Ramanan, and Charless Fowlkes
 UC Irvine, Irvine CA 92697, USA,"
-61228ef559e4d73c8c726115f945f5f86d5638fb,Naturalistic Driver Intention and Path Prediction using Recurrent Neural Networks,"Naturalistic Driver Intention and Path Prediction
-using Recurrent Neural Networks
-Alex Zyner, Member, IEEE, Stewart Worrall, Member, IEEE, and Eduardo Nebot, Member, IEEE"
 61e97d8440627bdc9772b3b2083c65f44a51107d,Oxytocin and vasopressin in the human brain: social neuropeptides for translational medicine,"R E V I E W S
 Oxytocin and vasopressin in the
 human brain: social neuropeptides
@@ -26999,9 +23037,6 @@ Furqan M. Khan, Francois Bremond
 INRIA Sophia Antipolis-Mediterrannee
 004 Route des Lucioles, Sophia Antipolis Cedex, France
 {furqan.khan |"
-7b6f0c4b22aee0cb4987cba9df121d4076fac5a5,On Learning 3D Face Morphable Model from In-the-wild Images,"On Learning 3D Face Morphable Model
-from In-the-wild Images
-Luan Tran, and Xiaoming Liu, Member, IEEE"
 7b0e81249159686337ca2cfe81662123906b6b26,An Automatic Eye Detection Method for Gray Intensity Facial Images,"IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 4, No 2, July 2011
 ISSN (Online): 1694-0814
 www.IJCSI.org
@@ -27040,26 +23075,6 @@ Emre Akbas, Miguel P. Eckstein"
 Recognition for Objects by Relationships Between Attributes
 Hiroka Horiguchi*, Kazuo Ikeshiro and Hiroki Imamura
 Graduate School of Engineering, Soka University, Hachioji-Shi, Tokyo, Japan"
-7b9ebcc8b9c05ef661182fe73438b7725584817d,Restoring effects of oxytocin on the attentional preference for faces in autism,"Citation: Transl Psychiatry (2017) 7, e1097; doi:10.1038/tp.2017.67
-www.nature.com/tp
-ORIGINAL ARTICLE
-Restoring effects of oxytocin on the attentional preference
-for faces in autism
-M Kanat1,2, I Spenthof1,3, A Riedel4, LT van Elst2,4, M Heinrichs1,2 and G Domes1,2,3
-Reduced attentional preference for faces and symptoms of social anxiety are common in autism spectrum disorders (ASDs). The
-neuropeptide oxytocin triggers anxiolytic functions and enhances eye gaze, facial emotion recognition and neural correlates of face
-processing in ASD. Here we investigated whether a single dose of oxytocin increases attention to faces in ASD. As a secondary
-question, we explored the influence of social anxiety on these effects. We tested for oxytocin’s effects on attention to neutral faces
-s compared to houses in a sample of 29 autistic individuals and 30 control participants using a dot-probe paradigm with two
-different presentation times (100 or 500 ms). A single dose of 24 IU oxytocin was administered in a randomized, double-blind
-placebo-controlled, cross-over design. Under placebo, ASD individuals paid less attention to faces presented for 500 ms than did
-ontrols. Oxytocin administration increased the allocation of attention toward faces in ASD to a level observed in controls.
-Secondary analyses revealed that these oxytocin effects primarily occurred in ASD individuals with high levels of social anxiety who
-were characterized by attentional avoidance of faces under placebo. Our results conﬁrm a positive influence of intranasal oxytocin
-on social attention processes in ASD. Further, they suggest that oxytocin may in particular restore the attentional preference for
-facial information in ASD individuals with high social anxiety. We conclude that oxytocin’s anxiolytic properties may partially
-ccount for its positive effects on socio-cognitive functioning in ASD, such as enhanced eye gaze and facial emotion recognition.
-Translational Psychiatry (2017) 7, e1097; doi:10.1038/tp.2017.67; published online 18 April 2017"
 7b9b3794f79f87ca8a048d86954e0a72a5f97758,Passing an Enhanced Turing Test - Interacting with Lifelike Computer Representations of Specific Individuals,"DOI 10.1515/jisys-2013-0016      Journal of Intelligent Systems 2013; 22(4): 365–415
 Avelino J. Gonzalez*, Jason Leigh, Ronald F. DeMara, Andrew
 Johnson, Steven Jones, Sangyoon Lee, Victor Hung, Luc
@@ -27078,12 +23093,6 @@ Andreas Bulling
 MPI for Informatics
 Otmar Hilliges
 ETH Zurich"
-7bdcd85efd1e3ce14b7934ff642b76f017419751,Learning Discriminant Face Descriptor,"Learning Discriminant Face Descriptor
-Zhen Lei, Member, IEEE, Matti Pietika¨ inen, Fellow, IEEE, and Stan Z. Li, Fellow, IEEE"
-7b1dd2708e1d7bf0fdcda437de1970a9a6facc0d,Deep Recurrent Convolutional Neural Network: Improving Performance For Speech Recognition,"Deep Recurrent Convolutional Neural Network:
-Improving Performance For Speech Recognition
-Zewang Zhang, Student Member, IEEE, Zheng Sun, Student Member, IEEE, Jiaqi Liu, Student Member, IEEE,
-Jingwen Chen, Student Member, IEEE, Zhao Huo, Member, IEEE, and Xiao Zhang, Member, IEEE"
 7bbaa09c9e318da4370a83b126bcdb214e7f8428,"FaaSter, Better, Cheaper: The Prospect of Serverless Scientific Computing and HPC","FaaSter, Better, Cheaper: The Prospect of
 Serverless Scientiﬁc Computing and HPC
 Josef Spillner1, Cristian Mateos2, and David A. Monge3
@@ -27127,11 +23136,6 @@ Matteo Fabbri(cid:63), Fabio Lanzi(cid:63), Simone Calderara(cid:63), Andrea Pal
 Vezzani, and Rita Cucchiara
 Department of Engineering “Enzo Ferrari”
 University of Modena and Reggio Emilia, Italy"
-7b331c80a91acf3616afd88e78801ac55c874f43,Multiple Player Tracking in Sports Video: A Dual-Mode Two-Way Bayesian Inference Approach With Progressive Observation Modeling,"Multiple Player Tracking in Sports Video: A
-Dual-Mode Two-Way Bayesian Inference Approach
-With Progressive Observation Modeling
-Junliang Xing, Student Member, IEEE, Haizhou Ai, Senior Member, IEEE, Liwei Liu, and
-Shihong Lao, Member, IEEE"
 7b8e9c50f74ce6ca66a8ab61fb18ca31d26cf13f,Nonlinear Channels Aggregation Networks for Deep Action Recognition,"Under review as a conference paper at ICLR 2019
 Nonlinear Channels Aggregation Networks
 for Deep Action Recognition
@@ -27279,10 +23283,6 @@ engineering ,Jaipur(INDIA)"
 6bcc2b50e32bdbb0c668f75000badf21e6cd0839,Knowledge Projection for Deep Neural Networks,"Knowledge Projection for Effective Design of
 Thinner and Faster Deep Neural Networks
 Zhi Zhang, Guanghan Ning, and Zhihai He"
-6be0ab66c31023762e26d309a4a9d0096f72a7f0,Enhance Visual Recognition under Adverse Conditions via Deep Networks,"Enhance Visual Recognition under Adverse
-Conditions via Deep Networks
-Ding Liu, Student Member, IEEE, Bowen Cheng, Zhangyang Wang, Member, IEEE,
-Haichao Zhang, Member, IEEE, and Thomas S. Huang, Life Fellow, IEEE"
 6b8a5a2d018356b396301b27156fd69dd18b1d82,A Study on the Impact of Wavelet Decomposition on Face Recognition Methods,"International Journal of Computer Applications (0975 – 8887)
 Volume 87 – No.3, February 2014
 A Study on the Impact of Wavelet Decomposition on
@@ -27396,18 +23396,6 @@ IEEE, 2011. 561 - 564
 Copyright:  © 2011 IEEE
 El acceso a la versión del editor puede requerir la suscripción del recurso
 Access to the published version may require subscription"
-e4e95b8bca585a15f13ef1ab4f48a884cd6ecfcc,Face Recognition with Independent Component Based Super-resolution,"Face Recognition with Independent Component Based
-Super-resolution
-Osman Gokhan Sezer†,a, Yucel Altunbasakb, Aytul Ercila
-Faculty of Engineering and Natural Sciences, Sabanci Univ., Istanbul, Turkiye, 34956
-School of Elec. and Comp. Eng. , Georgia Inst. of Tech., Atlanta, GA, USA, 30332-0250"
-e44d8409bb5233bd1822555bf85095a80e27fd49,Spatio-temporal interaction model for crowd video analysis,"Spatio-temporal interaction model for crowd video analysis
-Indian Institute of Technology Bombay
-Indian Institute of Technology Bombay
-Neha Bhargava
-India
-Subhasis Chaudhuri
-India"
 e4a5ff03ac258f1bcc9c214c30497610b3d5faa2,DropBlock: A regularization method for convolutional networks,"DropBlock: A regularization method for
 onvolutional networks
 Golnaz Ghiasi
@@ -27450,14 +23438,6 @@ Lu Yuan
 Microsoft Research Asia"
 e4d33362b4f99ab77fd6ceaafa183c087c79faea,Design and implementation of a high performance pedestrian detection,"June 23-26, 2013, Gold Coast, Australia
 978-1-4673-2754-1/13/$31.00 ©2013 Crown"
-e4bce7dabefaff6069fc0773773c80dbc4865005,Evaluation of Face Recognition using Principle Component Analysis and Two Dimensional Component Analysis,"Indian Journal of Advanced Communication Engineering
-Volume.1 Number.1 January – June 2013, pp.1-7
-Academic Research Journals, (India)
-Evaluation of Face Recognition using Principle Component
-Analysis and Two Dimensional Component Analysis
-Dr.G.M.Tamilselvan1, Dr. S. Valarmathy2, M.Brindha3 and M. Arun Kumar 4
-Department of ECE, Bannari Amman Institute of Technology, Sathyamangalam, India
-E-mails:"
 e475e857b2f5574eb626e7e01be47b416deff268,Facial Emotion Recognition Using Nonparametric Weighted Feature Extraction and Fuzzy Classifier,"Facial Emotion Recognition Using Nonparametric
 Weighted Feature Extraction and Fuzzy Classifier
 Maryam Imani and Gholam Ali Montazer"
@@ -27474,19 +23454,6 @@ Pascal Fua
 Computer Vision Laboratory, ´Ecole Polytechnique F´ed´erale de Lausanne
 {weizhe.liu, krzysztof.lis, mathieu.salzmann,
 (EPFL)"
-e4b9c14951cea6259dd9d522586ba2c5bb1fbcce,Social Image Captioning: Exploring Visual Attention and User Attention,"Article
-Social Image Captioning: Exploring Visual Attention
-nd User Attention
-Leiquan Wang 1 ID , Xiaoliang Chu 1, Weishan Zhang 1, Yiwei Wei 1, Weichen Sun 2,3
-nd Chunlei Wu 1,*
-College of Computer & Communication Engineering, China University of Petroleum (East China),
-Qingdao 266555, China; (L.W.); (X.C.);
-(W.Z.); (Y.W.)
-First Research Institute of the Ministry of Public Security of PRC, Beijing 100048, China;
-School of Information and Communication Engineering, Beijing University of Posts and
-Telecommunications, Beijing 100876, China
-* Correspondence:
-Received: 1 December 2017; Accepted: 12 February 2018; Published: 22 February 2018"
 e4cbe39daed8700a1d6f4a25a3a98645c4f231d0,A nonconvex formulation for low rank subspace clustering: algorithms and convergence analysis,"Comput Optim Appl (2018) 70:395–418
 https://doi.org/10.1007/s10589-018-0002-6
 A nonconvex formulation for low rank subspace
@@ -27517,27 +23484,9 @@ University of Augsburg
 uni-augsburg.de
 Dan Zecha
 University of Augsburg"
-e4a05b1a478a2aeb6c0b1a4a42f8bdb4f97122f6,Quality Fusion Rule for Face Recognition in Video,"Quality Fusion Rule for Face Recognition in Video
-Chao Wang, Yongping Li, and Xinyu Ao
-The center for Advanced Detection and Instrumentation, Shanghai Institute of Applied Physics,
-Chinese Academy of Science, 201800 Shanghai, China"
 e4d0e87d0bd6ead4ccd39fc5b6c62287560bac5b,Implicit video multi-emotion tagging by exploiting multi-expression relations,"Implicit Video Multi-Emotion Tagging by Exploiting Multi-Expression
 Relations
 Zhilei Liu, Shangfei Wang*, Zhaoyu Wang and Qiang Ji"
-e472ab9005af1beb1e0d4a11d83e552c89b4cec2,"An Integrated Approach to Robust Human Face Detection for Complicated Facial Expressions , Angles and Illuminations","European Journal of Scientific Research
-ISSN 1450-216X Vol.85 No.1 (2012), pp.123-144
-© EuroJournals Publishing, Inc. 2012
-http://www.europeanjournalofscientificresearch.com
-An Integrated Approach to Robust Human Face Detection for
-Complicated Facial Expressions, Angles and Illuminations
-M. Madhu
-Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya University, Kanchipuram, India
-Department of Electronics and Communication Engineering
-E-mail: Tel: +91-9944331257
-R. Amutha
-Department of Electronics and Communication Engineering
-SSN College of Engineering, Chennai, India
-E-mail:"
 e480f8c00dfe217653c2569d0eec6e2ffa836d59,The “Something Something” Video Database for Learning and Evaluating Visual Common Sense,"The “something something” video database
 for learning and evaluating visual common sense
 Raghav Goyal
@@ -27558,14 +23507,6 @@ e4896772d51a66b743e0d072d53cf26f6b61fc75,Automated Identification of Trampoline
 Using Computer Vision Extracted Pose Estimation
 Paul W. Connolly, Guenole C. Silvestre and Chris J. Bleakley
 School of Computer Science, University College Dublin, Belﬁeld, Dublin 4, Ireland."
-e478c322de923337627487d8a688f5922b45b2ff,Automatic Garage Door Opening Using License Plate Recognition and Fingerprint Verification,"International Journal of Innovative Research in Science, Engineering and Technology
-ISSN: 2319-8753
-Vol. 2, Issue 4, April 2013
-Automatic Garage Door Opening Using
-License Plate Recognition and Fingerprint
-Verification
-E. Gomathi, B. Kousalya
-Assistant Professor, Department of ECE, Karpagam College of Engineering, Coimbatore, India"
 e45bcda905b897513f4cff9e5c0a5bf475674a02,"Domain Stylization: A Strong, Simple Baseline for Synthetic to Real Image Domain Adaptation","Domain Stylization: A Strong, Simple Baseline for
 Synthetic to Real Image Domain Adaptation
 Aysegul Dundar, Ming-Yu Liu, Ting-Chun Wang, John Zedlewski, Jan Kautz
@@ -27593,12 +23534,6 @@ broad, or from public or private research centers.
 L’archive ouverte pluridisciplinaire HAL, est
 destin´ee au d´epˆot et `a la diffusion de documents
 scientiﬁques de niveau recherche, publi´es ou non,"
-e4a1b46b5c639d433d21b34b788df8d81b518729,Side Information for Face Completion: a Robust PCA Approach,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015
-Side Information for Face Completion: a Robust
-PCA Approach
-Niannan Xue, Student Member, IEEE, Jiankang Deng, Student Member,IEEE,
-Shiyang Cheng, Student Member,IEEE, Yannis Panagakis, Member,IEEE,
-nd Stefanos Zafeiriou, Member, IEEE"
 e496d6be415038de1636bbe8202cac9c1cea9dbe,Facial Expression Recognition in Older Adults using Deep Machine Learning,"Facial Expression Recognition in Older Adults using
 Deep Machine Learning
 Andrea Caroppo, Alessandro Leone and Pietro Siciliano
@@ -27610,12 +23545,6 @@ Department of Engineering ”Enzo Ferrari”
 University of Modena and Reggio Emilia, Italy
 Keywords:
 Head Detection, Head Localization, Depth Maps, Convolutional Neural Network"
-e41e1e4d9e578c29bf648e7098c466935b50f1a9,A Generative Model for Simultaneous Estimation of Human Body Shape and Pixel-Level Segmentation,"A Generative Model for Simultaneous
-Estimation of Human Body Shape and
-Pixel-level Segmentation
-Ingmar Rauschert and Robert T. Collins
-Pennsylvania State University,
-University Park, 16802 PA, USA"
 e4dc24e4926df4de3e8d7ca7cd1f4115e91f03e1,Instance-level video segmentation from object tracks Anonymous CVPR submission,"CVPR 2016 Submission #185. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE.
 Instance-level video segmentation from object tracks
 Anonymous CVPR submission
@@ -27667,12 +23596,6 @@ Full Terms & Conditions of access and use can be found at
 http://www.tandfonline.com/action/journalInformation?journalCode=pcem20
 Download by: [Vrije Universiteit Amsterdam]
 Date: 04 April 2016, At: 13:19"
-e4bf70e818e507b54f7d94856fecc42cc9e0f73d,FACE RECOGNITION UNDER VARYING BLUR IN AN UNCONSTRAINED ENVIRONMENT,"IJRET: International Journal of Research in Engineering and Technology        eISSN: 2319-1163 | pISSN: 2321-7308
-FACE RECOGNITION UNDER VARYING BLUR IN AN
-UNCONSTRAINED ENVIRONMENT
-Anubha Pearline.S1, Hemalatha.M2
-M.Tech, Information Technology,Madras Institute of Technology, TamilNadu,India,
-Assistant Professor, Information Technology,Madras Institute of Technology, TamilNadu,India, email:,"
 e4d8ba577cabcb67b4e9e1260573aea708574886,Um Sistema De Recomendaç˜ao Inteligente Baseado Em V ´ Idio Aulas Para Educaç˜ao a Distˆancia an Intelligent Recommendation System Based on Video Lectures for Distance Education (revelation),"UM SISTEMA DE RECOMENDAC¸ ˜AO INTELIGENTE BASEADO EM V´IDIO
 AULAS PARA EDUCAC¸ ˜AO A DIST ˆANCIA
 Gaspare Giuliano Elias Bruno
@@ -27744,13 +23667,6 @@ s a Guide for Facial Feature Extraction
 Nozomi Nakao, Wataru Ohyama, Tetsushi Wakabayashi and Fumitaka Kimura
 Graduate School of Engineering, Mie University
 577 Kurimamachiya-cho, Tsu-shi, Mie, 5148507, Japan"
-eea9994c71831219aacd537f5f4ab8a91110a7e2,Optimizing the Trade-off between Single-Stage and Two-Stage Object Detectors using Image Difficulty Prediction,"Optimizing the Trade-off between
-Single-Stage and Two-Stage Deep Object Detectors
-using Image Difﬁculty Prediction
-Petru Soviany, Radu Tudor Ionescu
-Department of Computer Science
-University of Bucharest, Romania
-E-mails:"
 eee8a37a12506ff5df72c402ccc3d59216321346,Volume C,"Uredniki:
 dr. Tomaž Erjavec
 Odsek za tehnologije znanja
@@ -27771,34 +23687,15 @@ Informacijska družba
 ISSN 1581-9973
 CIP - Kataložni zapis o publikaciji
 Narodna in univerzitetna knjižnica, Ljubljana"
-eea77e2a891e49e65d4bed54c1b24411f33203a3,Exploring Guide Context in City Scenario Using Color and Gradient Features,"The Open Construction and Building Technology Journal, 2015, 9, 177-181
-Open Access
-Exploring  Guide  Context  in  City  Scenario  Using  Color  and  Gradient
-Features
-Send Orders for Reprints to
-Zhuo Bian*
-Art Academy of Northeast Agriculture University, Harbin 150001, China"
 ee9385efb66ee0b1bee31c1632141729bb7fb6f5,Numerical simplification for bloat control and analysis of building blocks in genetic programming,"Noname manuscript No.
 (will be inserted by the editor)
 Numerical Simpliﬁcation for Bloat Control and Analysis of
 Building Blocks in Genetic Programming
 David Kinzett · Mark Johnston · Mengjie Zhang
 the date of receipt and acceptance should be inserted later"
-eee69704bde40ab20090c19a21487f7ca5bcc674,On the Effect of Perspective Distortions in Face Recognition,"ON THE EFFECT OF PERSPECTIVE DISTORTIONS
-IN FACE RECOGNITION
-Zahid Riaz and Michael Beetz
-Intelligent Autonomous Systems (IAS), Department of Computer Science,
-Technical University of Munich, Munich, Germany
-Keywords:
-Face Recognition, Active Appearance Models, Feature Extraction, Biometrics."
 eeec69e910430bebe3808773f5a6a155d77059a0,Multi-shot Pedestrian Re-identification via Sequential Decision Making,"Multi-shot Pedestrian Re-identiﬁcation via Sequential Decision Making
 Jianfu Zhang1, Naiyan Wang2 and Liqing Zhang1
 Shanghai Jiao Tong University∗, 2TuSimple"
-ee335fb785c332b1ac43565b007461002616f1e0,Processing Large Amounts of Images on Hadoop with OpenCV,"Processing Large Amounts of Images
-on Hadoop with OpenCV
-Timofei Epanchintsev1,2 and Andrey Sozykin1,2
-IMM UB RAS, Yekaterinburg, Russia,
-Ural Federal University, Yekaterinburg, Russia"
 eed1dd2a5959647896e73d129272cb7c3a2e145c,The Elements of Fashion Style,"INPUTSTYLE DOCUMENTTOP ITEMS“             ”I need an outﬁt for a beach wedding that I'm going to early this summer. I'm so excited -- it's going to be warm and exotic and tropical... I want my outﬁt to look effortless, breezy, flowy, like I’m floating over the sand! Oh, and obviously no white! For a tropical spot, I think my outﬁt should be bright and"
 eedfb384a5e42511013b33104f4cd3149432bd9e,Multimodal probabilistic person tracking and identification in smart spaces,"Multimodal Probabilistic Person
 Tracking and Identiﬁcation
@@ -27839,14 +23736,6 @@ Dr. Marco Loog
 Dr. Silvia-Laura Pintea
 Dr. Adriana Gonzalez
 Eindhoven, Aug 2017"
-ee53c9480132fc0d09b1192226cb2c460462fd6d,Channel Pruning for Accelerating Very Deep Neural Networks,"Channel Pruning for Accelerating Very Deep Neural Networks
-Yihui He*
-Xi’an Jiaotong University
-Xi’an, 710049, China"
-ee8d2256ac99799677a5bd88bb1a12973bd245df,Depth Pooling Based Large-Scale 3-D Action Recognition With Convolutional Neural Networks,"Depth Pooling Based Large-scale 3D Action
-Recognition with Convolutional Neural Networks
-Pichao Wang, Member, IEEE, Wanqing Li, Senior Member, IEEE,
-Zhimin Gao, Chang Tang, and Philip Ogunbona, Senior Member, IEEE,"
 eed98eb53b34820df736203d62076eff81de926e,Scene Segmentation and Object Classification for Place Recognition,"Dr. Mongi A. Abidi,  Major Professor
 To the Graduate Council:
 I  am  submitting  herewith  a  dissertation    written  by  Chang  Cheng  entitled  “Scene
@@ -28016,26 +23905,6 @@ Dr. Gabriel Dichter
 Dr. Kevin LaBar
 Dr. Joseph Piven
 Dr. Aldo Rustioni"
-784cc0363d44bf09f3f636abd1a532ddac95ca13,Group-level emotion recognition using transfer learning from face identification,"Group-level Emotion Recognition using Transfer Learning from
-Face Identification
-Alexandr Rassadin
-Alexey Gruzdev
-Andrey Savchenko
-National Research University Higher
-National Research University Higher
-National Research University Higher
-School of Economics
-Laboratory of Algorithms and
-Technologies for Network Analysis,
-School of Economics
-Nizhny Novgorod
-Russia
-School of Economics
-Laboratory of Algorithms and
-Technologies for Network Analysis,
-Nizhny Novgorod
-Russia
-Nizhny Novgorod"
 78df7d3fdd5c32f037fb5cc2a7c104ac1743d74e,Temporal Pyramid Pooling-Based Convolutional Neural Network for Action Recognition,"TEMPORAL PYRAMID POOLING CNN FOR ACTION RECOGNITION
 Temporal Pyramid Pooling Based Convolutional
 Neural Network for Action Recognition
@@ -28069,10 +23938,6 @@ Chi-Hao Wu, Qin Huang, Siyang Li, and C.-C. Jay Kuo, Fellow, IEEE"
 78fdf2b98cf6380623b0e20b0005a452e736181e,Dense Wide-Baseline Stereo with Varying Illumination and its Application to Face Recognition,
 78c9a63be8e07dc6acb90f4fe3f06821719eaa34,Hierarchical online domain adaptation of deformable part-based models,"Hierarchical online domain adaptation of deformable part-based models
 Jiaolong Xu1, David V´azquez2, Krystian Mikolajczyk3 and Antonio M. L´opez1"
-78e00cfe5f0bd4bbb3d4111fa11de9e6dda17afc,Multimodal Task-Driven Dictionary Learning for Image Classification,"Multimodal Task-Driven Dictionary Learning
-for Image Classiﬁcation
-Soheil Bahrampour, Member, IEEE, Nasser M. Nasrabadi, Fellow, IEEE, Asok Ray, Fellow, IEEE,
-nd W. Kenneth Jenkins, Life Fellow, IEEE"
 788a3faa14ca191d7f187b812047190a70798428,Interpretable Set Functions,"Interpretable Set Functions
 Andrew Cotter, Maya Gupta, Heinrich Jiang,
 James Muller, Taman Narayan, Serena Wang, Tao Zhu
@@ -28080,18 +23945,6 @@ James Muller, Taman Narayan, Serena Wang, Tao Zhu
 Google Research"
 7882c67f555b761e10ecc70216db25382890d9d7,Automated Characterization of Stenosis in Invasive Coronary Angiography Images with Convolutional Neural Networks,"Automated Characterization of Stenosis in Invasive Coronary Angiography Images with Convolutional
 Neural Networks"
-787303db8e707feee2fa2b93dfc46e3d3cc244cd,Defocus Blur Parameter Estimation Technique,"International Journal of Electronics and Communication Engineering and Technology (IJECET)
-Volume 7, Issue 4, July-August 2016, pp. 85–90, Article ID: IJECET_07_04_010
-Available online at
-http://www.iaeme.com/IJECET/issues.asp?JType=IJECET&VType=7&IType=4
-Journal Impact Factor (2016): 8.2691 (Calculated by GISI) www.jifactor.com
-ISSN Print: 0976-6464 and ISSN Online: 0976-6472
-© IAEME Publication
-DEFOCUS BLUR PARAMETER ESTIMATION
-TECHNIQUE
-Ruchi Gajjar, Aditi Pathak and Tanish Zaveri
-Electronics and Communication Engineering Department
-Institute of Technology, Nirma University, Ahmedabad, Gujarat, India"
 78749b58299ecebf100e2512872029f89878449b,One-class Selective Transfer Machine for Personalized Anomalous Facial Expression Detection,
 782188821963304fb78791e01665590f0cd869e8,Automatic Spatially-Aware Fashion Concept Discovery,"sleevelengthincreasing dress length+ mini =(b) Structured product browsing(c) Attribute-feedback product retrieval(a) Concept discoveryminimidimaxisleevelessshort-sleevelong-sleeveblueblackredyellowFigure1.(a)Weproposeaconceptdiscoveryapproachtoauto-maticallyclusterspatially-awareattributesintomeaningfulcon-cepts.Thediscoveredspatially-awareconceptsarefurtherutilizedfor(b)structuredproductbrowsing(visualizingimagesaccordingtoselectedconcepts)and(c)attribute-feedbackproductretrieval(reﬁningsearchresultsbyprovidingadesiredattribute).variousfeedback,includingtherelevanceofdisplayedim-ages[20,4],ortuningparameterslikecolorandtexture,andthenresultsareupdatedcorrespondingly.However,rel-evancefeedbackislimitedduetoitsslowconvergencetomeetthecustomerrequirements.Inadditiontocolorandtexture,customersoftenwishtoexploithigher-levelfea-tures,suchasneckline,sleevelength,dresslength,etc.Semanticattributes[13],whichhavebeenappliedef-fectivelytoobjectcategorization[15,27]andﬁne-grainedrecognition[12]couldpotentiallyaddresssuchchallenges.Theyaremid-levelrepresentationsthatdescribesemanticproperties.Recently,researchershaveannotatedclotheswithsemanticattributes[9,2,8,16,11](e.g.,material,pat-tern)asintermediaterepresentationsorsupervisorysignalstobridgethesemanticgap.However,annotatingsemanticattributesiscostly.Further,attributesconditionedonob-jectpartshaveachievedgoodperformanceinﬁne-grainedrecognition[3,33],conﬁrmingthatspatialinformationiscriticalforattributes.Thisalsoholdsforclothingimages.Forexample,thenecklineattributeusuallycorrespondstothetoppartinimageswhilethesleeveattributeordinarily1"
 78f7304ba4c853c568dc4e38fef35aa2c003e3f3,Modeling correlations in spontaneous activity of visual cortex with centered Gaussian-binary deep Boltzmann machines.,"visual cortex with centered Gaussian-binary deep
@@ -28108,10 +23961,6 @@ Laurenz Wiskott
 Institut f¨ur Neuroinformatik
 Ruhr-Universit¨at Bochum
 Bochum, 44780, Germany"
-78a85785150b2b80eca826ba9afc05005184a7c3,Optical Flow Super-Resolution Based on Image Guidence Using Convolutional Neural Network,"Optical Flow Super-Resolution Based on Image
-Guidence Using Convolutional Neural Network
-Liping Zhang, Zongqing Lu∗, Qingmin Liao
-Graduate School at Shenzhen, Tsinghua University Shenzhen, China"
 78a144d5dce1a61c92420e77c11116f541a7617f,Box Aggregation for Proposal Decimation: Last Mile of Object Detection,"Box Aggregation for Proposal Decimation: Last Mile of Object Detection
 The Chinese University of Hong Kong ♯Stanford University ‡Shanghai Jiao Tong University
 Shu Liu† Cewu Lu♯,‡
@@ -28133,20 +23982,6 @@ Arman Savran
 Electrical and Electronics Engineering Department
 Bo˘gazic¸i University, Istanbul, Turkey
 B¨ulent Sankur"
-7809a42a833b49725f3a4bb8f70f63f4d2cee11c,Detection of Person in A Group of People Using 3-D Based Model,"Detection of Person in A Group of People Using 3-D Based Model
-Dr. P. Srirama Chandra Murty1, Ch. Anuradha2, Dr. Syed Muneer3
-Assistant Professor, Dept. of  Computer Science and Engineering, ANUCET, Acharya Nagarjuna
-University, Guntur, India
-Asst. Professor, Dept. of Computer Science and Engineering, PNC & Vijay Institute of Engineering
-Computer Professional, Dept. of Computer Science and Engineering, ANUCET, Acharya Nagarjuna
-nd Technology, Guntur, Andhra Pradesh, India.
-University, Guntur, Andhra Pradesh, India"
-78342d17c6c6fff00cf1b20602f3213a3f61ba56,Collaborative Discriminant Locality Preserving Projections With its Application to Face Recognition,"Collaborative Discriminant Locality Preserving Projections With its Application
-to Face Recognition
-Sheng Huanga,c, Dan Yanga,b,∗, Dong Yangc, Ahmed Elgammalc
-College of Computer Science at Chongqing University, Chonqing, 400044, China
-School of Software Engineering at Chongqing University Chonqing, 400044, China
-Department of Computer Science at Rutgers University, Piscataway, NJ, 08854, USA"
 78d00241fc9798eba895d41a0068715212a70489,Person identification from gait analysis with a depth camera at home,978-1-4244-9270-1/15/$31.00 ©2015 IEEE
 781c2553c4ed2a3147bbf78ad57ef9d0aeb6c7ed,Tubelets: Unsupervised Action Proposals from Spatiotemporal Super-Voxels,"Int J Comput Vis
 DOI 10.1007/s11263-017-1023-9
@@ -28215,24 +24050,6 @@ Asturias, Spain; (R.U.); (R.C.)
 * Corrospondence: Tel.: +34-984-29-12-12; Fax: +34-984-39-06-12
 Academic Editor: Gonzalo Pajares Martinsanz
 Received: 14 July 2016; Accepted: 24 October 2016; Published: 28 October 2016"
-4991dcef497ddd7ea115663985a9e0635494a95d,Detecting Group Activities With Multi-Camera Context,"Detecting Group Activities With
-Multi-Camera Context
-Zheng-Jun Zha, Member, IEEE, Hanwang Zhang, Meng Wang, Member, IEEE, Huanbo Luan, and Tat-Seng Chua"
-49b349021c958772926851ee7b704c8839977e28,Face Recognition by Using Distance Classifier Based On PCA and LDA,"ISSN (Online)  : 2319 - 8753
-ISSN (Print)    : 2347 - 6710
-International Journal of Innovative Research in Science, Engineering and Technology
-2014 International Conference on Innovations in Engineering and Technology (ICIET’14)
-Volume 3, Special Issue 3, March 2014
-On 21st & 22nd March Organized by
-K.L.N. College of Engineering, Madurai, Tamil Nadu, India
-Face Recognition by Using Distance Classifier
-Based On PCA and LDA
-Gayathri.S#1, Mary Jeya priya.R#2, Dr.Valarmathy.S *3
-#1 P.G Scholar, Department of Electronics and Communication, Bannari Amman Institute of Technology,
-#2 P.G Scholar, Department of Electronics and Communication, Bannari Amman Institute of Technology,
-Sathyamangalam, Tamilnadu, India.
-Sathyamangalam, Tamilnadu, India.
-*3Bannari Amman Institute of Technology, Sathyamangalam, , Tamilnadu, India."
 49004f22a420e0897f7b811239c1e098b0c655bf,Out of the Box: Reasoning with Graph Convolution Nets for Factual Visual Question Answering,"Out of the Box: Reasoning with Graph Convolution
 Nets for Factual Visual Question Answering
 Medhini Narasimhan, Svetlana Lazebnik, Alexander G. Schwing
@@ -28358,15 +24175,6 @@ Yu-Wing Tai
 Tencent
 Chi-Keung Tang
 HKUST"
-49b3f6d8712c01f315686b6b8541eda8c5ee428a,Virtual friend or threat? The effects of facial expression and gaze interaction on psychophysiological responses and emotional experience.,"Copyright r 2009 Society for Psychophysiological Research
-DOI: 10.1111/j.1469-8986.2009.00831.x
-Virtual friend or threat? The effects of facial expression
-nd gaze interaction on psychophysiological responses
-nd emotional experience
-FRANZISKA SCHRAMMEL,a SEBASTIAN PANNASCH,a SVEN-THOMAS GRAUPNER,a
-ANDREAS MOJZISCH,b and BORIS M. VELICHKOVSKYa
-Institute for Psychology III, Technische Universitaet Dresden, Germany
-Institute for Psychology, Georg-August-University Goettingen, Germany"
 490a0b6ff5b982e884622bb9c81250f05c069f32,Template Aging in 3 D and 2 D Face Recognition,"Template Aging in 3D and 2D Face Recognition
 Ishan Manjani∗
 Hakki Sumerkan†
@@ -28414,13 +24222,6 @@ neodvisnih komponent, zanesljivost razpoznavanja, kakovost vhodnih slik
 Impact of image degradations on the face recognition accuracy"
 49e85869fa2cbb31e2fd761951d0cdfa741d95f3,Adaptive Manifold Learning,"Adaptive Manifold Learning
 Zhenyue Zhang, Jing Wang, and Hongyuan Zha"
-4980511ea7ac286b7fff0456216425287bc9a083,Automatic Image Annotation Using Modified Keywords Transfer Mechanism Base on Image-Keyword Graph,"Automatic Image Annotation Using Modified Keywords Transfer
-Mechanism Base on Image-Keyword Graph
-Guo-Qing Xu1, Zhi-Chun Mu2
-1 School of Automation and Electrical Engineering, University of Science and Technology Beijing
-School of Automation and Electrical Engineering, University of Science and Technology Beijing
-Beijing, 100083, China
-Beijing, 100083, China"
 493abaf881c3a6e9d3bf47a8d6e75abb4e75f557,Introspective Evaluation of Perception Performance for Parameter Tuning without Ground Truth,"Introspective Evaluation of Perception Performance for Parameter Tuning
 without Ground Truth
 Humphrey Hu† and George Kantor†"
@@ -28441,11 +24242,6 @@ Computer Vision Group
 June 9, 2017
 M.Sc. John Chiotellis: Metric Learning
 / 46"
-49f22f29e57f5867b47348555136844ffa6c6603,Beyond Lesion-Based Diabetic Retinopathy: A Direct Approach for Referral,"JOURNAL OF LATEX CLASS FILES, VOL. 11, NO. 4, DECEMBER 2012
-Beyond Lesion-based Diabetic Retinopathy:
-Direct Approach for Referral
-Ramon Pires, Member, IEEE, Sandra Avila, Member, IEEE, Herbert F. Jelinek, Member, IEEE,
-Jacques Wainer, Eduardo Valle, and Anderson Rocha, Senior Member, IEEE"
 4987ac5638e1fdb116cc76626465f166998d7536,Polysemous codes.,"Polysemous codes
 Matthijs Douze, Herv´e J´egou and Florent Perronnin
 Facebook AI Research"
@@ -28480,10 +24276,6 @@ Generic and attribute-specific deep
 representations for maritime vessels
 Berkan Solmaz*†
 , Erhan Gundogdu†, Veysel Yucesoy and Aykut Koc"
-23a8dc98eb38039f032d77a209751b25d3106c4b,Memory Efficient Max Flow for Multi-label Submodular MRFs,"Memory Efﬁcient Max Flow for Multi-label
-Submodular MRFs
-Thalaiyasingam Ajanthan, Student Member, IEEE, Richard Hartley, Fellow, IEEE,
-nd Mathieu Salzmann, Member, IEEE"
 2322ec2f3571e0ddc593c4e2237a6a794c61251d,Four not six: Revealing culturally common facial expressions of emotion.,"Jack, R. E. , Sun, W., Delis, I., Garrod, O. G. B. and Schyns, P. G. (2016)
 Four not six: revealing culturally common facial expressions of
 emotion.Journal of Experimental Psychology: General, 145(6), pp. 708-
@@ -28519,10 +24311,6 @@ Institut de Police Scientiﬁque, E´ cole des Sciences Criminelles, Universite�
 Speech Processing and Biometrics Group, Signal Processing Institute, E´ cole Polytechnique Fe´de´rale de Lausanne, Switzerland
 Received 9 June 2006; accepted 14 June 2006
 Available online 4 August 2006"
-236942bb64f1711b4763424b2f795fb518c9d8d4,Optimizing LBP Structure For Visual Recognition Using Binary Quadratic Programming,"Optimizing LBP Structure For Visual Recognition
-Using Binary Quadratic Programming
-Jianfeng Ren, Student Member, IEEE, Xudong Jiang, Senior Member, IEEE, Junsong Yuan, Senior Member, IEEE,
-nd Gang Wang, Member, IEEE"
 239df42479c69cf95e7194cc0ec3d8cf7d4a98e8,Face Detection and Extraction from Low Resolution Surveillance Video Using Motion Segmentation,"Face Detection and Extraction from Low
 Resolution Surveillance Video Using
 Motion Segmentation
@@ -28583,10 +24371,6 @@ Jack Terwilliger, Julia Kindelsberger, Li Ding, Sean Seaman, Hillary Abraham, Al
 Ming-Hsuan Yang
 Honda Fundamental Research Labs
 Mountain View, CA 94041"
-236a4f38f79a4dcc2183e99b568f472cf45d27f4,Randomized Clustering Forests for Image Classification,"Randomized Clustering Forests
-for Image Classification
-Frank Moosmann, Student Member, IEEE, Eric Nowak, Student Member, IEEE, and
-Frederic Jurie, Member, IEEE Computer Society"
 2312bc2d48a0f68bd5ab1b024d5726786455da3a,Learning Deep Context-Aware Features over Body and Latent Parts for Person Re-identification,"Learning Deep Context-aware Features over Body and Latent Parts
 for Person Re-identiﬁcation
 Supplementary Materials
@@ -28609,35 +24393,11 @@ including detected and manually annotated. In this paragraph, we show the overal
 results to approximate the single-shot results. The DGD [6] is trained using multiple datasets. In this paper, we use the"
 23172f9a397f13ae1ecb5793efd81b6aba9b4537,Defining Visually Descriptive Language,"Proceedings of the 2015 Workshop on Vision and Language (VL’15), pages 10–17,
 Lisbon, Portugal, 18 September 2015. c(cid:13)2015 Association for Computational Linguistics."
-237734e3fd3abab005b0b97d61416ee16105f902,Consensus Maximization for Semantic Region Correspondences,"Consensus Maximization for Semantic Region Correspondences
-Pablo Speciale1, Danda P. Paudel2, Martin R. Oswald1,
-Hayko Riemenschneider2, Luc V. Gool2,4, and Marc Pollefeys1,3
-Department of Computer Science, ETH Z¨urich.
-Microsoft, Redmond, USA
-{pablo, moswald,
-Computer Vision Laboratory, D-ITET, ETH Z¨urich
-VISICS, ESAT/PSI, KU Leuven, Belgium
-{paudel, hayko,
-Day / Night
-Registration
-Outdoor / Indoor
-Registration
-Scan / CAD
-Registration
-Figure 1: Example registration results. Our approach solves challenging registration problems by maximizing the number of corre-
-sponding semantic regions – such as windows, doors or balconies – for datasets from different modalities, with large amounts of noise and
-outliers, little data overlap, or signiﬁcantly different data statistics."
 23e881c9b791fd17e248b1fb4fc980710dd005d7,An Unbiased Temporal Representation for Video-Based Person Re-Identification,"AN UNBIASED TEMPORAL REPRESENTATION FOR VIDEO-BASED PERSON
 RE-IDENTIFICATION
 Xiu Zhang and Bir Bhanu
 Center for Research in Intelligent Systems
 University of California, Riverside, Riverside, CA 92521, USA"
-239c06cd437832faa55a8e7292c50e45229a3d7c,Generating analytic insights on human behavior using image processing,"Generating Analytic Insights on Human behavior
-using Image Processing
-Namit Juneja, Rajesh Kumar M, Senior Member, IEEE
-School of Electronics Engineering
-VIT University
-Vellore, India"
 23ea8a34570342855611a78a4ff00ddd902e6123,Gradient-based global features and its application to image retargeting,"Gradient-based Global Features and Its Application
 to Image Retargeting
 Izumi Ito
@@ -28645,10 +24405,6 @@ Tokyo Institute of Technology Tokyo, 152-8552 Japan
 +81-3-5734-2997"
 23cb53fd272c105e98111e66502120216ae1788c,Incremental learning for robot perception through HRI,"Incremental Learning for Robot Perception through HRI
 Sepehr Valipour∗, Camilo Perez∗ and Martin Jagersand"
-23fa51635c646aa621bb18ff76f31d5e48ac969b,MFSC: A new shape descriptor with robustness to deformations,"MFSC: A NEW SHAPE DESCRIPTOR WITH ROBUSTNESS TO DEFORMATIONS
-Lunshao Chaia, Zhen Qinb, Honggang Zhanga, Jun Guoa, Bir Bhanub
-Beijing University of Posts and Telecomuunictions, Beijing, 100876, China
-University of California at Riverside, Riverside, CA 92521, USA"
 2333cf918f50ac2ae201a837166d310adf3a00b0,Optimally Training a Cascade Classifier,"Optimally Training a Cascade Classiﬁer
 Chunhua Shen, Peng Wang, and Anton van den Hengel"
 23e0571fd42347ca2bdf424b8562c6c6f72b88fc,Classification of Things in DBpedia using Deep Neural Networks,"International Journal of Web & Semantic Technology (IJWesT) Vol.9, No.1, January 2018
@@ -28712,47 +24468,10 @@ Computer Vision Laboratory
 ETH Zurich
 ESAT-PSI / IBBT
 KU Leuven"
-238fc68b2e0ef9f5ec043d081451902573992a03,Enhanced Local Gradient Order Features and Discriminant Analysis for Face Recognition,"Enhanced Local Gradient Order Features and
-Discriminant Analysis for Face Recognition
-Chuan-Xian Ren, Zhen Lei, Member, IEEE, Dao-Qing Dai, Member, IEEE, and Stan Z. Li, Fellow, IEEE
-role in robust face recognition [5]. Many algorithms have
-een proposed to deal with the effectiveness of feature design
-nd extraction [6], [7]; however, the performance of many
-existing methods is still highly sensitive to variations of
-imaging conditions, such as outdoor illumination, exaggerated
-expression, and continuous occlusion. These complex varia-
-tions are signiﬁcantly affecting the recognition accuracy in
-recent years [8]–[10].
-Appearance-based subspace learning is one of the sim-
-plest approach for feature extraction, and many methods
-re usually based on linear correlation of pixel intensities.
-For example, Eigenface [11] uses eigen system of pixel
-intensities to estimate the lower rank linear subspace of
-set of training face images by minimizing the (cid:2)2 dis-
-tance metric. The solution enjoys optimality properties when
-noise is independent
-identically distributed Gaussian only."
-23b37c2f803a2d4b701e2f39c5f623b2f3e14d8e,Modified Approaches on Face Recognition By using Multisensory Image,"Available Online at www.ijcsmc.com
-International Journal of Computer Science and Mobile Computing
-A Monthly Journal of Computer Science and Information Technology
-ISSN 2320–088X
-IJCSMC, Vol. 2, Issue. 4, April 2013, pg.646 – 649
-RESEARCH ARTICLE
-Modified Approaches on Face Recognition
-By using Multisensory Image
-S. Dhanarajan1, G. Michael2
-Computer Science Department, Bharath University, India
-Computer Science Department, Bharath University, India"
 23943197f4124aa6c5a263bf2042169c9b816906,Crafting GBD-Net for Object Detection,"MANUSCRIPT
 Crafting GBD-Net for Object Detection
 Xingyu Zeng*,Wanli Ouyang*,Junjie Yan, Hongsheng Li,Tong Xiao, Kun Wang, Yu Liu, Yucong Zhou, Bin
 Yang, Zhe Wang,Hui Zhou, Xiaogang Wang,"
-23c9fe37fa0474967be4cc6c7a310dcc87b86b72,Spatial Feature Interdependence Matrix (SFIM): A Robust Descriptor for Face Recognition,"Spatial Feature Interdependence Matrix (SFIM):
-A Robust Descriptor for Face Recognition
-Anbang Yao1 and Shan Yu2
-National Laboratory of Pattern Recognition, Institute of Automation,
-Chinese Academy of Science, Beijing, 100090, China
-National Institute for Research in Computer Science and Control, France"
 231a12de5dedddf1184ae9caafbc4a954ce584c3,Closed and Open World Multi-shot Person Re-identification. (Ré-identification de personnes à partir de multiples images dans le cadre de bases d'identités fermées et ouvertes),"Closed and Open World Multi-shot Person
 Re-identification
 Solène Chan-Lang
@@ -28773,9 +24492,6 @@ L’archive ouverte pluridisciplinaire HAL, est
 destinée au dépôt et à la diffusion de documents
 scientifiques de niveau recherche, publiés ou non,
 émanant des établissements d’enseignement et de"
-2340a8fa6d90741c53e659cd1e7ca86ff900aa55,Body Parts Dependent Joint Regressors for Human Pose Estimation in Still Images,"Body Parts Dependent Joint Regressors for
-Human Pose Estimation in Still Images
-Matthias Dantone, Juergen Gall, Member, IEEE Christian Leistner, and Luc Van Gool, Member, IEEE"
 2349eab05cd0c6f94ba5314c037d198aa12c2f0f,Eigen-profiles of spatio-temporal fragments for adaptive region-based tracking,"978-1-4673-0046-9/12/$26.00 ©2012 IEEE
 ICASSP 2012"
 237316762470d72a02795a7f57de9279e9cda16a,Dimensionality-reduced subspace clustering,"Dimensionality-reduced subspace clustering
@@ -28977,52 +24693,6 @@ Technische Universit¨at Ilmenau
 Die Dissertation wurde am 16.06.2009 bei der Technischen Universit¨at M¨unchen einge-
 reicht und durch die Fakult¨at f¨ur Elektrotechnik und Informationstechnik am 30.10.2009
 ngenommen."
-f113aed343bcac1021dc3e57ba6cc0647a8f5ce1,A Survey on Mining of Weakly Labeled Web Facial Images and Annotation,"International Journal of Science and Research (IJSR)
-ISSN (Online): 2319-7064
-Index Copernicus Value (2013): 6.14 | Impact Factor (2014): 5.611
-A Survey on Mining of Weakly Labeled Web Facial
-Images and Annotation
-Tarang Boharupi1, Pranjali Joshi2
-Pune Institute of Computer Technology, Pune, India
-Professor, Pune Institute of Computer Technology, Pune, India
-the  proposed  system  which"
-f1c76d97caa6f882764c1382c622a2dfb6aade43,CoreRank: Redeeming “Sick Silicon” by Dynamically Quantifying Core-Level Healthy Condition,"CoreRank: Redeeming “Sick Silicon”
-y Dynamically Quantifying Core-Level
-Healthy Condition
-Guihai Yan, Member, IEEE, Faqiang Sun, Huawei Li, Senior Member, IEEE, and
-Xiaowei Li, Senior Member, IEEE"
-f1ec3752535e0aa6aafe3930974a22250e652ca1,Gender and emotion recognition with implicit user signals,"Gender and Emotion Recognition with Implicit User Signals
-Maneesh Bilalpur
-International Institute of Information
-Technology
-Hyderabad, India
-Seyed Mostafa Kia
-Donders Institute, Radboud
-University
-Nijmegen, Netherlands
-Manisha Chawla
-Centre for Cognitive Science, Indian
-Institute of Technology
-Gandhinagar, India
-Tat-Seng Chua
-School of Computing, National
-University of Singapore
-Singapore
-Ramanathan Subramanian
-University of Glasgow & Advanced
-Digital Sciences Center"
-f1471a408369689e2fc956b417dce24e47557a38,A Novel Face Template Protection Algorithm Based on the Fusion of Chaos Theory and RSA Encryption,"International Journal of Security and Its Applications
-Vol. 10, No. 6 (2016) pp.315-330
-http://dx.doi.org/10.14257/ijsia.2016.10.6.30
-A Novel Face Template Protection Algorithm Based on the Fusion
-of Chaos Theory and RSA Encryption
-Liu Yunan1, Zhao Fudong2, Xu Yanli3 and Cao Yu2*
-.School of Foreign Languages, Harbin University of Science and Technology,
-Harbin, 150080, China
-.School of Automation, Harbin University of Science and Technology, Harbin,
-50080, China
-.School of Foreign Languages, Northeast Forestry University, Harbin, 150040,
-China"
 f1498ba94d64ee221e27b658bcd407c160cf0897,LS-VO: Learning Dense Optical Subspace for Robust Visual Odometry Estimation,"LS-VO: Learning Dense Optical Subspace for Robust Visual Odometry
 Estimation
 Gabriele Costante†,1 and Thomas A. Ciarfuglia†,1"
@@ -29100,25 +24770,6 @@ f1d8c377093ecf64afd7f17383738e81666fe5ae,Remote Detection of Idling Cars Using I
 Remote Detection of Idling Cars Using Infrared Imaging and Deep Networks
 Muhammet Bastan · Kim-Hui Yap · Lap-Pui Chau
 Date: April 2018"
-f19527b2ceabf50831e78ac04161107c936efb2b,Discriminative Sparse Neighbor Approximation for Imbalanced Learning,"Discriminative Sparse Neighbor Approximation
-for Imbalanced Learning
-Chen Huang, Chen Change Loy, Member, IEEE, and Xiaoou Tang, Fellow, IEEE"
-56fcc0ef7c10ff322626fec29f532af1860ff2f7,Occlusion and Abandoned Object Detection for Surveillance Applications,"International Journal of Computer Applications Technology and Research
-Volume 2– Issue 6, 708 - 713, 2013, ISSN:  2319–8656
-Occlusion and Abandoned Object Detection for
-Surveillance Applications
-M. Chitra
-RVS college of Engineering
-nd Technology
-Karaikal, India
-M.Kalaiselvi Geetha
-Annamalai University
-Chidambaram, India
-L.Menaka
-RVS college of Engineering
-nd Technology
-Karaikal, India
-is  challenging  and"
 568727a76dc1242e3d48392f9c19678a27c63482,High Entropy Ensembles for Holistic Figure-ground Segmentation,"GALLO et al.: HEE FOR HOLISTIC FIGURE-GROUND SEGMENTATION
 High Entropy Ensembles for Holistic
 Figure-ground Segmentation
@@ -29132,23 +24783,6 @@ Department of Theoretical and Applied
 Science
 University of Insubria
 Varese, Italy"
-56f5a94047966eac4b2f97ded4b50513f9a09951,Is the Kidney Donor Risk Index a Useful Tool in Non-US Patients?,"791148 CJKXXX10.1177/2054358118791148Canadian Journal of Kidney Health and DiseaseYoung et al
-research-article20182018
-Original Research Article
-Is the Kidney Donor Risk Index a
-Useful Tool in Non-US Patients?
-Ann Young1, Greg A. Knoll2,3, Eric McArthur2,
-Stephanie N. Dixon2,4, Amit X. Garg2,5,
-Charmaine E. Lok1,2,6, Ngan N. Lam7, and S. Joseph Kim1,2,6,8
-Canadian Journal of Kidney Health
-nd Disease
-Volume 5: 1 –10
-© The Author(s) 2018
-Reprints and permissions:
-sagepub.com/journals-permissions
-DOI: 10.1177/2054358118791148
-https://doi.org/10.1177/2054358118791148
-journals.sagepub.com/home/cjk"
 566038a3c2867894a08125efe41ef0a40824a090,Face recognition and gender classification in personal memories,"978-1-4244-2354-5/09/$25.00 ©2009 IEEE
 ICASSP 2009"
 56b9c6efe0322f0087d2f82b52129cc6b41ab356,"Acquire, Augment, Segment & Enjoy: Weakly Supervised Instance Segmentation of Supermarket Products","Acquire, Augment, Segment & Enjoy:
@@ -29229,22 +24863,10 @@ Relatively-Paired Space Analysis: Learning a Latent Common
 Space from Relatively-Paired Observations
 Zhanghui Kuang · Kwan-Yee K. Wong
 Received: date / Accepted: date"
-56d4eeb7fcdfd4f3156b9bdd20a9f35c995ebcac,Local Similarity Based Linear Discriminant Analysis for Face Recognition with Single Sample per Person,"Local Similarity based Linear Discriminant
-Analysis for Face Recognition with Single
-Sample per Person
-Fan Liu1, Ye Bi1, Yan Cui2, Zhenmin Tang1
-School of Computer Science and Engineering, Nanjing University of Science and
-Key Laboratory of Broadband Wireless Communication and Sensor Network
-Technology, Nanjing University of Posts and Telecommunications, China
-Technology, China"
 56a0ead811a1bf15e42be8a9a007b0299636f213,Talk the Walk: Navigating New York City through Grounded Dialogue,"Talk the Walk: Navigating New York City through
 Grounded Dialogue
 Harm de Vries1, Kurt Shuster3, Dhruv Batra3,2, Devi Parikh3,2, Jason Weston3 & Douwe Kiela3
 MILA, Université de Montréal; 2Georgia Institute of Technology; 3Facebook AI Research"
-56a653fea5c2a7e45246613049fb16b1d204fc96,Quaternion Collaborative and Sparse Representation With Application to Color Face Recognition,"Quaternion Collaborative and Sparse Representation
-With Application to Color Face Recognition
-Cuiming Zou, Kit Ian Kou, Member, IEEE, and Yulong Wang, Student Member, IEEE
-representation-based"
 56dca23481de9119aa21f9044efd7db09f618704,Riemannian Dictionary Learning and Sparse Coding for Positive Definite Matrices,"Riemannian Dictionary Learning and Sparse
 Coding for Positive Deﬁnite Matrices
 Anoop Cherian
@@ -29271,26 +24893,6 @@ nel MBPLS presents favorable aspects such as the scalability and robustness with
 number of cameras combined with the high matching rates."
 56cf859363f1b5231418b40b957a9132a78ea546,VLASE: Vehicle Localization by Aggregating Semantic Edges,"VLASE: Vehicle Localization by Aggregating Semantic Edges
 Xin Yu1∗, Sagar Chaturvedi1∗, Chen Feng2, Yuichi Taguchi2, Teng-Yok Lee2, Clinton Fernandes1, Srikumar Ramalingam1"
-568067d7232c753e182dbc1d7075364560ffc363,Scope of physiological and behavioural pain assessment techniques in children – a review,"Scope of physiological and behavioural pain assessment techniques
-in children – a review
-Saranya Devi Subramaniam1, Brindha Doss1 ✉, Lakshmi Deepika Chanderasekar2, Aswini Madhavan1,
-Antony Merlin Rosary2
-Department of Biomedical Engineering, PSG College of Technology, Coimbatore 641004, India
-Department of Electronics & Communication Engineering, PSG College of Technology, Coimbatore, 641004, India
-✉ E-mail:
-Published in Healthcare Technology Letters; Received on 7th February 2018; Accepted on 10th May 2018
-Pain is an unpleasant subjective experience. At present, clinicians are using self-report or pain scales to recognise and monitor pain in children.
-However, these techniques are not efﬁcient to observe the pain in children having cognitive disorder and also require highly skilled observers
-to measure pain. Using these techniques it is also difﬁcult to choose the analgesic drug dosages to the patients after surgery. Thus, this
-onceptual work explains the demand for automatic coding techniques to evaluate pain and also it documents some evidence of
-techniques that act as an alternative approach for objectively determining pain in children. In this review, some good indicators of pain in
-hildren are explained in detail; they are facial expressions from an RGB image, thermal image and also feature from well proven
-physiological signals such as electrocardiogram, skin conductance, body temperature, surgical pleth index, pupillary reflex dilation,
-nalgesia nociception index, photoplethysmography, perfusion index etc.
-. Introduction: The children will encounter pain resulting from
-injuries, disease, after surgery and other health problems. The
-‘International Association for the Study of Pain (IASP)’, an
-interdisciplinary organisation created in 1973 to study pain and"
 564d4ee76c0511bc395dfc8ef8e3b3867fc34a6d,Robust group sparse representation via half-quadratic optimization for face recognition,"Robust Group Sparse Representation via Half-Quadratic Optimization
 for Face Recognition
 Yong Peng and Bao-Liang Lu(cid:3), Senior Member, IEEE"
@@ -29336,26 +24938,6 @@ Berichter: Universit¨atsprofessor Dr.-Ing. Hermann Ney
 Universit¨atsprofessor Dr.-Ing. Hans Burkhardt
 Tag der m¨undlichen Pr¨ufung: 14. M¨arz 2006
 Diese Dissertation ist auf den Internetseiten der Hochschulbibliothek online verf¨ugbar."
-98a60b218ff8addaf213e97e2f4b54d39e45f5b9,Benchmarking Real World Object Recognition,"Bonn-Aachen International Center for Information Technology
-Master of Science in Autonomous Systems
-Bonn-Rhein-Sieg University of Applied Sciences
-Date: March 4, 2005
-Student: Adolf, Florian-Michael
-Matriculation-No: 9005989
-eMail:
-Supervisor: Prassler, Erwin
-Institution: UAS Bonn-Rhein-Sieg
-eMail:
-Benchmarking Real World Object Recognition
-Summer Term 2005
-Master Thesis Proposal
-Context
-Service robotics basically comprise everything that is not industrial robotics, and reflects
-the distinction between the manufacturing and service sectors of the economy. Hence
-service robots are supposed to operate in our human world as autonomously as possible.
-The perception of objects in video images suitable for everyday use (”real-world”) is one
-of the key disciplines in developing this key technology.
-Recent service robotic projects [16, 13, 19, 20, 2] demand research in machine vision and"
 98a660c15c821ea6d49a61c5061cd88e26c18c65,Face Databases for 2 D and 3 D Facial Recognition : A Survey,"IOSR Journal of Engineering (IOSRJEN)
 e-ISSN: 2250-3021, p-ISSN: 2278-8719
 Vol. 3, Issue 4 (April. 2013), ||V1 || PP 43-48
@@ -29487,13 +25069,6 @@ OpenAI
 Sergey Levine
 Google Brain
 UC Berkeley"
-98735e57075ed6e8ef9d98d7ca4895013492e35b,Backdoor Embedding in Convolutional Neural Network Models via Invisible Perturbation,"Backdoor Embedding in Convolutional Neural Network Models
-via Invisible Perturbation
-Cong Liao∗†, Haoti Zhong∗‡, Anna Squicciarini†, Sencun Zhu⨿, David Miller‡
-College of Information Sciences & Technology
-⨿Dept. of Computer Sciences & Engineering
-Dept. of Electrical Engineering
-Pennsylvania State University"
 98c7a6210ca7bc81d2f7092ab28451f47039e920,UC Merced Proceedings of the Annual Meeting of the Cognitive Science Society Title What is the Ground ?,"UC Merced
 Proceedings of the Annual Meeting of the Cognitive Science
 Society
@@ -29793,23 +25368,6 @@ Nicolas Thome 3
 Sorbonne Universit´es, UPMC Univ Paris 06, CNRS, LIP6 UMR 7606, 4 place Jussieu, 75005 Paris
 Heuritech, 248 rue du Faubourg Saint-Antoine, 75012 Paris
 Conservatoire National des Arts et M´etiers"
-fefd9778ef0c23b9e59c2a4748dcb98c827168f4,Semantic Pixel Sets Based Local Binary Patterns for Face Recognition,"Semantic Pixel Sets based Local Binary Patterns
-for Face Recognition
-Zhenhua Chai1, Heydi Mendez-Vazquez2, Ran He1, Zhenan Sun1, and Tieniu
-National Laboratory of Pattern Recognition, Institute of Automation,
-Chinese Academy of Science, P.O. Box 2728, Beijing, 100080, P.R. China
-Advanced Technologies Application Center.
-7th Avenue #21812 b/ 218 and 222, P.C. 12200, Playa, Havana, Cuba."
-fe7e3cc1f3412bbbf37d277eeb3b17b8b21d71d5,Performance Evaluation of Gabor Wavelet Features for Face Representation and Recognition,"IOSR Journal of VLSI and Signal Processing (IOSR-JVSP)
-Volume 6, Issue 2, Ver. I (Mar. -Apr. 2016), PP 47-53
-e-ISSN: 2319 – 4200, p-ISSN No. : 2319 – 4197
-www.iosrjournals.org
-Performance Evaluation of Gabor Wavelet Features for Face
-Representation and Recognition
-M. E. Ashalatha1, Mallikarjun S. Holi2
-Dept. of Biomedical Engineering, Bapuji Institute of Engineering & Technology Davanagere, Karnataka,India
-Dept. of Electronics and Instrumentation Engineering, University B.D.T.College of Engineering, Visvesvaraya
-Technological University,  Davanagere, Karnataka, India"
 fe9b0accf0e7d3821bc5d7d62937499a441633c9,Learning Disentangled Representations with Reference-Based Variational Autoencoders,"Learning Disentangled Representations with
 Reference-Based Variational Autoencoders
 Adria Ruiz 1 Oriol Martinez 2 Xavier Binefa 2 Jakob Verbeek 1"
@@ -30036,11 +25594,6 @@ Panna Felsen1,2, Patrick Lucey2, and Sujoy Ganguly2
 BAIR, UC Berkeley
 STATS
 {plucey,"
-34b6466e3e69547f6d464ad6b5660b1e629a5c35,Similar and Class Based Image Retrieval Using Hash Code,"IJCSNS International Journal of Computer Science and Network Security, VOL.15 No.3, March 2015
-Similar and Class Based Image Retrieval Using Hash Code
-B.Bharathi 1, Nagarjuna Reddy Akkim2
-Faculty of computing, Sathyabama University, Chennai, India
-Introduction"
 3468740e4a9fc72a269f4f0ca8470ccd60925f92,Robustness Analysis of Visual QA Models by Basic Questions,"Robustness Analysis of Visual QA Models by Basic Questions
 Jia-Hong Huang
 Bernard Ghanem
@@ -30063,22 +25616,6 @@ Atlanta, GA, USA
 Duen Horng (Polo) Chau
 Georgia Tech
 Atlanta, GA, USA"
-341633ccce0f8c055dfc633765d905c269e28f82,Collaborative Representation for Face Recognition based on Bilateral Filtering,"Collaborative Representation for Face
-Recognition based on Bilateral Filtering
-Rokan Khaji1, Hong Li2, Ramadan Abdo Musleh3, Hongfeng Li4, Qabas Ali5
-School of Mathematics and Statistics,
-Huazhong University of Science & Technology , Wuhan, 430074, China
-Department of Mathematics, College of Science, Diyala University,  Diyala, 32001 ,Iraq
-,3,4School of Mathematics and Statistics,
-Huazhong University of Science & Technology , Wuhan, 430074, China
-5Department of Electronics and Information Engineering,
-Huazhong University of Science & Technology , Wuhan, 430074, China."
-34b4f264578fc674dd2bf8d478ec1314739a5629,3D Novel Face Sample Modeling for Face Recognition,"D Novel Face Sample Modeling for Face
-Recognition
-Yun Ge, Yanfeng Sun, Baocai Yin, Hengliang Tang
-Beijing Key Laboratory of Multimedia and Intelligent Software Technology
-College of Computer Science and Technology, BJUT, Beijing, China
-Email:"
 34d15fea236612e9df10e4c7a25ca31c0d95edd1,Biases in spatial bisection induced by viewing male and female faces.,"Research Article
 Biases in Spatial Bisection Induced
 y Viewing Male and Female Faces
@@ -30163,16 +25700,6 @@ Barbara Ruggeri & Ugis Sarkans & Gunter Schumann &
 Antonio M. Persico
 Received: 15 April 2013 /Accepted: 7 September 2013
 # Springer-Verlag Berlin Heidelberg 2013"
-34b124ecdc3471167cea1675a74a0232a881bc69,Infrared face recognition based on LBP co-occurrence matrix,"Int. J. Wireless and Mobile Computing, Vol. 8, No. 1, 2015
-Infrared face recognition based on LBP
-o-occurrence matrix and partial least squares
-Zhihua Xie and Guodong Liu*
-Key Lab of Optic-Electronic and Communication,
-Jiangxi Sciences and Technology Normal University,
-Nanchang, China
-Email:
-Email:
-*Corresponding author"
 34f8086eb67eb2cd332cd2d6bca0dd8f1e8f1062,Face Recognition and Growth Prediction using a 3 D Morphable Face Model,"Saarland University
 Faculty of Natural Sciences and Technology I
 Department of Computer Science
@@ -30237,11 +25764,6 @@ of New York
 The Graduate Center, City University
 Hunter College, City University of
 The Graduate Center, City University"
-3447fc311a3adf60d36283b51c1a1e0d3be7416c,A Generic Framework for Efficient 2-D and 3-D Facial Expression Analogy,"A Generic Framework for Ef(cid:2)cient 2D and 3D
-Facial Expression Analogy
-Mingli Song, Member, IEEE, Zhao Dong*, Student Member, IEEE,
-Christian Theobalt, Member, IEEE, Huiqiong Wang, Zicheng Liu, Senior Member, IEEE and
-Hans-Peter Seidel, Senior Member, IEEE"
 34d484b47af705e303fc6987413dc0180f5f04a9,RI : Medium : Unsupervised and Weakly-Supervised Discovery of Facial Events 1,"RI:Medium: Unsupervised and Weakly-Supervised
 Discovery of Facial Events
 Introduction
@@ -30323,9 +25845,6 @@ L’archive ouverte pluridisciplinaire HAL, est
 destinée au dépôt et à la diffusion de documents
 scientifiques de niveau recherche, publiés ou non,
 émanant des établissements d’enseignement et de"
-347ce37f15cea5bb8d0a676562664f80e3609b78,Pixel Objectness: Learning to Segment Generic Objects Automatically in Images and Videos,"Pixel Objectness: Learning to Segment Generic
-Objects Automatically in Images and Videos
-Bo Xiong∗, Suyog Dutt Jain∗, and Kristen Grauman, Member, IEEE"
 34df09a9445089c8f23eff5b2a43a822c9713f6e,Boosting chamfer matching by learning chamfer distance normalization,"Boosting Chamfer Matching by Learning
 Chamfer Distance Normalization
 Tianyang Ma, Xingwei Yang, and Longin Jan Latecki
@@ -30377,33 +25896,7 @@ email: {jamalad,"
 Generating Textual Adversarial Examples for
 Deep Learning Models: A Survey
 Wei Emma Zhang, Quan Z. Sheng, Ahoud Abdulrahmn F Alhazmi, and Chenliang Li"
-881066ec43bcf7476479a4146568414e419da804,From Traditional to Modern : Domain Adaptation for Action Classification in Short Social Video Clips,"From Traditional to Modern : Domain Adaptation for
-Action Classiﬁcation in Short Social Video Clips
-Aditya Singh, Saurabh Saini, Rajvi Shah, and P J Narayanan
-Center for Visual Information Technology, IIIT Hyderabad, India"
-88502625b546607f4992085a313dab1ceb68e4d7,A New Technique using Cubic Curves and Hamming Distance to Detect Human Emotions,"www.ijemr.net
-ISSN (ONLINE): 2250-0758, ISSN (PRINT): 2394-6962
-Volume-7, Issue-4, July-August 2017
-International Journal of Engineering and Management Research
-Page Number: 17-22
-A New Technique using Cubic Curves and Hamming Distance to Detect
-Human Emotions
-R. Neela1, M. Jayasri2
-Department of Computer Science, AVC College (Autonomous), Mannampandal, INDIA
-M.Phil. Research Scholar, Department of Computer Science, AVC College (Autonomous), Mannampandal, INDIA"
 8855d6161d7e5b35f6c59e15b94db9fa5bbf2912,COGNITION IN PREGNANCY AND THE POSTPARTUM PERIOD,COGNITION IN PREGNANCY AND THE POSTPARTUM PERIOD
-88f5f9d92c4fa696457a824c3eec204da05ba6a4,XGAN: Unsupervised Image-to-Image Translation for many-to-many Mappings,"XGAN: Unsupervised Image-to-Image
-Translation for Many-to-Many Mappings
-Am´elie Royer1[0000−0002−8407−0705], Konstantinos Bousmalis2,6, Stephan
-Gouws2, Fred Bertsch3, Inbar Mosseri4, Forrester Cole4, and Kevin Murphy5
-IST Austria, 3400 Klosterneuburg, Austria
-Work done while at Google Brain London, UK
-Google Brain, London, UK
-{konstantinos,
-Google Brain, Mountain View, USA
-Google Research, Cambridge, USA
-5 Google Research, Mountain View, USA
-6 Currently at Deepmind, London, UK"
 88850b73449973a34fefe491f8836293fc208580,XBeats-An Emotion Based Music Player,"www.ijaret.org                                                                                                                                                     Vol. 2, Issue I, Jan. 2014
 ISSN 2320-6802
 INTERNATIONAL JOURNAL FOR ADVANCE RESEARCH IN
@@ -30438,9 +25931,6 @@ Department of Computing, Curtin University of Technology, WA 6845, Australia"
 8813368c6c14552539137aba2b6f8c55f561b75f,Trunk-Branch Ensemble Convolutional Neural Networks for Video-Based Face Recognition,"Trunk-Branch Ensemble Convolutional Neural
 Networks for Video-based Face Recognition
 Changxing Ding, Student Member, IEEE, Dacheng Tao, Fellow, IEEE"
-889bc64c7da8e2a85ae6af320ae10e05c4cd6ce7,Using Support Vector Machines to Enhance the Performance of Bayesian Face Recognition,"Using Support Vector Machines to Enhance the
-Performance of Bayesian Face Recognition
-Zhifeng Li, Member, IEEE, and Xiaoou Tang, Senior Member, IEEE"
 8897dd825230695a8a669b29a4d1b284373adb31,Face Recognition using Co-occurrence Matrix of Local Average Binary Pattern ( CMLABP ),"Cyber Journals: Multidisciplinary Journals in Science and Technology, Journal of Selected Areas in Telecommunications (JSAT), April Edition, 2012
 Face Recognition using Co-occurrence Matrix
 of Local Average Binary Pattern (CMLABP)
@@ -30523,15 +26013,6 @@ Jingdong Wang† Xian-Sheng Hua‡ Shipeng Li†
 Microsoft Corporation
 Microsoft Research Asia
 August 10, 2012"
-88909ec19d2c6750f836e8b9c15ee3e1236b37e7,Local Learning with Deep and Handcrafted Features for Facial Expression Recognition,"Local Learning with Deep and Handcrafted Features
-for Facial Expression Recognition
-Mariana-Iuliana Georgescu1,2
-Radu Tudor Ionescu1,3
-Marius Popescu1,3
-University of Bucharest, 14 Academiei, Bucharest, Romania
-Novustech Services, 12B Aleea Ilioara, Bucharest, Romania
-SecurifAI, 21D Mircea Vod˘a, Bucharest, Romania
-georgescu"
 88e3aefe454e72388bbbe7dfa0b74fcfc52032f0,Weighted Gradient Feature Extraction Based on Multiscale Sub-Blocks for 3D Facial Recognition in Bimodal Images,"Article
 Weighted Gradient Feature Extraction Based on
 Multiscale Sub-Blocks for 3D Facial Recognition in
@@ -30551,14 +26032,6 @@ Heechul Jung† Sihaeng Lee† Sunjeong Park†
 Korea Advanced Institute of Science and Technology†
 Electronics and Telecommunications Research Institute‡
 {heechul, haeng, sunny0414, {ninja,"
-88a37a05024ef3390e2f1b67fb3637d1c8bbddb3,Home Theft Detection and Recognition Using ROI and PCA Technique,"International Journal of Science and Research (IJSR)
-ISSN (Online): 2319-7064
-Index Copernicus Value (2013): 6.14 | Impact Factor (2014): 5.611
-Home Theft Detection and Recognition Using ROI
-nd PCA Technique
-Ram Singh1, Ashok Kumar Bathla2
-Research scholar, CE Department, YCOE, Punjabi University, Patiala, India
-Assistant Professor, CE Department, YCOE, Punjabi University, Patiala, India"
 883006c0f76cf348a5f8339bfcb649a3e46e2690,Weakly supervised pain localization using multiple instance learning,"Weakly Supervised Pain Localization using Multiple Instance Learning
 Karan Sikka, Abhinav Dhall and Marian Bartlett"
 8816ee1e23983f5a4340743c7744a336fae02d60,Face Recognition Using Boosted Local Features,"MITSUBISHI ELECTRIC RESEARCH LABORATORIES
@@ -30581,47 +26054,8 @@ Belo Horizonte, Brazil"
 D Human Face Reconstruction Using a Hybrid of Photometric
 Stereo and Independent Component Analysis
 *Cheng-Jian Lin, 2Shyi-Shiun Kuo, 1Hsueh-Yi Lin, 2Shye-Chorng Kuo and 1Cheng-Yi Yu"
-507660f778fe913f6e1957fe39a87cbf50a52b2e,Sparse Camera Network for Visual Surveillance -- A Comprehensive Survey,"Sparse Camera Network for Visual
-Surveillance – A Comprehensive Survey
-Mingli Song, Member, IEEE, Dacheng Tao, Senior Member, IEEE,
-nd Stephen J. Maybank, Fellow, IEEE"
-500993a8852f766d4bac7b5039b9072b587e4d09,HARRISON: A Benchmark on HAshtag Recommendation for Real-world Images in Social Networks,"PARK, LI, KIM: HARRISON: A BENCHMARK FOR IMAGE HASHTAG RECOMMENDATION1
-HARRISON: A Benchmark on HAshtag
-Recommendation for Real-world Images in
-SOcial Networks
-School of Electrical Engineering
-KAIST
-South Korea
-Minseok Park
-Hanxiang Li
-Junmo Kim"
-50074af3edde8b12d5131339cc2c3b089fa5d8f1,Face Recognition Using Wavelet Transforms,"ISSN (Print)  : 2320 – 3765
-ISSN (Online): 2278 – 8875
-International Journal of Advanced Research in  Electrical,
-Electronics and Instrumentation Engineering
-(An ISO 3297: 2007 Certified Organization)
-Vol. 3, Issue 1, January 2014
-Face Recognition Using Wavelet Transforms
-Nikhila S 1, Pavitha U S 2, Krutthika H K 3
-Assistant Professor, Dept. of Instrumentation, Dayananda Sagar College of Engineering, Bangalore, India
-Assistant Professor, Dept. of Instrumentation, Dayananda Sagar College of Engineering, Bangalore, India
-Assistant Professor, Dept. of E&C, Dayananda Sagar College of Engineering, Bangalore, India"
-50ff21e595e0ebe51ae808a2da3b7940549f4035,Age Group and Gender Estimation in the Wild With Deep RoR Architecture,"IEEE TRANSACTIONS ON LATEX CLASS FILES, VOL. XX, NO. X, AUGUST 2017
-Age Group and Gender Estimation in the Wild with
-Deep RoR Architecture
-Ke Zhang, Member, IEEE, Ce Gao, Liru Guo, Miao Sun, Student Member, IEEE, Xingfang Yuan, Student
-Member, IEEE, Tony X. Han, Member, IEEE, Zhenbing Zhao, Member, IEEE and Baogang Li"
 50bf792c721293222248f906e95726ac2ac2fe9e,Characterising Pedestrian Detection on a Heterogeneous Platform,"Characterising Pedestrian Detection on a Heterogeneous Platform
 Calum Blair1, Neil Robertson2 and Danny Hume3"
-5042b358705e8d8e8b0655d07f751be6a1565482,"- 9359 ( Volume-4 , Issue-8 ) Review on Emotion Detection in Image","International Journal of
-Emerging Research in Management &Technology
-ISSN: 2278-9359 (Volume-4, Issue-8)
-Research  Article
-August
-Review  on Emotion Detection  in Image
-Aswinder Kaur*                                                                                                        Kapil Dewan
-CSE & PCET, PTU                                                                                             HOD, CSE & PCET, PTU
-Punjab, India                                                                                                            Punj ab, India"
 50a48fcd6176b72aea7a61233d3c7fb12a279ba4,A Computational Model of Eye Movements during Object Class Detection,"A Computational Model of Eye Movements
 during Object Class Detection
 Wei Zhang†
@@ -30632,26 +26066,6 @@ Dept. of Computer Science†
 Dept. of Psychology‡
 State University of New York at Stony Brook
 Stony Brook, NY 11794"
-50188f3b8d63e196af9ad156e8ff127e060d0aef,Metadata of the chapter that will be visualized in SpringerLink,"Metadata of the chapter that will be visualized in
-SpringerLink
-Neural Information Processing
-Finger-Vein Quality Assessment by Representation Learning from Binary Images
-Springer International Publishing Switzerland
-Family Name
-Particle
-Given Name
-Prefix
-Suffix
-Division
-Huafeng
-Chongqing Engineering Laboratory of Detection Control and Integrated
-System
-Chongqing Technology and Business University
-Chongqing, 400067, China
-Department of EPH
-Telecom-SudParis
-91011, Paris, Evry Cedex, France
-El-Yacoubi"
 50c1ab22f442470efbe3198f0b338fb699416bc5,A Commute in Data: The comma2k19 Dataset,"A Commute in Data: The comma2k19 Dataset
 Harald Sch¨afer, Eder Santana, Andrew Haden, and Riccardo Biasini
 omma.ai"
@@ -30871,13 +26285,6 @@ DECEMBER 2011"
 nd Pose Dictionary
 Anonymous ECCV submission
 Paper ID 895"
-50e5dd45a94a56cb973e51dc3347e621266db7e4,3 D Face Recognition Using Concurrent Neural Modules,"D Face Recognition Using Concurrent Neural Modules
-VICTOR-EMIL NEAGOE , IONUT MITRACHE, AND DANIEL CARAUSU
-Depart. Electronics, Telecommunications & Information Technology
-Polytechnic University of Bucharest
-Splaiul Independentei No. 313, Sector 6, Bucharest
-ROMANIA
-Email:"
 508eb5a6156b8fa1b4547b611e85969438116fa2,Perceptual Generative Adversarial Networks for Small Object Detection,"Perceptual Generative Adversarial Networks for Small Object Detection
 Jianan Li Xiaodan Liang Yunchao Wei
 Tingfa Xu
@@ -30953,14 +26360,6 @@ bide by the legal requirements associated with these rights.
 Take down policy
 The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer
 ontent complies with UK legislation. If you believe that the public display of this file breaches copyright please"
-1cdf8790a675037579bbe2ee4f39f731f7672fae,Pivot Correlational Neural Network for Multimodal Video Categorization,"Pivot Correlational Neural Network for
-Multimodal Video Categorization
-Sunghun Kang1[0000−0003−2632−7522], Junyeong Kim1[0000−0002−7871−9627],
-Hyunsoo Choi2, Sungjin Kim2, and Chang D. Yoo1
-KAIST, Daejeon, South Korea
-{sunghun.kang, junyeong.kim,
-SAMSUNG ELECTRONICS CO.,LTD, Seoul, South Korea
-{hsu.choi,"
 1cbc189a4484cd2b1371798bae2ff50c0442ce60,A Hybrid Loss for Multiclass and Structured Prediction,"IEEE TRANSACTIONS ON PATTERN ANALYSIS & MACHINE INTELLIGENCE, FINAL DRAFT, FEB. 2014
 A Hybrid Loss for Multiclass
 nd Structured Prediction
@@ -30974,30 +26373,6 @@ Language Acquisition in Virtual Environment
 Haonan Yu, Haichao Zhang, and Wei Xu
 Baidu Research - Institue of Deep Learning
 Sunnyvale, CA 94089"
-1c7e1248ce254b3a9a0b6fef9e37d37620fc8aa3,Dynamic Image-to-Class Warping for Occluded Face Recognition,"Dynamic Image-to-Class Warping for Occluded
-Face Recognition
-Xingjie Wei, Chang-Tsun Li, Senior Member, IEEE, Zhen Lei, Member, IEEE,
-Dong Yi, and Stan Z. Li, Fellow, IEEE"
-1ce4587e27e2cf8ba5947d3be7a37b4d1317fbee,Deep fusion of visual signatures for client-server facial analysis,"Deep fusion of visual signatures
-for client-server facial analysis
-Binod Bhattarai
-Normandie Univ, UNICAEN,
-ENSICAEN, CNRS, GREYC
-Gaurav Sharma
-Computer Sc. & Engg.
-IIT Kanpur, India
-Frederic Jurie
-Normandie Univ, UNICAEN,
-ENSICAEN, CNRS, GREYC
-Facial analysis is a key technology for enabling human-
-machine interaction.
-In this context, we present a client-
-server framework, where a client transmits the signature of
-face to be analyzed to the server, and, in return, the server
-sends back various information describing the face e.g. is the
-person male or female, is she/he bald, does he have a mus-
-tache, etc. We assume that a client can compute one (or a
-ombination) of visual features; from very simple and ef‌f‌i-"
 1cb95f013ec3e78acdda6ac6cfdb362ae6a5ceac,Nonnegative matrix factorization for segmentation analysis,"Nonnegative matrix factorization for
 segmentation analysis
 Roman Sandler
@@ -31011,10 +26386,6 @@ Huijuan Xu
 UMass Lowell
 Kate Saenko
 UMass Lowell"
-1cdff2cd2e3cf8dbeb8f0a42df0cdc77c953dc81,The Emergence of Visual Crowdsensing: Challenges and Opportunities,"The Emergence of Visual Crowdsensing:
-Challenges and Opportunities
-Bin Guo, Senior Member, IEEE, Qi Han,Member, IEEE , Huihui Chen, Longfei Shangguan, Member, IEEE,
-Zimu Zhou, Member, IEEE, and Zhiwen Yu, Senior Member, IEEE"
 1ce3a91214c94ed05f15343490981ec7cc810016,Exploring photobios,"Exploring Photobios
 Ira Kemelmacher-Shlizerman1
 Eli Shechtman2
@@ -31031,13 +26402,6 @@ Moustapha Cisse
 Facebook AI Research
 Natalia Neverova*
 Facebook AI Research"
-1cf01968594ae59d28b12c9a35fc43d944563071,Low-Level Features for Image Retrieval Based on Extraction of Directional Binary Patterns and Its Oriented Gradients Histogram,"Computer Applications: An International Journal (CAIJ), Vol.2, No.1, February 2015
-LOW-LEVEL FEATURES FOR IMAGE RETRIEVAL BASED
-ON EXTRACTION OF DIRECTIONAL BINARY PATTERNS
-AND ITS ORIENTED GRADIENTS HISTOGRAM
-Nagaraja S. and Prabhakar C.J.
-Department of P.G. Studies and Research in Computer Science
-Kuvempu University, India"
 1cd584f519d9cd730aeef1b1d87f7e2e82b4de59,A fully automatic face recognition system using a combined audio-visual approach ∗,"A fully automatic face recognition system using a combined
 udio-visual approach ∗
 Alberto Albiol†, Luis Torres†, and Edward J. Delp? †
@@ -31072,31 +26436,6 @@ AVCOE Sangamner"
 Hierarchical Adaptive Structural SVM for Domain Adaptation
 Jiaolong Xu · Sebastian Ramos · David V´azquez · Antonio M. L´opez
 Received: date / Accepted: date"
-1c9da6cef6b1be9c116b26dd52c341c0adcf7db2,Interactive Perception: Leveraging Action in Perception and Perception in Action,"Interactive Perception: Leveraging Action in
-Perception and Perception in Action
-Jeannette Bohg*, Member, IEEE, Karol Hausman*, Student Member, IEEE, Bharath Sankaran*, Student
-Member, IEEE, Oliver Brock, Senior Member, IEEE, Danica Kragic, Fellow, IEEE, Stefan Schaal, Fellow, IEEE,
-nd Gaurav Sukhatme, Fellow, IEEE"
-1c3ec6379ba664d52d250ac1647d379ec970fa5c,Object proposal by multi-branch hierarchical segmentation,"Object Proposal by Multi-branch Hierarchical Segmentation
-Chaoyang Wang1,3, Long Zhao2,3, Shuang Liang2, Liqing Zhang1, Jinyuan Jia2, Yichen Wei3
-Shanghai Jiao Tong University. 2Tongji University. 3Microsoft Research.
-Segmentation based object proposal methods [1, 2, 5, 6, 8] have become an
-important step in modern object detection paradigm. Among those, hierar-
-hical segmentation is favorable for its ability to capture objects of all scales
-nd has fast implementation such as hierarchical greedy merging [6, 8].
-However, single-way hierarchical greedy merging is fundamentally flawed
-in that the errors in early steps of greedy merging cannot be corrected and
-ccumulate.
-In this work, we propose a novel multi-branch hierarchical
-segmentation approach that alleviates such problems by learning multiple
-merging strategies in each step in a complementary manner, such that errors
-in one merging strategy could be corrected by the others. This approach
-turns the original hierarchical greedy merging’s sequential evolution struc-
-ture into a tree-like structure. As illustrated in Fig. 1, different merging
-strategies are tried throughout the greedy merging process, which we call
-ranching. Objects, especially large and complex ones will get a better
-hance to be detected in one of those tree branches.
-To make our multi-branched hierarchical segmentation effective, we ad-"
 1c3073b57000f9b6dbf1c5681c52d17c55d60fd7,Direction de thèse:,"THÈSEprésentéepourl’obtentiondutitredeDOCTEURDEL’ÉCOLENATIONALEDESPONTSETCHAUSSÉESSpécialité:InformatiqueparCharlotteGHYSAnalyse,Reconstruction3D,&AnimationduVisageAnalysis,3DReconstruction,&AnimationofFacesSoutenancele19mai2010devantlejurycomposéde:Rapporteurs:MajaPANTICDimitrisSAMARASExaminateurs:MichelBARLAUDRenaudKERIVENDirectiondethèse:NikosPARAGIOSBénédicteBASCLE"
 1ca155a4b65ae19ccb73df48516e4775770a382c,Action Representations in Robotics: A Taxonomy and Systematic Classification,"Action representations in robotics: A
 taxonomy and systematic classiﬁcation
@@ -31114,10 +26453,6 @@ Supervision
 Yalong Jiang1                                                                   1Department of Electronic and Information
 Engineering
 Zheru Chi1                                                                             The Hong Kong Polytechnic University, HK"
-1cc3c5f242d885738e9349a91d4beba82ae106a6,Scalable nonconvex inexact proximal splitting,"Scalable nonconvex inexact proximal splitting
-Suvrit Sra
-Max Planck Institute for Intelligent Systems
-72076 T¨ubigen, Germany"
 1c40cb899fccbe98a2bb63088e02d6c59e87c187,An Interaction Framework for a Cooperation between Fully Automated Vehicles and External Users in Semi-stationary Urban Scenarios,
 1c521ac6e68436f6c6aad3c0eb7ffa557fe25b0d,Modeling Image Patches with a Generic Dictionary of Mini-epitomes,"Modeling Image Patches with a Generic Dictionary of Mini-Epitomes
 George Papandreou
@@ -31126,11 +26461,6 @@ Liang-Chieh Chen
 UC Los Angeles
 Alan L. Yuille
 UC Los Angeles"
-1cb68fa98a0d9871a394cd0035488df167b9c2cf,RedNet: Residual Encoder-Decoder Network for indoor RGB-D Semantic Segmentation,"RedNet: Residual Encoder-Decoder Network for
-indoor RGB-D Semantic Segmentation
-Jindong Jiang, Lunan Zheng, Fei Luo, and Zhijun Zhang
-The School of Automation Science and Engineering, South China University of
-Technology, Guangzhou 510640, China"
 1cf29a0131211079fc73908ecf211ee78f090ad9,Regionlets for Generic Object Detection,"Regionlets for Generic Object Detection
 Xiaoyu Wang Ming Yang
 Shenghuo Zhu
@@ -31177,26 +26507,6 @@ Detection stream
 horse
 0.04 0.01 0.07 0.88
 person 0.02 0.03 0.91 0.04"
-1ca40e1d0ae377296ac6804c81c1e5bcbc5475c8,RVM-Based Human Action Classification in Crowd through Projection and Star Skeletonization,"Hindawi Publishing Corporation
-EURASIP Journal on Image and Video Processing
-Volume 2009, Article ID 164019, 12 pages
-doi:10.1155/2009/164019
-Research Article
-RVM-Based Human Action Classiﬁcation in Crowd through
-Projection and Star Skeletonization
-B. Yogameena, S. Veeralakshmi, E. Komagal, S. Raju, and V. Abhaikumar
-Department of Electronics and Communication Engineering, Thiagarajar College of Engineering,
-Madurai 625015, Tamil Nadu, India
-Correspondence should be addressed to B. Yogameena,
-Received 1 February 2009; Revised 17 May 2009; Accepted 26 August 2009
-Recommended by Amit Roy-Chowdhury
-Detection of abnormal human actions in the crowd has become a critical problem in video surveillance applications like terrorist
-ttacks. This paper proposes a real-time video surveillance system which is capable of classifying normal and abnormal actions of
-individuals in a crowd. The abnormal actions of human such as running, jumping, waving hand, bending, walking and ﬁghting
-with each other in a crowded environment are considered. In this paper, Relevance Vector Machine (RVM) is used to classify
-the abnormal actions of an individual in the crowd based on the results obtained from projection and skeletonization methods.
-Experimental results on benchmark datasets demonstrate that the proposed system is robust and ef‌f‌icient. A comparative study of
-lassiﬁcation accuracy between Relevance Vector Machine and Support Vector Machine (SVM) classiﬁcation is also presented."
 1cc0183d8fbef098d29b6b5f621745ff099f6c6c,Joint Discovery of Object States and Manipulation Actions,"Joint Discovery of Object States and Manipulation Actions
 Jean-Baptiste Alayrac∗ †
 Josef Sivic∗ † ‡
@@ -31282,24 +26592,6 @@ scientiﬁques de niveau recherche, publi´es ou non,
 Annotation: A Generative Adversarial Network
 Approach
 Avisek Lahiri*, Vineet Jain*, Arnab Mondal*, and Prabir Kumar Biswas, Senior Member, IEEE"
-45c4514ca2b7903b4c8f43e396bce73f014b72be,Parallel Feature Extraction through Preserving Global and Discriminative Property for Kernel-Based Image Classification,"Journal of Information Hiding and Multimedia Signal Processing
-Ubiquitous International
-(cid:13)2015 ISSN 2073-4212
-Volume 6, Number 5, September 2015
-Parallel Feature Extraction through Preserving
-Global and Discriminative Property for Kernel-Based
-Image Classiﬁcation
-Xun-Fei Liu, and Xiang-Xian Zhu
-Department of Electrical Engineering
-Suzhou Institute of Industrial Technology
-Suzhou, 215104, China
-Received May, 2015; revised June, 2015"
-45bedfcb562e48a64436ea3131bc91098eb93dab,Incremental update of biometric models in face-based video surveillance,"Incremental Update of Biometric Models in
-Face-Based Video Surveillance
-Miguel De-la-Torre∗†, Eric Granger∗, Paulo V. W. Radtke∗, Robert Sabourin∗, Dmitry O. Gorodnichy‡
-´Ecole de technologie sup´erieure, Montr´eal, Canada
-Centro Universitario de Los Valles, Universidad de Guadalajara, Ameca, M´exico
-Science and Engineering Directorate, Canada Border Services Agency, Ottawa, Canada"
 4583d7d1d76dfe18e86e91f7438ce1a03cdcf68f,3D Face: biometric template protection for 3d face recognition,"\3D Face"": Biometric Template Protection for
 D Face Recognition
 E.J.C. Kelkboom, B. G(cid:127)okberk, T.A.M. Kevenaar, A.H.M. Akkermans, and M.
@@ -31367,12 +26659,6 @@ Authors:
 Filani Araoluwa S., Adetunmbi Adebayo O.
 10.5120/ijca2016907932
 {bibtex}2016907932.bib{/bibtex}"
-45e2aa7706fcedcbb2d93304a9824fe762b8b3b0,DAC-SDC Low Power Object Detection Challenge for UAV Applications,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2018
-DAC-SDC Low Power Object Detection
-Challenge for UAV Applications
-Xiaowei Xu, Member, IEEE, Xinyi Zhang, Student Member, IEEE, Bei Yu, Senior Member, IEEE, Xiaobo
-Sharon Hu, Fellow, IEEE, Christopher Rowen, Fellow, IEEE, Jingtong Hu, Member, IEEE, and Yiyu
-Shi, Senior Member, IEEE"
 4560491820e0ee49736aea9b81d57c3939a69e12,Investigating the Impact of Data Volume and Domain Similarity on Transfer Learning Applications,"Investigating the Impact of Data Volume and
 Domain Similarity on Transfer Learning
 Applications
@@ -31390,11 +26676,6 @@ Armine Vardazaryan1, Didier Mutter2, Jacques Marescaux2, and
 Nicolas Padoy1
 ICube, University of Strasbourg, CNRS, IHU Strasbourg, France
 University Hospital of Strasbourg, IRCAD, IHU Strasbourg, France"
-459e840ec58ef5ffcee60f49a94424eb503e8982,One-shot Face Recognition by Promoting Underrepresented Classes,"One-shot Face Recognition by Promoting Underrepresented Classes
-Yandong Guo, Lei Zhang
-Microsoft
-One Microsoft Way, Redmond, Washington, United States
-{yandong.guo,"
 453e311c6de1285cd5ea6d93fd78a636eac0ba82,Multi patches 3D facial representation for person authentication using AdaBoost,"Multi patches 3D facial representation for Person
 Authentication using AdaBoost
 Lahoucine Ballihi, Boulbaba Ben Amor, Mohamed Daoudi, Anuj Srivastava
@@ -31415,20 +26696,6 @@ broad, or from public or private research centers.
 L’archive ouverte pluridisciplinaire HAL, est
 destinée au dépôt et à la diffusion de documents
 scientifiques de niveau recherche, publiés ou non,"
-455943924a98593655ae7197ee3835b9f6a3b778,Visual SLAM for Automated Driving: Exploring the Applications of Deep Learning,"Visual SLAM for Automated Driving:
-Exploring the Applications of Deep Learning
-Stefan Milz, Georg Arbeiter, Christian Witt
-Valeo Schalter und Sensoren GmbH
-Bassam Abdallah
-Valeo Vision, Bobigny
-stefan.milz, georg.arbeiter,
-Senthil Yogamani
-Valeo Vision Systems, Ireland"
-4562272025a5bcdb321408116c699798a7997847,Leveraging RGB-D Data: Adaptive fusion and domain adaptation for object detection,"Leveraging RGB-D Data: Adaptive Fusion and
-Domain Adaptation for Object Detection
-Luciano Spinello and Kai O. Arras
-Social Robotics Lab, University of Freiburg, Germany
-{spinello,"
 4534d78f8beb8aad409f7bfcd857ec7f19247715,Transformation-Based Models of Video Sequences,"Under review as a conference paper at ICLR 2017
 TRANSFORMATION-BASED MODELS OF VIDEO
 SEQUENCES
@@ -31614,13 +26881,7 @@ Stefan K¨onig∗"
 Levodopa-Induced Dyskinesia with Deep
 Learning Pose Estimation
 Michael H. Li, Tiago A. Mestre, Susan H. Fox, Babak Taati*"
-457abee61182a320b301d73ecceff00d055f596e,Face Recognition Using Line Edge Map,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 24, NO. 6,
-JUNE 2002
-Face Recognition Using Line Edge Map
-Yongsheng Gao, Member, IEEE, and Maylor K.H. Leung, Member, IEEE"
 458713d5c1dd8ff95865302e51f0f8df22204d91,ON FACE RECOGNITION USING DIFFERENT PRE-PROCESSING METHODS IN IMAGES CAPTURED UNDER VARIOUS ILLUMINATION AND POSING CONDITIONS,
-454ec30d0a491800458a52a5aa655eb76a28f4f5,3-D Object Recognition Using 2-D Views,"-D Object Recognition Using 2-D Views
-Wenjing Li, Member, IEEE, George Bebis, Member, IEEE, and Nikolaos G. Bourbakis, Fellow, IEEE"
 45ae4c0cdc2df02c278995623b2e25ae5cc4c91f,Visual Search for Musical Performances and Endoscopic Videos,"Visual Search
 for Musical Performances
 nd Endoscopic Videos
@@ -31666,9 +26927,6 @@ National Institute of Technology, Toyota College, Japan
 Correspondence: Taichi Hayasaka, Department of Information and Computer Engineering, National Institute of Technology,
 Toyota College, 2-1 Eisei, Toyota-shi, Aichi, 471-8525 Japan,
 E-mail: phone +81 565 36 5861, fax +81 565 36 5926"
-2bbb772332a90b2aba893f7467daa76b373be240,Extracting 3D Layout From a Single Image Using Global Image Structures,"Extracting 3D Layout From a Single Image
-Using Global Image Structures
-Zhongyu Lou, Theo Gevers, Member, IEEE, and Ninghang Hu"
 2bdc0c79b26fed51bc2af1af16117879ee3f571e,Augmented Multitouch Interaction upon a 2-DOF Rotating Disk,"Augmented Multitouch Interaction
 upon a 2-DOF Rotating Disk
 Xenophon Zabulis, Panagiotis Koutlemanis, and Dimitris Grammenos
@@ -31678,9 +26936,6 @@ Herakleion, Crete, Greece"
 Krishnam Gupta1, Syed Ashar Javed2, Vineet Gandhi2 and K. Madhava Krishna2
 evidences is more likely to perform the task better. Recent
 efforts [3] on multi modal fusion also suggests likewise."
-2b9082b6b5266f6f7d7a95892f30cc84138697e5,Video Person Re-Identification by Temporal Residual Learning,"Video Person Re-identiﬁcation by Temporal
-Residual Learning
-Ju Dai∗, Pingping Zhang∗, Huchuan Lu, Senior Member, IEEE, and Hongyu Wang, Member, IEEE"
 2bfb43cb0e72aaa7aff71007bb420df2c9ae4375,Deep Attentional Structured Representation Learning for Visual Recognition,": DEEP ATTENTIONAL STRUCTURED REPRESENTATION LEARNING
 Deep Attentional Structured Representation
 Learning for Visual Recognition
@@ -31817,27 +27072,6 @@ http://lear.inrialpes.fr/people/schmid
 LEAR - INRIA Grenoble, LJK
 655, avenue de l’Europe
 8330 Montbonnot, France"
-2bb968e8f9df0fa72dd72e5d705ea7b75af8dcd7,Fast Support Vector Classifier for automated content-based search in video surveillance,"Fast Support Vector Classifier for Automated
-Content-based Search in Video Surveillance
-Cătălin A. Mitrea1, Ionuț Mironică1, Bogdan Ionescu1,2, Radu Dogaru1
-LAPI & Natural Computing Labs, University “Politehnica” of Bucharest, 061971, Romania
-LISTIC, University Savoie Mont Blanc, 74940 Annecy-le-Vieux, France
-Email:
-for  multiple-instance  human  retrieval"
-2bbbbe1873ad2800954058c749a00f30fe61ab17,Face Verification across Ages Using Self Organizing Map,"ISSN(Online): 2320-9801
-ISSN (Print):  2320-9798
-International Journal of Innovative Research in Computer and Communication Engineering
-(An ISO 3297: 2007 Certified Organization)
-Vol.2, Special Issue 1, March 2014
-Proceedings of International Conference On Global Innovations In Computing Technology (ICGICT’14)
-Organized by
-Department of CSE, JayShriram Group of Institutions, Tirupur, Tamilnadu, India on 6th & 7th March 2014
-Face Verification across Ages Using Self
-Organizing Map
-B.Mahalakshmi1, K.Duraiswamy2, P.Gnanasuganya3, P.Aruldhevi4, R.Sundarapandiyan5
-Associate Professor, Department of CSE, K.S.Rangasamy College of Technology, Namakkal, TamilNadu, India1
-Dean, K.S.Rangasamy College of Technology, Namakkal, TamilNadu, India2
-B.E, Department of CSE, K.S.Rangasamy College of Technology, Namakkal, TamilNadu, India3, 4, 5"
 2b3fe9a0356eaf50f1340dda3f3d14f6904905ec,Taking advantage of sensor modality specific properties in Automated Driving Extended Abstract,"Taking advantage of sensor modality specific properties in
 Automated Driving"
 2badc4c87a7751dd5ae1797bc4091d10d1acf442,Multimodal Retrieval with Asymmetrically Weighted Regularized Canonical Correla- Tion Analysis,"Under review as a conference paper at ICLR 2016
@@ -31847,11 +27081,6 @@ TION ANALYSIS
 Youssef Mroueh, Etienne Marcheret, Vaibhava Goel
 Multimodal Algorithms and Engines Group
 IBM T.J Watson Research Center, USA"
-2ba7c88a7e96d412c116d6bea4ba27be2ed4dd48,CocoNet: A deep neural network for mapping pixel coordinates to color values,"CocoNet: A Deep Neural Network for Mapping
-Pixel Coordinates to Color Values
-Paul Andrei Bricman1 and Radu Tudor Ionescu2
-George Co¸sbuc National College, 29-31 Olari, Bucharest, Romania,
-University of Bucharest, 14 Academiei, Bucharest, Romania"
 2b8667df1a0332386d8d799fbac0327496ce02c9,Stranger danger : Parenthood increases the envisioned bodily formidability of menacing men ☆,"Evolution and Human Behavior 35 (2014) 109–117
 Contents lists available at ScienceDirect
 Evolution and Human Behavior
@@ -31877,31 +27106,6 @@ density estimation from space
 Andres C. Rodriguez and Jan D. Wegner
 ETH Zurich, Stefano-franscini-platz 5 8093 Zurich, Switzerland
 Accepted at GCPR 2018"
-2b4d092d70efc13790d0c737c916b89952d4d8c7,Robust Facial Expression Recognition using Local Haar Mean Binary Pattern,"JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 32, XXXX-XXXX (2016)
-Robust Facial Expression Recognition using Local Haar
-Mean Binary Pattern
-MAHESH GOYANI1, NARENDRA PATEL2
-,2 Department of Computer Engineering
-Charotar University of Science and Technology, Changa, India
-Gujarat Technological University, V.V.Nagar, India
-E-mail:
-In this paper, we propose a hybrid statistical feature extractor, Local Haar Mean Bina-
-ry Pattern (LHMBP). It extracts level-1 haar approximation coefficients and computes Local
-Mean  Binary  Pattern  (LMBP)  of  it.  LMBP  code  of  pixel  is  obtained  by  weighting  the
-thresholded neighbor value of 3  3 patch on its mean. LHMBP produces highly discrimina-
-tive code compared to other state of the art methods. To localize appearance features, ap-
-proximation subband is divided into M  N regions. LHMBP feature descriptor is derived
-y  concatenating  LMBP  distribution  of  each  region.  We  also  propose  a  novel  template
-matching strategy called Histogram Normalized Absolute Difference (HNAD) for histogram
-ased  feature  comparison.  Experiments  prove  the  superiority  of  HNAD  over  well-known
-template  matching  techniques  such  as  L2  norm  and  Chi-Square.  We  also  investigated
-LHMBP for expression recognition in low resolution. The performance of the proposed ap-
-proach is tested on well-known CK, JAFFE, and SFEW facial expression datasets in diverse"
-2b4d40ef1610500c207f166e9a5b55dbfe234045,A New Biased Discriminant Analysis Using Composite Vectors for Eye Detection,"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 42, NO. 4, AUGUST 2012
-A New Biased Discriminant Analysis Using
-Composite Vectors for Eye Detection
-Chunghoon Kim, Member, IEEE, Sang-Il Choi, Member, IEEE,
-Matthew Turk, Senior Member, IEEE, and Chong-Ho Choi, Member, IEEE"
 2b507f659b341ed0f23106446de8e4322f4a3f7e,Deep Identity-aware Transfer of Facial Attributes,"Deep Identity-aware Transfer of Facial Attributes
 Mu Li1, Wangmeng Zuo2, David Zhang1
 The Hong Kong Polytechnic University 2Harbin Institute of Technology"
@@ -32055,10 +27259,6 @@ What Works
 .3 Reconstruction, Localization, Navigation, and
 Visual SLAM
 .4 Object Recognition"
-469d249a40639d4ffb62abfb2c25f5aab0812fa4,Image Inspired Poetry Generation in XiaoIce,"Image Inspired Poetry Generation in XiaoIce∗
-Wen-Feng Cheng1,2, Chao-Chung Wu2, Ruihua Song1, Jianlong Fu1, Xing Xie1, Jian-Yun Nie3
-{wencheng, rsong, jianf,
-Microsoft, 2National Taiwan University, 3University of Montreal"
 46f3b113838e4680caa5fc8bda6e9ae0d35a038c,Automated Dermoscopy Image Analysis of Pigmented Skin Lesions,"Cancers 2010, 2, 262-273; doi:10.3390/cancers2020262
 OPEN ACCESS
 ancers
@@ -32077,35 +27277,6 @@ ACS, Advanced Computer Systems, Via della Bufalotta 378, 00139 Rome, Italy
 Fax: +390815569693.
 Received: 23 February 2010; in revised form: 15 March 2010 / Accepted: 25 March 2010 /
 Published: 26 March 2010"
-469ee1b00f7bbfe17c698ccded6f48be398f2a44,SURVEy : Techniques for Aging Problems in Face Recognition,"MIT International Journal of Computer Science and Information Technology, Vol. 4, No. 2, August 2014, pp. 82-88
-ISSN 2230-7621©MIT Publications
-SURVEy: Techniques for
-Aging Problems in Face Recognition
-Aashmi
-Sakshi Sahni
-Sakshi Saxena
-Scholar, Computer Science Engg. Dept.
-Moradabad Institute of Technology
-Scholar, Computer Science Engg. Dept.
-Moradabad Institute of Technology
-Scholar, Computer Science Engg. Dept.
-Moradabad Institute of Technology
-Moradabad, U.P., INDIA
-Moradabad, U.P., INDIA
-Moradabad, U.P., INDIA
-E-mail:
-E-mail:
-E-mail:"
-468322e98f87a33d926aad99295acc2919b2ca0b,Wally: crowd powered image matching on tablets,"Wally – Crowd powered image matching on tablets
-Deepak Pai
-Adobe Systems India Pvt Ltd
-Bangalore
-India
-91-80-41939984
-James Davis
-UC Santa Cruz
-California
--650-799-2574"
 4640dfc0bfe7923c08d0c762a9c33b52b9029409,Head Movement and Facial Expression Transfer from 2 D Video to a 3 D Model,"Head Movement and Facial Expression Transfer
 from 2D Video to a 3D Model
 Mairead Grogan
@@ -32143,8 +27314,6 @@ Annotations
 Toru Ogawa · Atsushi Otsubo · Rei
 Narita · Yusuke Matsui · Toshihiko
 Yamasaki · Kiyoharu Aizawa"
-46f5bb35ea99c62320199b1f0924a4e7c0b001d3,Perspective-Aware CNN For Crowd Counting,"Perspective-Aware CNN For Crowd Counting
-Miaojing Shi, Zhaohui Yang, Chao Xu, Member, IEEE, and Qijun Chen, Senior Member, IEEE"
 4679f4a7da1cf45323c1c458b30d95dbed9c8896,Recognizing Facial Expressions Using Model-Based Image Interpretation,"We are IntechOpen,
 the world’s leading publisher of
 Open Access books
@@ -32208,18 +27377,6 @@ Stanford University and Max Planck Institute for Informatics"
 46fbf807f1c0c863aa35d3d8acb40870182d3b28,Multi-Instance Dynamic Ordinal Random Fields for Weakly Supervised Facial Behavior Analysis,"Multi-Instance Dynamic Ordinal Random Fields for
 Weakly-supervised Facial Behavior Analysis
 Adria Ruiz∗, Ognjen (Oggi) Rudovic†, Xavier Binefa∗ and Maja Pantic(cid:5)"
-46a553e670027e838716e5a1a39577d7cd7a4893,Face Recognition using TSF Model and DWT based Multilevel Illumination Normalization,"International Journal of Science and Research (IJSR)
-ISSN (Online): 2319-7064
-Index Copernicus Value (2013): 6.14 | Impact Factor (2014): 5.611
-Face Recognition using TSF Model and DWT based
-Multilevel Illumination Normalization
-Midhun Madhusoodanan1, Jini Cheriyan2
-M.Tech Scholar (Signal Processing), Department of Electronics and Communication, TKM Institute of Technology,
-MusaliarHills, Karuvelil P.O, Ezhukone, Kollam-691505, Kerala, India
-Assistant Professor, Department of Electronics and Communication, TKM Institute of Technology,
-Musaliar Hills, Karuvelil P.O, Ezhukone, Kollam-691505, Kerala, India
-recognition
-is  a"
 46299c9db8a4570d060ee8fc1616c4a148056365,IJCSI Publicity Board 2011,"IJCSI
 IJCSI
 International Journal of
@@ -32228,9 +27385,6 @@ Computer Science Issues
 www.IJCSI.org
 Volume 7, Issue 5, September 2010
 ISSN (Online): 1694-0814"
-46d0a519da10160a20a3070cc53e5b9401066526,Incremental Learning of Random Forests for Large-Scale Image Classification,"Incremental Learning of Random Forests for
-Large-Scale Image Classiﬁcation
-Marko Ristin, Matthieu Guillaumin, Juergen Gall, Member, IEEE and Luc Van Gool, Member, IEEE"
 46106d9f9d9b90401b7984794536e2f45fff1dbe,Learning Distance Functions for Automatic Annotation of Images,"Learning Distance Functions for
 Automatic Annotation of Images
 Josip Krapac and Fr´ed´eric Jurie
@@ -32249,10 +27403,6 @@ Associate Professor
 Department of Computer Engineering
 KKWIEER, Nashik, India.
 Savitribai Phule Pune University,Pune"
-4688787d064e59023a304f7c9af950d192ddd33e,Investigating the Discriminative Power of Keystroke Sound,"Investigating the Discriminative Power of Keystroke
-Sound
-Joseph Roth Student Member, IEEE,, Xiaoming Liu, Member, IEEE, Arun Ross, Senior Member, IEEE,
-nd Dimitris Metaxas, Member, IEEE"
 4682fee7dc045aea7177d7f3bfe344aabf153bd5,Tabula rasa: Model transfer for object category detection,"Tabula Rasa: Model Transfer for
 Object Category Detection
 Yusuf Aytar & Andrew Zisserman,
@@ -32384,12 +27534,6 @@ Sand 14, 72076 Tbingen, Germany
 Enkelejda Kasneci
 Eberhard Karls Universit¨at T¨ubingen
 Sand 14, 72076 Tbingen, Germany"
-3a4c70ca0bbd461fe2e4de3448a01f06c0217459,Accurate Vision-based Vehicle Localization using Satellite Imagery,"Accurate Vision-based Vehicle Localization using Satellite Imagery
-Hang Chu
-Hongyuan Mei
-Mohit Bansal
-Matthew R. Walter
-Toyota Technological Institute at Chicago, Chicago, IL 60637, USA"
 3a89236bb9fb3198a45089fb4a99ddba070d0cba,Image Area Reduction for Efficient Medical Image Retrieval,"Image Area Reduction for Ef‌f‌icient
 Medical Image Retrieval
 Zehra Camlica
@@ -32425,11 +27569,6 @@ Italy
 University of North Carolina Wilmington
 Master of Science in
 Computer Science and Information Systems"
-3a60678ad2b862fa7c27b11f04c93c010cc6c430,A Multimodal Database for Affect Recognition and Implicit Tagging,"JANUARY-MARCH 2012
-A Multimodal Database for
-Affect Recognition and Implicit Tagging
-Mohammad Soleymani, Member, IEEE, Jeroen Lichtenauer,
-Thierry Pun, Member, IEEE, and Maja Pantic, Fellow, IEEE"
 3acfbc2aee9b2ed246a640930ebc2e350621f990,Progressive Boosting for Class Imbalance,"Progressive Boosting for Class Imbalance
 Roghayeh Soleymania,∗, Eric Grangera, Giorgio Fumerab
 Laboratoire d’imagerie, de vision et d’intelligence artiﬁcielle, ´Ecole de technologie sup´erieure
@@ -32471,25 +27610,10 @@ Xianfeng Gu
 Dept of Comp Sci
 Stony Brook Univ
 Stony Brook, USA"
-3a564db6701cc64a4bf336e6012ada0952fed02d,Comparative Study of Diverse Face Recognition Approaches along with Intrinsic Worth and Recognition Rate,"International Journal of Computer Applications (0975 – 8887)
-Volume 179 – No.21, February 2018
-Comparative Study of Diverse Face Recognition
-Approaches along with Intrinsic Worth and Recognition
-Shivang Shukla
-Department of Computer Science
-Medi-Caps Institute of Science and Technology
-Indore, Madhya Pradesh, India
-Sourabh Dave
-Department of Information Technology
-Medi-Caps Inst. Of Science and Technology
-Indore, Madhya Pradesh, India"
 3a591a9b5c6d4c62963d7374d58c1ae79e3a4039,Driver Cell Phone Usage Detection from HOV/HOT NIR Images,"Driver Cell Phone Usage Detection From HOV/HOT NIR Images
 Yusuf Artan, Orhan Bulan, Robert P. Loce, and Peter Paul
 Xerox Research Center Webster
 800 Phillips Rd. Webster NY 14580"
-3a95eea0543cf05670e9ae28092a114e3dc3ab5c,Constructing the L2-Graph for Robust Subspace Learning and Subspace Clustering,"Constructing the L2-Graph for Robust Subspace
-Learning and Subspace Clustering
-Xi Peng, Zhiding Yu, Huajin Tang, Member, IEEE, and Zhang Yi, Senior Member, IEEE"
 3aef744dad3982a7ae1ad97b4f126b6772fc3d07,Scene-Centric Joint Parsing of Cross-View Videos,"Scene-centric Joint Parsing of Cross-view Videos
 Hang Qi1∗, Yuanlu Xu1∗, Tao Yuan1∗, Tianfu Wu2, Song-Chun Zhu1
 Dept. Computer Science and Statistics, University of California, Los Angeles (UCLA)
@@ -32503,10 +27627,6 @@ Zaragoza. 5018, María de Luna 7-8, Spain
 University of Zaragoza, Computer Science and Systems Engineering Department,
 Zaragoza. 50018, María de Luna 3, Spain
 {sballano, {ecerezo,"
-3aee6a6285869e6db48ad269eb110b542ad23c93,One-Click Annotation with Guided Hierarchical Object Detection,"One - Click Annotation with Guided Hierarchical Object Detection
-Adithya Subramanian, Anbumani Subramanian
-Intel
-Bangalore, India"
 3a9681e2e07be7b40b59c32a49a6ff4c40c962a2,"Comparing treatment means : overlapping standard errors , overlapping confidence intervals , and tests of hypothesis","Biometrics & Biostatistics International Journal
 Comparing treatment means: overlapping standard
 errors, overlapping confidence intervals, and tests of
@@ -32583,20 +27703,6 @@ Publisher: UCSD Institute for Neural Computation
 Location: The Salk Institute for Biological Studies
 La Jolla California, USA
 ISBN: 0-615-12704-5"
-3abfd884d553f91cd6c9c8b704bbeb9b49d171d3,A Hybrid Color Space for Skin Detection Using Genetic Algorithm Heuristic Search and Principal Component Analysis Technique,"RESEARCH ARTICLE
-A Hybrid Color Space for Skin Detection
-Using Genetic Algorithm Heuristic Search and
-Principal Component Analysis Technique
-Mahdi Maktabdar Oghaz*☯, Mohd Aizaini Maarof☯, Anazida Zainal☯, Mohd Foad Rohani☯,
-S. Hadi Yaghoubyan☯
-Faculty of Computing, Universiti Teknologi Malaysia, Johor Bahru, Malaysia
-☯ These authors contributed equally to this work."
-3aa98c08043558fec09bbf731cd7a8f09cf4eacf,Projective Nonnegative Matrix Factorization with α-Divergence,"Projective Nonnegative Matrix Factorization
-with α-Divergence
-Zhirong Yang and Erkki Oja
-Department of Information and Computer Science(cid:2)
-P.O. Box 5400, FI-02015, TKK, Espoo, Finland
-Helsinki University of Technology"
 3a37f57a9b94fff82ffea4e77803ebe5ebf6401b,ER7ST-algorithm for extracting facial expressions,"068                                                                 The International Arab Journal of Information Technology Vol. 13, No. 6B, 2016
 ER7ST-Algorithm for Extracting Facial Expressions
 Ahmad Tayyar1, Shadi Al-Shehabi2, and Majida AlBakoor3
@@ -32643,11 +27749,6 @@ Margaret Mitchell · Kota Yamaguchi · Karl Stratos · Amit Goyal ·
 Jesse Dodge · Alyssa Mensch · Hal Daum´e III · Alexander C. Berg ·
 Yejin Choi · Tamara L. Berg
 Received: date / Accepted: date"
-3a92a00b41dc6217f7685148c8a378524fa1a542,Human Pose Estimation Using Exemplars and Part Based Refinement,"Human Pose Estimation
-Using Exemplars and Part Based Reﬁnement
-Yanchao Su1, Haizhou Ai1, Takayoshi Yamashita2, and Shihong Lao2
-Computer Science and Technology Department, Tsinghua, Beijing 100084, China
-Core Technology Center, Omron Corporation, Kyoto 619-0283, Japan"
 3a962138ede25d81a6d5aa42aa1abba649481f10,Flow Fields: Dense Correspondence Fields for Highly Accurate Large Displacement Optical Flow Estimation,"Flow Fields: Dense Correspondence Fields for Highly Accurate Large
 Displacement Optical Flow Estimation
 Christian Bailer1
@@ -32687,11 +27788,6 @@ Aaditya Prakash and James Storer
 Brandeis University"
 3a0cceb1a10697e3e17738579d27708c9c3303a8,Data-Intensive Multimedia Semantic Concept Modeling using Robust Subspace Bagging and MapReduce,"Data-Intensive Multimedia Semantic Concept Modeling
 using Robust Subspace Bagging and MapReduce"
-3af16b0c1265cc9c8969f9c16ce65185297a2bfc,Regularizing Deep Networks by Modeling and Predicting Label Structure,"Regularizing Deep Networks by Modeling and Predicting Label Structure
-Mohammadreza Mostajabi
-Michael Maire
-Gregory Shakhnarovich
-Toyota Technological Institute at Chicago"
 3abf8e5f1f5778b99890b193de59a3a9031e3691,Revisiting Linear Discriminant Techniques in Gender Recognition,"Revisiting Linear Discriminant Techniques
 in Gender Recognition
 Juan Bekios-Calfa, Jose´ M. Buenaposada, and
@@ -32727,10 +27823,6 @@ Linguistics Meets Video Search
 Andrei Barbu∗
 N. Siddharth∗
 Jeffrey Mark Siskind∗"
-3ac09c2589178dac0b6a2ea2edf04b7629672d81,Wasserstein CNN: Learning Invariant Features for NIR-VIS Face Recognition,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2017
-Wasserstein CNN: Learning Invariant Features
-for NIR-VIS Face Recognition
-Ran He, Senior Member, IEEE, Xiang Wu, Zhenan Sun∗, Member, IEEE, and Tieniu Tan, Fellow, IEEE"
 3acdccd33e518f22dcfe36ee29c332a644afdb25,Automatic Detection of Facial Midline And Its Contributions To Facial Feature Extraction,"Electronic Letters on Computer Vision and Image Analysis 6(3):55-66, 2008
 Automatic Detection of Facial Midline
 And Its Contributions To Facial Feature Extraction
@@ -32775,16 +27867,6 @@ Junkai Chen1, Zenghai Chen1, Zheru Chi1 and Hong Fu1,2
 Department of Electronic and Information Engineering, The Hong Kong Polytechnic
 University, Hong Kong
 Department of Computer Science, Chu Hai College of Higher Education, Hong Kong"
-b501361ad3ad4f78a3966830a40d2b4f68466c80,Night-time Vehicle Detection for Automatic Headlight Beam Control,"International Journal of Computer Applications (0975 – 8887)
-Volume 157 – No 7, January 2017
-Night-time Vehicle Detection for Automatic Headlight
-Beam Control
-Pushkar Sevekar
-Student, Department of
-Electronics Engineering
-A.I.S.S.M.S. Institute of
-Information Technology,
-Pune, India"
 b5160e95192340c848370f5092602cad8a4050cd,Video Classification With CNNs: Using the Codec as a Spatio-Temporal Activity Sensor,"Video Classiﬁcation With CNNs: Using The Codec
 As A Spatio-Temporal Activity Sensor
 Aaron Chadha, Alhabib Abbas and Yiannis Andreopoulos, Senior Member, IEEE"
@@ -32793,9 +27875,6 @@ A TEACHER STUDENT NETWORK FOR FASTER VIDEO
 CLASSIFICATION
 Anonymous authors
 Paper under double-blind review"
-b54c477885d53a27039c81f028e710ca54c83f11,Semi-Supervised Kernel Mean Shift Clustering,"Semi-Supervised Kernel Mean Shift Clustering
-Saket Anand, Member, IEEE, Sushil Mittal, Member, IEEE, Oncel Tuzel, Member, IEEE,
-nd Peter Meer, Fellow, IEEE"
 b58417561ea400b60bd976104e43b1361e1314ba,Target Tracking In Real Time Surveillance Cameras and Videos,"Target Tracking In Real Time Surveillance
 Cameras and Videos
 Nayyab Naseem                                             Mehreen Sirshar
@@ -32820,18 +27899,6 @@ Abdolrahim Kadkhodamohammadi1, Afshin Gangi1,2, Michel de Mathelin1, Nicolas Pad
 ICube, University of Strasbourg, CNRS, IHU Strasbourg, France
 Radiology Department, University Hospital of Strasbourg, France
 {kadkhodamohammad, gangi, demathelin,"
-b5793958cd1654b4817ebb57f5484dfd8861f916,Recurrent Image Captioner: Describing Images with Spatial-Invariant Transformation and Attention Filtering,"Recurrent Image Captioner: Describing Images with Spatial-Invariant
-Transformation and Attention Filtering
-Hao Liu
-UESTC, China
-Yang Yang
-UESTC, China
-Fumin Shen
-UESTC, China
-Lixin Duan
-UESTC, China
-Heng Tao Shen
-UESTC, China"
 b5f7b17b0feb3a1f3af60dce61fd9a9c6b067368,The Benefits of Dense Stereo for Pedestrian Detection,"The Beneﬁts of Dense Stereo
 for Pedestrian Detection
 Christoph G. Keller, Markus Enzweiler, Marcus Rohrbach, David Fernández Llorca,
@@ -32850,9 +27917,6 @@ Emma Sumner 1
 & Hayley C. Leonard 2 & Elisabeth L. Hill 3
 # The Author(s) 2018. This article is an open access publication"
 b5d1a7bc9f89ba9e8d99f6b151f83a4ff9220bb9,"A Framework for the Segmentation and Classification of 3D Point Clouds using Temporal, Spatial and Semantic Information",
-b54f15a02d8454333ca7dbca665f7712572b56e0,Role Playing Learning for Socially Concomitant Mobile Robot Navigation,"Role Playing Learning for Socially Concomitant
-Mobile Robot Navigation
-Mingming Li, Rui Jiang, Shuzhi Sam Ge, Fellow, IEEE, and Tong Heng Lee, Member, IEEE"
 b5857b5bd6cb72508a166304f909ddc94afe53e3,SSIG and IRISA at Multimodal Person Discovery,"SSIG and IRISA at Multimodal Person Discovery
 Cassio E. dos Santos Jr1, Guillaume Gravier2, William Robson Schwartz1
 Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
@@ -32951,12 +28015,6 @@ Major Professor: Gita R. Sukthankar"
 b55853483873d3947e8c962f1152128059369d93,DoShiCo challenge: Domain shift in control prediction,"DoShiCo challenge:
 Domain Shift in Control prediction
 Klaas Kelchtermans∗ and Tinne Tuytelaars∗"
-b50f2ad8d7f08f99d4ba198120120f599f98095e,Spatiotemporal data fusion for precipitation nowcasting,"Spatiotemporal data fusion for precipitation
-nowcasting
-Vladimir Ivashkin
-Yandex, Moscow, Russia
-Vadim Lebedev
-Yandex, Moscow, Russia"
 b525a863eab597055e02351acfeab64754d22690,Pictorial Structures Revisited : Multiple Human Pose Estimation,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
 D Pictorial Structures Revisited:
 Multiple Human Pose Estimation
@@ -32981,9 +28039,6 @@ Comparison of face Recognition Algorithms on
 Dummy Faces
 Aruni Singh, Sanjay Kumar Singh, Shrikant Tiwari
 Department of Computer Engineering, IT-BHU, Varanasi-India"
-b5050d74dd8f0384506bcd365b31044c80d476c0,Discriminative Multimetric Learning for Kinship Verification,"Discriminative Multimetric Learning
-for Kinship Veriﬁcation
-Haibin Yan, Jiwen Lu, Member, IEEE, Weihong Deng, and Xiuzhuang Zhou, Member, IEEE"
 b5d14fee9658877abbbfa760dd9765db0af86ba6,Swarm intelligence and evolutionary computation approaches for 2 D face recognition : a systematic review,"Revista Brasileira de Computação Aplicada, July, 2018
 DOI: 10.5335/rbca.v10i2.8046
 Vol. 10, No 2, pp. 2–17
@@ -33017,26 +28072,6 @@ Andreas Ess · Konrad Schindler · Bastian Leibe · Luc Van Gool"
 b52886610eda6265a2c1aaf04ce209c047432b6d,Microexpression Identification and Categorization Using a Facial Dynamics Map,"Microexpression Identiﬁcation and Categorization
 using a Facial Dynamics Map
 Feng Xu, Junping Zhang, James Z. Wang"
-b55489547790f7fb2c8b4689530b5660fbc8ee64,Face Scanning in Autism Spectrum Disorder and Attention Deficit/Hyperactivity Disorder: Human Versus Dog Face Scanning,"ORIGINAL RESEARCH
-published: 23 October 2015
-doi: 10.3389/fpsyt.2015.00150
-Face scanning in autism spectrum
-disorder and attention deficit/
-hyperactivity disorder: human
-versus dog face scanning
-Mauro Muszkat 1, Claudia Berlim de Mello 2, Patricia de Oliveira Lima Muñoz 3,
-Tania Kiehl Lucci 3, Vinicius Frayze David 3, José de Oliveira Siqueira 3 and Emma Otta 3*
-Departamento de Psicobiologia, Universidade Federal de São Paulo, São Paulo, Brazil, 2 Programa de Pós Graduação em
-Educação e Saúde, Universidade Federal de São Paulo, São Paulo, Brazil, 3 Departamento de Psicologia Experimental,
-Instituto de Psicologia, Universidade de São Paulo, São Paulo, Brazil
-This study used eye tracking to explore attention allocation to human and dog faces in chil-
-dren and adolescents with autism spectrum disorder (ASD), attention deficit/hyperactivity
-disorder (ADHD), and typical development (TD). Significant differences were found among
-the three groups. TD participants looked longer at the eyes than ASD and ADHD ones,
-irrespective of the faces presented. In spite of this difference, groups were similar in that
-they looked more to the eyes than to the mouth areas of interest. The ADHD group gazed
-longer at the mouth region than the other groups. Furthermore, groups were also similar
-in that they looked more to the dog than to the human faces. The eye-tracking tech-"
 b5dd744df6de73bd072b18d9108b79431a28c539,Gait Recognition With Shifted Energy Image and Structural Feature Extraction,"Gait Recognition with Shifted Energy Image
 nd Structural Feature Extraction
 Xiaxi Huang and Nikolaos V. Boulgouris, Senior Member, IEEE"
@@ -33081,26 +28116,6 @@ d745eaeb096fbf61ac0694e447acd2081a08b084,Ðáñáêïëïýèçóç
 ÄÉÄÁÊÔÏÑÉÊÏÕ ÄÉÐËÙÌÁÔÏÓ ÓÔÇÍ ÐËÇÑÏÖÏÑÉÊÇ
 ÄåêÝìâñéïò 2009"
 d7da0f595d135474cc2193d382b22458b313cdbf,Multi-View Constraint Propagation with Consensus Prior Knowledge.,Multi-View Constraint Propagation with Consensus Prior Knowledge
-d7d90d768c4770c356901f20077af9ad27efdfd0,Real-time dense map fusion for stereo SLAM,"doi:10.1017/xxxx
-Real-time Dense Map Fusion for Stereo SLAM
-Taih´u Pire†∗, Rodrigo Baravalle†, Ariel D’Alessandro† and
-Javier Civera‡
-CIFASIS, French Argentine International Center for Information and Systems
-Sciences (CONICET-UNR), Argentina
-University of Zaragoza, Spain
-(Accepted MONTH DAY, YEAR. First published online: MONTH DAY, YEAR)
-SUMMARY
-A robot should be able to estimate an accurate and dense 3D model of its environment
-(a map), along with its pose relative to it, all of it in real time, in order to be able to
-navigate autonomously without collisions.
-As the robot moves from its starting position and the estimated map grows, the
-omputational and memory footprint of a dense 3D map increases and might exceed the
-robot capabilities in a short time. However, a global map is still needed to maintain its
-onsistency and plan for distant goals, possibly out of the robot ﬁeld of view.
-In this work we address such problem by proposing a real-time stereo mapping pipeline,
-feasible for standard CPUs, which is locally dense and globally sparse and accurate. Our
-lgorithm is based on a graph relating poses and salient visual points, in order to maintain
-long-term accuracy with a small cost. Within such framework, we propose an ef‌f‌icient"
 d7c659ce0442bf1047e7d2e942837b18105f6f47,Depth-Adaptive Deep Neural Network for Semantic Segmentation,"Depth Adaptive Deep Neural Network
 for Semantic Segmentation
 Byeongkeun Kang, Yeejin Lee, and Truong Q. Nguyen, Fellow, IEEE"
@@ -33117,32 +28132,6 @@ Stefano Pini, Guido Borghi, Roberto Vezzani, Rita Cucchiara
 University of Modena and Reggio Emilia
 Figure 1: Sample frames synthesized by the proposed framework. Given an initial RGB frame at time t0 and a set of following
 event frames at time t1, ..., tn as input, the proposed framework accordingly synthesizes a RGB frame for each time step."
-d7453fa0c70a15681e76b509fff6e1dd49f5a4a5,Indian Classical Dance Action Identification and Classification with Convolutional Neural Networks,"Hindawi
-Advances in Multimedia
-Volume 2018, Article ID 5141402, 10 pages
-https://doi.org/10.1155/2018/5141402
-Research Article
-Indian Classical Dance Action Identification and Classification
-with Convolutional Neural Networks
-, K. V. V. Kumar
-, A. S. C. S. Sastry,
-P. V. V. Kishore
-M. Teja Kiran , D. Anil Kumar
-Department of Electronics and Communication Engineering, KL University, Vaddeswaram, Guntur, India
-, and M. V. D. Prasad
-, E. Kiran Kumar
-Correspondence should be addressed to P. V. V. Kishore;
-Received 13 October 2017; Accepted 20 December 2017; Published 22 January 2018
-Academic Editor: Lin Wu
-Copyright © 2018 P. V. V. Kishore et al. This is an open access article distributed under the Creative Commons Attribution License,
-which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
-Extracting and recognizing complex human movements from unconstrained online/offline video sequence is a challenging task"
-d7fe2a52d0ad915b78330340a8111e0b5a66513a,Photo-to-Caricature Translation on Faces in the Wild,"Unpaired Photo-to-Caricature Translation on Faces in
-the Wild
-Ziqiang Zhenga, Chao Wanga, Zhibin Yua, Nan Wanga, Haiyong Zhenga,∗,
-Bing Zhenga
-No. 238 Songling Road, Department of Electronic Engineering, Ocean University of
-China, Qingdao, China"
 d7f7eb0fbe3339d13f5a6a23df0fd27fdb357d48,Intention-Aware Multi-Human Tracking for Human-Robot Interaction via Particle Filtering over Sets,"Intention-Aware Multi-Human Tracking for
 Human-Robot Interaction via Particle Filtering over Sets
 Aijun Bai
@@ -33206,15 +28195,6 @@ Suhelah Sandokji1, Fathy Eassa2
 Faculty of Computing and Information Technology, KAU
 Jeddah ,Saudi Arabia
 studies  consider  partitioning"
-d7731565ec4cb1b910290ccb580405cb55224286,Robust Face Recognition via Adaptive Sparse Representation,"Robust Face Recognition via Adaptive Sparse
-Representation
-Jing Wang, Canyi Lu, Meng Wang, Member, IEEE, Peipei Li,
-Shuicheng Yan, Senior Member, IEEE, Xuegang Hu"
-d73221adda13a99e8dd8dab101abcfeae6b7b706,The ApolloScape Dataset for Autonomous Driving,"The ApolloScape Dataset for Autonomous Driving
-Xinyu Huang, Xinjing Cheng, Qichuan Geng, Binbin Cao,
-Dingfu Zhou, Peng Wang, Yuanqing Lin, and Ruigang Yang
-Baidu Research, Beijing, China
-National Engineering Laboratory of Deep Learning Technology and Application, China"
 d745cf8c51032996b5fee6b19e1b5321c14797eb,Viewpoint Invariant Pedestrian Recognition with an Ensemble of Localized Features,"Viewpoint Invariant Pedestrian Recognition
 with an Ensemble of Localized Features
 Douglas Gray and Hai Tao
@@ -33332,13 +28312,6 @@ d7f153112c51923c8e78036fc694220c9d4bf4bc,The 2018 DAVIS Challenge on Video Objec
 Video Object Segmentation
 Sergi Caelles, Alberto Montes, Kevis-Kokitsi Maninis, Yuhua Chen,
 Luc Van Gool, Federico Perazzi, and Jordi Pont-Tuset"
-d79121a03584123fad02c4f2607f0e63d08ff7c2,Tracking Occluded Objects and Recovering Incomplete Trajectories by Reasoning About Containment Relations and Human Actions,"Tracking Occluded Objects and Recovering Incomplete Trajectories
-y Reasoning about Containment Relations and Human Actions
-Wei Liang1,2
-Yixin Zhu2
-Song-Chun Zhu2
-Beijing Laboratory of Intelligent Information Technology, Beijing Institute of Technology, China
-Center for Vision, Cognition, Learning, and Autonomy, University of California, Los Angeles, USA"
 d7b850537ccf33cabc2f0b231553aad79ad43aa8,Grid Map based Free Space Estimation using Stereo Vision,"Grid Map based Free Space Estimation using Stereo Vision
 Hannes Harms1, Eike Rehder1 and Martin Lauer1"
 d7e8c6da1a95f41d8097b7b713890ccde13ef1d8,Development of an Efficient Face Recognition System Based on Linear and Nonlinear Algorithms,"Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms
@@ -33551,17 +28524,6 @@ RESIDUAL NETWORKS
 REGULARIZATION OF
 -BRANCH
 Xavier Gastaldi"
-220d62414053519f7b9a6aecb4aa9f775014c98c,Incremental Feature Transformation for Temporal Space,"Incremental Feature Transformation for Temporal Space
-International Journal of Computer Applications (0975 – 8887)
-Volume 145 – No.8, July 2016
-Preeti Mahadev
-University of Mysore,
-Mysuru, Karnataka,
-India
-P. Nagabhushan
-University of Mysore,
-Mysuru, Karnataka,
-India"
 22137ce9c01a8fdebf92ef35407a5a5d18730dde,Recognition of Faces from single and Multi-View Videos,
 227b1a09b942eaf130d1d84cdcabf98921780a22,Multi-feature shape regression for face alignment,"Yang et al. EURASIP Journal on Advances in Signal Processing  (2018) 2018:51
 https://doi.org/10.1186/s13634-018-0572-6
@@ -33586,10 +28548,6 @@ Pulkit Agrawal
 UC Berkeley
 Jitendra Malik
 UC Berkeley"
-224868cc607dc38b7eca8536018580c577f9fedf,Exploring Temporal Patterns in Classifying Frustrated and Delighted Smiles,"IEEE TRANSACTIONS ON AFFECTIVE COMPUTING, MANUSCRIPT ID
-Exploring Temporal Patterns in Classifying
-Frustrated and Delighted Smiles
-Mohammed E. Hoque, Daniel J. McDuff, and Rosalind W. Picard, Member, IEEE"
 22d656a6395e22473b8764eddff759ea03f48032,Nonrigid Image Registration Using Higher-Order MRF Model with Dense Local Descriptor,"Nonrigid Image Registration Using Higher-Order MRF Model
 with Dense Local Descriptor
 Dongjin Kwon1, Kyong Joon Lee1, Il Dong Yun2, and Sang Uk Lee1
@@ -33643,26 +28601,6 @@ September 2011
 ANU Computer Science Technical Report Series"
 22c89775cb5309eae5ac1f9ce9d1c2d569439492,Face recognition based on extended separable lattice 2-D HMMS,"978-1-4673-0046-9/12/$26.00 ©2012 IEEE
 ICASSP 2012"
-224fc841ad5b6766f828fe54f00e4f6153354627,Privacy preserving optics for miniature vision sensors,"Privacy Preserving Optics for Miniature Vision Sensors
-Francesco Pittaluga1, Sanjeev J. Koppal2
-,2Department of Electrical and Computer Engineering, University of Florida.
-We present a novel framework, which enables ”pre-capture” privacy, for
-miniature vision sensors. Most privacy preserving systems for computer
-vision, process images after capture. There exists a moment of vulnerabil-
-ity in such systems, after capture, when privacy has not yet been enforced.
-Our privacy sensors ﬁlter the incident light-ﬁeld before image capture, while
-light passes through the sensor optics, so sensitive information is never mea-
-sured by the sensor. Within this framework, we introduce, to our knowledge,
-the ﬁrst ever sensor that enables pre-capture k-anonymity and multiple sen-
-sors that achieve pre-capture privacy through optical defocus. We also show
-theory for miniaturizing the proposed designs, including a novel ”optical
-knapsack” solution for ﬁnding a ﬁeld-of-view-optimal arrangement of op-
-tical elements. Our privacy preserving sensors enable applications such as
-ccurate depth sensing, full-body motion tracking, multiple people tracking
-nd low-power blob detection.
-Related Work. Ad hoc privacy preserving algorithms for video data, such
-s naive blurring, trade off data utility for privacy protection, as they rely
-on heavy distortion of the data, to thwart restoration attacks [3]. In con-"
 224ffad672f7e6c7995780eb9bd3c8a141cb25cd,Understanding pedestrian behaviors from stationary crowd groups,"Understanding Pedestrian Behaviors from Stationary Crowd Groups
 Shuai Yi1, Hongsheng Li1,2, Xiaogang Wang1
 Department of Electronic Engineering, The Chinese University of Hong Kong.
@@ -33683,16 +28621,6 @@ to model pedestrian behaviors.
 The Proposed Pedestrian Behavior Model
 A general energy map M is proposed to model the traveling difﬁculty of
 every location of the scene. It can be modeled with three channels calculated"
-2236294e803316c5934fa387f27d128fa7819a03,Iterative Human Pose Estimation based on A New Part Appearance Model,"Appl. Math. Inf. Sci. 8, No. 1L, 311-317 (2014)
-Applied Mathematics & Information Sciences
-An International Journal
-http://dx.doi.org/10.12785/amis/081L39
-Iterative Human Pose Estimation based on A New Part
-Appearance Model
-Wang Hao, Meng Fanhui and Fang Baofu∗
-School of Computer and Information, Hefei Universty of Technology, Hefei, China
-Received: 15 May. 2013, Revised: 9 Sep. 2013, Accepted: 10 Sep. 2013
-Published online: 1 Apr. 2014"
 22355c1b0a8af6b9e1cc2ef3fd5dce08edc48dd5,Learning to Detect Vehicles by Clustering Appearance Patterns,"(cid:13)2015IEEE.Personaluseofthismaterialispermitted.PermissionfromIEEEmustbeobtainedforallotheruses,inanycurrentorfuturemedia,includingreprinting/republishingthismaterialforadvertisingorpromotionalpurposes,creatingnewcollectiveworks,forresaleorredistributiontoserversorlists,orreuseofanycopyrightedcomponentofthisworkinotherworks."
 225f09fd8103626c486ea9bfcd3770858dcf1906,Strangeness Based Feature Selection for Part Based Recognition,"Strangeness Based Feature Selection for Part Based Recognition
 Fayin Li and Jana Koˇseck´a and Harry Wechsler
@@ -33730,13 +28658,6 @@ KyungHyun Cho, Tapani Raiko and Alexander Ilin
 Department of Information and Computer Science,
 Aalto University School of Science
 Email:"
-224547337e1ace6411a69c2e06ce538bc67923f7,Convolutional Neural Network for Camera Pose Estimation from Object Detections,"CONVOLUTIONAL NEURAL NETWORK FOR CAMERA POSE ESTIMATION FROM
-OBJECT DETECTIONS
-E. V. Shalnova, A. S. Konushina,b
-MSU, Faculty of Computational Mathematics and Cybernetics, Russia, 119991, Moscow, GSP-1, 1-52, Leninskiye Gory, -
-HSE, Faculty of Computer Science, Russia, 125319, Moscow, 3, Kochnovsky Proezd
-KEY WORDS: Camera Pose, CNN, Head Detection, Computer Graphics
-Commission II, WG II/5"
 221debbd7878ed303eaa4666f8df04a48e4c5070,Making Computer Vision Computationally Efficient,"Making computer vision computationally efficient
 Narayanan Sundaram
 Electrical Engineering and Computer Sciences
@@ -33753,42 +28674,8 @@ Zhe Lin2
 Adobe Research
 Li Zhang1
 http://www.cs.wisc.edu/~lizhang/projects/face-landmark-localization/"
-22029de24dbf6867658145264f36b161c40a09d8,A Discriminative Representation of Convolutional Features for Indoor Scene Recognition,"A Discriminative Representation of Convolutional
-Features for Indoor Scene Recognition
-S. H. Khan, M. Hayat, M. Bennamoun, Member, IEEE, R. Togneri, and F. Sohel, Senior Member, IEEE"
-7c1e1c767f7911a390d49bed4f73952df8445936,Non-Rigid Object Detection with LocalInterleaved Sequential Alignment (LISA),"NON-RIGID OBJECT DETECTION WITH LOCAL INTERLEAVED SEQUENTIAL ALIGNMENT (LISA)
-Non-Rigid Object Detection with Local
-Interleaved Sequential Alignment (LISA)
-Karel Zimmermann, Member, IEEE,, David Hurych, Member, IEEE,
-nd Tom´aˇs Svoboda, Member, IEEE"
-7cee2a2bee27657e6599b13f9ed6536d5f46fd0a,A Semantic Labeling Approach for Accurate Weed Mapping of High Resolution UAV Imagery,"Article
-A Semantic Labeling Approach for Accurate Weed
-Mapping of High Resolution UAV Imagery
-Huasheng Huang 1,2,†, Yubin Lan 1,2,†, Jizhong Deng 1,2,*, Aqing Yang 3, Xiaoling Deng 2,3,
-Lei Zhang 2,4 and Sheng Wen 2,5
-College of Engineering, South China Agricultural University, Wushan Road, Guangzhou 510642, China;
-(H.H.); (Y.L.)
-National Center for International Collaboration Research on Precision Agricultural Aviation Pesticide
-Spraying Technology, Wushan Road, Guangzhou 510642, China; (X.D.);
-(L.Z.); (S.W.)
-College of Electronic Engineering, South China Agricultural University, Wushan Road, Guangzhou 516042,
-China;
-College of Agriculture, South China Agricultural University, Wushan Road, Guangzhou 516042, China
-Engineering Fundamental Teaching and Training Center, South China Agricultural University,
-Wushan Road, Guangzhou 510642, China
-* Correspondence: Tel.: +86-20-8528-8201
-These authors contributed equally to this work and should be considered as co-ﬁrst authors.
-Received: 13 May 2018; Accepted: 27 June 2018; Published: 1 July 2018"
 7c8d57ca9cbefd1c2b3f4d45ab6791adba2d6bb4,Two-Stage Hashing for Fast Document Retrieval,"Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Short Papers), pages 495–500,
 Baltimore, Maryland, USA, June 23-25 2014. c(cid:13)2014 Association for Computational Linguistics"
-7c9d8593cdf2f8ba9f27906b2b5827b145631a0b,MsCGAN: Multi-scale Conditional Generative Adversarial Networks for Person Image Generation,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, OCTOBER 2018
-MsCGAN: Multi-scale Conditional Generative
-Adversarial Networks for Person Image
-Generation
-Wei Tang∗, Teng Li 
-† Anhui University, HeFei, China
-Hefei University, HeFei, China
-§ Hefei University of Technology, HeFei, China"
 7c2f2080473d25db73c53869337afb79d2135731,"Remondino , Gerke 75 Oblique Aerial Imagery – A Review","Remondino, Gerke
 Oblique Aerial Imagery – A Review
 Fabio Remondino, Trento
@@ -33809,13 +28696,6 @@ Dongning Wang
 Glenn M. Fung
 American Family Insurance, Strategic Data & Analytics, Madison, WI
 {lpolania, dwang1,"
-7c0f7d47da05a41e8671b059ade70dd2df7070db,Face Recognition and Feature Detection Using Artificial Neural Networks and ANFIS,"International Journal of Emerging Technology and Advanced Engineering
-Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 5, Issue 7, July 2015)
-Face Recognition and Feature Detection Using Artificial
-Neural Networks and ANFIS
-Sanjay Kumar Dekate1, Dr. Anupam Shukla2
-Research Scholar, Dr. C. V. Raman University, Bilaspur, India
-Professor, ABV-IIITM, Gwalior, India"
 7c26559e7269679ef52a85d02c6ff7000c2387d2,Towards a Development of a Learners’ Ratified Acceptance of Multi-biometrics Intentions Model (RAMIM): Initial Empirical Results,"Yair Levy, Michelle M. Ramim
 Towards a Development of a Learners’ Ratified
 Acceptance of Multi-biometrics Intentions Model
@@ -33840,25 +28720,9 @@ Anirudh Vemula, Katharina Muelling and Jean Oh"
 7c4864065f4e107cb5be49a8dba8cf7d94b8340f,Multi-target Tracking by Lagrangian Relaxation to Min-cost Network Flow,"Multi-target Tracking by Lagrangian Relaxation to Min-Cost Network Flow
 Asad A. Butt and Robert T. Collins
 The Pennsylvania State University, University Park, PA. 16802, USA"
-7c47da191f935811f269f9ba3c59556c48282e80,Robust eye centers localization with zero-crossing encoded image projections,"Robust Eye Centers Localization
-with Zero–Crossing Encoded Image Projections
-Laura Florea
-Image Processing and Analysis Laboratory
-University ”Politehnica” of Bucharest, Romania, Address Splaiul Independent¸ei 313
-Corneliu Florea
-Image Processing and Analysis Laboratory
-University ”Politehnica” of Bucharest, Romania, Address Splaiul Independent¸ei 313
-Constantin Vertan
-Image Processing and Analysis Laboratory
-University ”Politehnica” of Bucharest, Romania, Address Splaiul Independent¸ei 313"
 7c7af300c4780ad01e7db4d60fbf89771672585b,Detection and Segmentation of Manufacturing Defects with Convolutional Neural Networks and Transfer Learning,"Detection and Segmentation of Manufacturing Defects with
 Convolutional Neural Networks and Transfer Learning
 Max Ferguson1 Ronay Ak2 Yung-Tsun Tina Lee2 and Kincho. H. Law1"
-7c0a6824b556696ad7bdc6623d742687655852db,MPCA+MDA: A novel approach for face recognition based on tensor objects,"8th Telecommunications forum TELFOR 2010
-Serbia, Belgrade, November 23-25, 2010.
-MPCA+DATER: A Novel Approach for Face
-Recognition Based on Tensor Objects
-Ali. A. Shams Baboli, Member, IEEE, G. Rezai-rad, Member, IEEE, Aref. Shams Baboli"
 7cda4fc187f446a52cc5c9ac0e6a0752c1f0d5e9,Domain-Specific Approximation for Object Detection,"© 2018 IEEE. DOI: 10.1109/MM.2018.112130335
 © 2018 IEEE. Personal use of this material is permitted.
 Permission from IEEE must be obtained for all other uses, in
@@ -33868,10 +28732,6 @@ promotional purposes, creating new collective works, for
 resale or redistribution to servers or lists, or reuse of any
 opyrighted component of this work in other works. DOI:
 0.1109/MM.2018.112130335"
-7c1db13ae2c62d1f860fd2664885c9c93a28cab8,Multistage Particle Windows for Fast and Accurate Object Detection,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication.
-Multi-Stage Particle Windows for Fast and
-Accurate Object Detection
-Giovanni Gualdi, Andrea Prati, Member, IEEE, and Rita Cucchiara, Member, IEEE"
 7c98c27f4be40a7675ba9c85179ce72d12593a7a,Training Bit Fully Convolutional Network for Fast Semantic Segmentation,"Training Bit Fully Convolutional Network for Fast Semantic Segmentation
 He Wen and Shuchang Zhou and Zhe Liang and Yuxiang Zhang and Dieqiao Feng and Xinyu Zhou and Cong Yao
 {wenhe, zsc, liangzhe, zyx, fdq, zxy,
@@ -33897,20 +28757,6 @@ for fast Object Detection
 Marco Pedersoli, Jordi Gonz`alez, Andrew D. Bagdanov, and Juan J. Villanueva
 Dept. Ci`encies de la Computaci´o & Centre de Visi´o per Computador,
 Ediﬁci O, Campus UAB 08193 Bellaterra (Cerdanyola) Barcelona, Spain"
-7cd5d849212c294c452be009ff465ca7d3d923c8,A Brief Survey of Face Recognition Techniques,"(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:2)(cid:2)(cid:3)(cid:3)(cid:4)(cid:4)(cid:5)(cid:5)(cid:6)(cid:6)(cid:7)(cid:7)(cid:1)(cid:1)(cid:8)(cid:8)(cid:1)(cid:1)(cid:9)(cid:9)(cid:1)(cid:1)(cid:10)(cid:10)(cid:5)(cid:5)(cid:6)(cid:6)(cid:11)(cid:11)(cid:7)(cid:7)(cid:12)(cid:12)(cid:1)(cid:1)(cid:13)(cid:13)(cid:1)(cid:1)(cid:14)(cid:14)(cid:15)(cid:15)(cid:12)(cid:12)(cid:16)(cid:16)(cid:17)(cid:17)(cid:1)(cid:1)(cid:13)(cid:13)(cid:18)(cid:18)(cid:19)(cid:19)(cid:20)(cid:20)(cid:1)(cid:1)(cid:21)(cid:21)(cid:1)(cid:1)(cid:22)(cid:22)(cid:7)(cid:7)(cid:23)(cid:23)(cid:24)(cid:24)(cid:1)(cid:1)(cid:13)(cid:13)(cid:18)(cid:18)(cid:19)(cid:19)(cid:20)(cid:20)(cid:1)(cid:1)(cid:23)(cid:23)(cid:23)(cid:23)(cid:25)(cid:25)(cid:1)(cid:1)(cid:13)(cid:13)(cid:18)(cid:18)(cid:21)(cid:21)(cid:26)(cid:26)(cid:27)(cid:27)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)
-(cid:15)(cid:15)(cid:28)(cid:28)(cid:15)(cid:15)(cid:29)(cid:29)(cid:4)(cid:4)(cid:15)(cid:15)(cid:11)(cid:11)(cid:4)(cid:4)(cid:7)(cid:7)(cid:1)(cid:1)(cid:3)(cid:3)(cid:30)(cid:30)(cid:4)(cid:4)(cid:29)(cid:29)(cid:30)(cid:30)(cid:7)(cid:7)(cid:1)(cid:1)(cid:15)(cid:15)(cid:24)(cid:24)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:1)(cid:31)(cid:31)(cid:31)(cid:31)(cid:31)(cid:31)(cid:25)(cid:25)(cid:16)(cid:16)  !!(cid:3)(cid:3)(cid:5)(cid:5)(cid:12)(cid:12)(cid:30)(cid:30)(cid:15)(cid:15)(cid:4)(cid:4)    (cid:25)(cid:25)(cid:16)(cid:16)(cid:3)(cid:3)(cid:6)(cid:6)(cid:1)
-(cid:1)
-(cid:1)
-AA  BBrriieeff  SSuurrvveeyy  ooff  FFaaccee  RReeccooggnniittiioonn  TTeecchhnniiqquueess
-Nilam B. Goswami, Pinal Patel, Chirag I. Patel, Parth Parekh
-Post Graduation, CE and IT department, Government Engineering College, Gandhinagar, India"
-7c119e6bdada2882baca232da76c35ae9b5277f8,Facial expression recognition using embedded Hidden Markov Model,"Facial Expression Recognition Using Embedded
-Hidden Markov Model
-Languang He, Xuan Wang, Member, IEEE, Chenglong Yu, Member, IEEE, Kun Wu
-Intelligence Computing Research Center
-HIT Shenzhen Graduate School
-Shenzhen, China
-{telent, wangxuan, ycl, wukun}"
 7c7158273f0f833329ad86f7f642aedeb161a73c,A video database of human faces under near Infra-Red illumination for human computer interaction applications,"A Video Database of Human Faces under Near Infra-Red
 Illumination for Human Computer Interaction Aplications
 S L Happy, Anirban Dasgupta, Anjith George, and Aurobinda Routray
@@ -33946,11 +28792,6 @@ ReDMark: Framework for Residual Diffusion
 Watermarking based on Deep Networks
 Mahdi Ahmadi, Alireza Norouzi, S.M.Reza Soroushmehr, Nader Karimi,
 Kayvan Najarian, Shadrokh Samavi and Ali Emami"
-7cee802e083c5e1731ee50e731f23c9b12da7d36,2^B3^C: 2 Box 3 Crop of Facial Image for Gender Classification with Convolutional Networks,"B3C: 2 Box 3 Crop of Facial Image for Gender Classification with Convolutional
-Networks
-Vandit Gajjar
-Department of Electronics and Communication Engineering and
-Computer Vision Group, L. D. College of Engineering, Ahmedabad, India"
 7c25ed788da1f5f61d8d1da23dd319dfb4e5ac2d,Human-In-The-Loop Person Re-Identification,"Human-In-The-Loop Person Re-Identiﬁcation
 Hanxiao Wang, Shaogang Gong, Xiatian Zhu, and Tao Xiang"
 7c45b5824645ba6d96beec17ca8ecfb22dfcdd7f,News Image Annotation on a Large Parallel Text-image Corpus.,"News image annotation on a large parallel text-image corpus
@@ -33958,16 +28799,6 @@ Pierre Tirilly, Vincent Claveau, Patrick Gros
 Universit´e de Rennes 1/IRISA, CNRS/IRISA, INRIA Rennes-Bretagne Atlantique
 Campus de Beaulieu
 5042 Rennes Cedex, France"
-7cb569246ade0393a0ccf2cd0f9fd01921569ecd,An Exploratory Survey on Various Face Recognition Methods Using Component Analysis,"ISSN (Print)    : 2319-5940
-ISSN (Online) : 2278-1021
-International Journal of Advanced Research in Computer and Communication Engineering
-Vol. 2, Issue 5, May 2013
-An Exploratory Survey on Various Face
-Recognition Methods Using Component Analysis
-Shamna P1, Paul Augustine2, Tripti C3
-M.Tech Scholar, Dept of CSE, Rajagiri School of Engineering and Technology, Kochi, India1
-Asst. Professor, Dept of CSE, Rajagiri School of Engineering and Technology, Kochi, India2
-Asst. Professor, Dept of CSE, Rajagiri School of Engineering and Technology, Kochi, India3"
 7c1802d8d43dfe783650a03f03d41609fa5ae91e,Discriminability Objective for Training Descriptive Captions,"Discriminability objective for training descriptive captions
 Ruotian Luo
 TTI-Chicago
@@ -34033,17 +28864,9 @@ Enrico Piazza1 Andrea Romanoni1 Matteo Matteucci1"
 Ra´ul Mart´ın-F´elez, Ram´on A. Mollineda, and J. Salvador S´anchez
 Institute of New Imaging Technologies (INIT)
 Universitat Jaume I. Av. Sos Baynat s/n, 12071, Castell´o de la Plana, Spain"
-519f4eb5fe15a25a46f1a49e2632b12a3b18c94d,Non-Lambertian Reflectance Modeling and Shape Recovery of Faces Using Tensor Splines,"Non-Lambertian Reflectance Modeling and
-Shape Recovery of Faces using Tensor Splines
-Ritwik Kumar, Student Member, IEEE, Angelos Barmpoutis, Member, IEEE,
-Arunava Banerjee, Member, IEEE, and Baba C. Vemuri, Fellow, IEEE"
 51bfc693d170b4171f5bd9f9aed51f1fe8b5304d,Zero-shot Recognition via Direct Classifier Learning with Transferred Samples and Pseudo Labels AAAI Anonymous Submission 182,"Zero-shot Recognition via Direct Classiﬁer Learning
 with Transferred Samples and Pseudo Labels
 AAAI Anonymous Submission 182"
-513d9d0fdc9efa0f042ed1a3c8eab1fbb564f67b,Efficient Processing of Deep Neural Networks: A Tutorial and Survey,"Efﬁcient Processing of Deep Neural Networks:
-A Tutorial and Survey
-Vivienne Sze, Senior Member, IEEE, Yu-Hsin Chen, Student Member, IEEE, Tien-Ju Yang, Student
-Member, IEEE, Joel Emer, Fellow, IEEE"
 5121f42de7cb9e41f93646e087df82b573b23311,Classifying Online Dating Profiles on Tinder using FaceNet Facial Embeddings,"CLASSIFYING ONLINE DATING PROFILES ON TINDER USING FACENET FACIAL
 EMBEDDINGS
 Charles F. Jekel and Raphael T. Haftka
@@ -34101,10 +28924,6 @@ Sorbonne Universit´es, UPMC Univ Paris 06, UMR 7606, LIP6, F-75005, Paris, Fran
 Prajjwal Bhargava
 SRM University
 Chennai"
-519db7bb7d1778bddfbe3725220756627373d69a,A Comparative Study of Local Matching Approach for Face Recognition,"A Comparative Study of Local Matching
-Approach for Face Recognition
-Jie Zou, Member, IEEE, Qiang Ji, Senior Member, IEEE, and George Nagy, Fellow, IEEE
-to holistic methods,"
 51d97f4e4385a3da78bf9277a5426216198698c3,Improving the Accuracy of Face Detection for Damaged Video and Distant Targets,"Improving the Accuracy of Face Detection for Damaged Video and
 Distant Targets
 Department of Communication Engineering, Oriental Institute of Technology, New Taiepi City, Taiwan
@@ -34157,9 +28976,6 @@ Media Security and IT Forensics – Fraunhofer Institute for Secure Information
 51cf3fa26b7c31c10427317fb5d72a6712023279,What Shape Is Your Conjugate? A Survey of Computational Convex Analysis and Its Applications,"A SURVEY OF COMPUTATIONAL CONVEX ANALYSIS AND ITS APPLICATIONS
 WHAT SHAPE IS YOUR CONJUGATE?
 YVES LUCET"
-5157dde17a69f12c51186ffc20a0a6c6847f1a29,Evolutionary Cost-sensitive Extreme Learning Machine and Subspace Extension,"Evolutionary Cost-sensitive Extreme Learning
-Machine
-Lei Zhang, Member, IEEE, and David Zhang, Fellow, IEEE"
 51a9f9dcffad494cb88b949b7e98e7e11240a015,A Hybrid Face Recognition Approach Using GPUMLib,"A Hybrid Face Recognition Approach Using
 GPUMLib
 Noel Lopes1,2 and Bernardete Ribeiro1
@@ -34202,14 +29018,6 @@ Shared Randomized Vocabularies
 (1 / 44)"
 5146832515ba8b4ad48372967d9fb7dcdea61869,CUNI System for WMT16 Automatic Post-Editing and Multimodal Translation Tasks,"Proceedings of the First Conference on Machine Translation, Volume 2: Shared Task Papers, pages 646–654,
 Berlin, Germany, August 11-12, 2016. c(cid:13)2016 Association for Computational Linguistics"
-516a27d5dd06622f872f5ef334313350745eadc3,Fine-Grained Facial Expression Analysis Using Dimensional Emotion Model,"> REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) <
-Fine-Grained Facial Expression Analysis Us-
-ing Dimensional Emotion Model
-ǂFeng Zhou, ǂShu Kong, Charless C. Fowlkes, Tao Chen, *Baiying Lei, Member, IEEE"
-517cc1084952133b6d2ecd0a535cdc3ddf8955d7,A Graphical Social Topology Model for Multi-Object Tracking,"A Graphical Social Topology Model for
-Multi-Object Tracking
-Shan Gao, Xiaogang Chen, Qixiang Ye, Senior Member, IEEE, Arjan Kuijper, Member, IEEE,
-Xiangyang Ji, Member, IEEE,"
 51ab92566306c2f26e8415b451f3dd1f83f59008,The USC CreativeIT database of multimodal dyadic interactions: from speech and full body motion capture to continuous emotional annotations,"The USC CreativeIT Database of Multimodal Dyadic
 Interactions: From Speech and Full Body Motion
 Capture to Continuous Emotional Annotations
@@ -34221,38 +29029,11 @@ March 23, 2015"
 Embedded System for Human-Robot Interaction
 Yang-Bok Lee1, Seung-Bin Moon1, and Yong-Guk Kim 1*
 School of Computer Engineering, Sejong University, Seoul, Korea"
-5161e38e4ea716dcfb554ccb88901b3d97778f64,SSPP-DAN: Deep domain adaptation network for face recognition with single sample per person,"SSPP-DAN: DEEP DOMAIN ADAPTATION NETWORK FOR
-FACE RECOGNITION WITH SINGLE SAMPLE PER PERSON
-Sungeun Hong, Woobin Im, Jongbin Ryu, Hyun S. Yang
-School of Computing, KAIST, Republic of Korea"
 51c7c5dfda47647aef2797ac3103cf0e108fdfb4,Cs 395t: Celebrity Look-alikes *,"CS 395T: Celebrity Look-Alikes ∗
 Adrian Quark"
-514fdf2152dda3a39fc05eb6e1c80314837d96a2,Detailed 3D Representations for Object Recognition and Modeling,"Detailed 3D Representations for
-Object Recognition and Modeling
-M. Zeeshan Zia, Student Member, IEEE, Michael Stark, Member, IEEE,
-Bernt Schiele, Member, IEEE, and Konrad Schindler, Member, IEEE"
 51c7236feaa2ae23cef78c7bca75c69d7081e24a,Deep multi-frame face super-resolution,"Deep multi-frame face super-resolution
 Evgeniya Ustinova, Victor Lempitsky
 October 17, 2017"
-ddbb6e0913ac127004be73e2d4097513a8f02d37,Face Detection Using Quantized Skin Color Regions Merging and Wavelet Packet Analysis,"IEEE TRANSACTIONS ON MULTIMEDIA, VOL. 1, NO. 3, SEPTEMBER 1999
-Face Detection Using Quantized Skin Color
-Regions Merging and Wavelet Packet Analysis
-Christophe Garcia and Georgios Tziritas, Member, IEEE"
-dd72ed9a30e4d04703487df29a8762940bd79967,Image Retrieval based on LBP Transitions,"International Journal of Computer Applications (0975 – 8887)
-Volume 101– No.16, September 2014
-Image Retrieval based on LBP Transitions
-A. Srinivasa Rao
-Assoc.Prof in CSE Dept.
-MSSISTCE
-Mylavaram, Vijayawada
-V.Venkata Krishna
-Professor in CSE Dept.
-GIET, Rajahmundry
-Andhra Pradesh, India
-A.Obulesu
-Asst.Prof in CSE Dept.
-AGI (Autonomous), Hyderabad
-Telanganastate, India"
 ddbfea5302fcb5cbc2ca4c498a592ddb063b9eff,L Ow Supervision Visual Learning through Cooperative Agents,"Low-supervision visual learning through cooperative agents
 Ashish Bora
 Abhishek Sinha"
@@ -34300,11 +29081,6 @@ SenseTime Research
 ddfde5d6f4e720aeb770a20e4197db3a0c279958,Learning Convolutional Text Representations for Visual Question Answering,"Learning Convolutional Text Representations for Visual Question Answering
 Zhengyang Wang∗
 Shuiwang Ji†"
-dd8084b2878ca95d8f14bae73e1072922f0cc5da,"Model Distillation with Knowledge Transfer in Face Classification, Alignment and Verification","Model Distillation with Knowledge Transfer from
-Face Classiﬁcation to Alignment and Veriﬁcation
-Chong Wang∗, Xipeng Lan and Yangang Zhang
-Beijing Orion Star Technology Co., Ltd. Beijing, China
-{chongwang.nlpr, xipeng.lan,"
 dda7bb490171a1d3364928fb8143bbe021146c5f,Local Shape Spectrum Analysis for 3D Facial Expression Recognition,"Local Shape Spectrum Analysis for 3D Facial Expression Recognition
 Department of Information and Communication Technologies, Pompeu Fabra University, Barcelona, Spain
 Dmytro Derkach and Federico M. Sukno"
@@ -34322,14 +29098,6 @@ dd7ed20a65d811dcf863f796d6dcbe873f57e7c4,Object Detection Via Structural Feature
 Selection and Shape Model
 Huigang Zhang, Xiao Bai, Jun Zhou, Senior Member, IEEE, Jian Cheng and
 Huijie Zhao"
-dd5ef2a12753c5c923fa6b8033384db7875acf95,Upper Body Detection and Feature Set Evaluation for Body Pose Classification,"Upper Body Detection and Feature Set Evaluation for Body Pose
-Classiﬁcation
-Laurent Fitte-Duval, Alhayat Ali Mekonnen and Fr´ed´eric Lerasle
-CNRS, LAAS, 7, Avenue du Colonel Roche, F-31400 Toulouse, France
-Universit´e de Toulouse, UPS, LAAS, F-31400 Toulouse, France
-Keywords:
-Upper Body Detection, Body Pose Classiﬁcation, Fast Feature Pyramid, Sparse Classiﬁcation, Aggregated
-Channel Features, Feature Evaluation"
 ddcb77d09e4e9e2a948f9ffe7eaa5554dceb8ce3,Revisiting Cross Modal Retrieval,
 ddeb017c0452f14690ce240c90128d979289ab5f,A Comprehensive Survey on Human Skin Detection,"I.J. Image, Graphics and Signal Processing, 2016, 5, 1-35
 Published Online May 2016 in MECS (http://www.mecs-press.org/)
@@ -34370,14 +29138,6 @@ ddefb92908e6174cf48136ae139efbb4bd198896,Feature-wise Bias Amplification,"Under
 FEATURE-WISE BIAS AMPLIFICATION
 Anonymous authors
 Paper under double-blind review"
-ddf099f0e0631da4a6396a17829160301796151c,Chen et al . Face Quality Value : Input : Feat -‐ 5 Features : L 2 R + PKM Model : Feat -‐,"IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
-Learning Face Image Quality from
-Human Assessments
-Lacey Best-Rowden, Member, IEEE, and Anil K. Jain, Life Fellow, IEEE"
-dd8d53e67668067fd290eb500d7dfab5b6f730dd,A Parameter-Free Framework for General Supervised Subspace Learning,"A Parameter-Free Framework for General
-Supervised Subspace Learning
-Shuicheng Yan, Member, IEEE, Jianzhuang Liu, Senior Member, IEEE, Xiaoou Tang, Senior Member, IEEE,
-nd Thomas S. Huang, Life Fellow, IEEE"
 dde5125baefa1141f1ed50479a3fd67c528a965f,Synthesizing Normalized Faces from Facial Identity Features,"Synthesizing Normalized Faces from Facial Identity Features
 Forrester Cole1 David Belanger1,2 Dilip Krishnan1 Aaron Sarna1 Inbar Mosseri1 William T. Freeman1,3
 Google, Inc. 2University of Massachusetts Amherst 3MIT CSAIL
@@ -34399,10 +29159,6 @@ Bernhard Pfahringer†
 Michael Cree‡
 Department of Computer Science, University of Waikato, Hamilton, New Zealand
 School of Engineering, University of Waikato, Hamilton, New Zealand"
-59d66790ac1db459ba78ed0147cde7c66e7ed0c5,Ensemble-based discriminant learning with boosting for face recognition,"Ensemble-Based Discriminant Learning
-With Boosting for Face Recognition
-Juwei Lu, Member, IEEE, K. N. Plataniotis, Senior Member, IEEE, A. N. Venetsanopoulos, Fellow, IEEE, and
-Stan Z. Li"
 59d0d7ccec2db66cad20cac5721ce54a8a058294,Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference,"Quantization and Training of Neural Networks for Efﬁcient
 Integer-Arithmetic-Only Inference
 Benoit Jacob
@@ -34510,10 +29266,6 @@ Gatsby Unit, UCL, London, United Kingdom
 Christoph von der Malsburg
 Frankfurt Institute for Advanced Studies, JWG University, Ruth-Moufang-Str. 1, Frankfurt am Main, Germany
 Keywords:"
-59b202ccc01bae85a88ad0699da7a8ae6aa50fef,"Looking at Vehicles on the Road: A Survey of Vision-Based Vehicle Detection, Tracking, and Behavior Analysis","Looking at Vehicles on the Road: A Survey of
-Vision-Based Vehicle Detection, Tracking,
-nd Behavior Analysis
-Sayanan Sivaraman, Member, IEEE, and Mohan Manubhai Trivedi, Fellow, IEEE"
 59c9d416f7b3d33141cc94567925a447d0662d80,Matrix factorization over max-times algebra for data mining,"Universität des Saarlandes
 Max-Planck-Institut für Informatik
 Matrix factorization over max-times
@@ -34561,31 +29313,6 @@ Chuang Gan
 MIT-IBM Watson AI Lab
 Song Han"
 59da714d643757871bf3a48757a5919b9b577e89,A Statistical Quadtree Decomposition to Improve Face Analysis,
-5955bb0325ec4dd3b56759aeb96cc9c18b09bf3e,Self-Supervised Depth Learning Improves Semantic Segmentation,"Self-Supervised Depth Learning Improves Semantic Segmentation
-Huaizu Jiang, Erik Learned-Miller
-Univ. of Massachusetts, Amherst
-Amherst MA 01003
-. Introduction
-How does a newborn agent learn about the world?
-When an animal (or robot) moves, its visual system is
-exposed to a shower of information. Usually, the speed
-with which something moves in the image is inversely
-proportional to its depth.1 As an agent continues to
-experience visual stimuli under its own motion, it is
-natural for it to form associations between the appear-
-nce of objects and their relative motion in the image.
-For example, an agent may learn that objects that look
-like mountains typically don’t move in the image (or
-hange appearance much) as the agent moves. Objects
-like nearby cars and people, however, appear to move
-rapidly in the image as the agent changes position rel-
-tive to them. This continuous pairing of images with
-motion acts as a kind of “automatic” supervision that"
-59a35b63cf845ebf0ba31c290423e24eb822d245,The FaceSketchID System: Matching Facial Composites to Mugshots,"The FaceSketchID System: Matching Facial
-Composites to Mugshots
-Scott J. Klum, Student Member, IEEE, Hu Han, Member, IEEE, Brendan F. Klare, Member, IEEE,
-nd Anil K. Jain, Fellow, IEEE
-tedious, and may not"
 599b7e1b4460c8ad77def2330ec76a2e0dfedb84,Robust Subspace Clustering via Smoothed Rank Approximation,"Robust Subspace Clustering via Smoothed Rank
 Approximation
 Zhao Kang, Chong Peng, and Qiang Cheng∗"
@@ -34649,9 +29376,6 @@ Videos
 Serena Yeung · Olga Russakovsky · Ning Jin · Mykhaylo Andriluka · Greg Mori ·
 Li Fei-Fei
 Received: date / Accepted: date"
-59cca46a0442fc6bd0525e5f13cef5b5a9747d34,Cross-Domain Shoe Retrieval With a Semantic Hierarchy of Attribute Classification Network,"Cross-Domain Shoe Retrieval With a Semantic
-Hierarchy of Attribute Classiﬁcation Network
-Huijing Zhan, Student Member, IEEE, Boxin Shi, Member, IEEE, and Alex C. Kot, Fellow, IEEE"
 59c194bc84d604baf09241238dc47806a998df70,Building a post-compression region-of-interest encryption framework for existing video surveillance systems,"(will be inserted by the editor)
 Building a Post-Compression Region-of-Interest Encryption Framework
 for Existing Video Surveillance Systems
@@ -34735,10 +29459,6 @@ on Tourist Interests and Preferences
 *Department of Computing and Information Systems, The University of Melbourne, Australia
 Victoria Research Laboratory, National ICT Australia, Australia
 Kwan Hui Lim*†"
-2559b15f8d4a57694a0a33bdc4ac95c479a3c79a,Contextual Object Localization With Multiple Kernel Nearest Neighbor,"Contextual Object Localization With Multiple
-Kernel Nearest Neighbor
-Brian McFee, Student Member, IEEE, Carolina Galleguillos, Student Member, IEEE, and
-Gert Lanckriet, Member, IEEE"
 25ae83767c926898047bbc50971b5b11de34e12a,Detection and Tracking of Occluded People,"Noname manuscript No.
 (will be inserted by the editor)
 Detection and Tracking of Occluded People
@@ -34805,8 +29525,6 @@ Shiro Kumano · Kazuhiro Otsuka · Junji Yamato ·
 Eisaku Maeda · Yoichi Sato
 Received: date / Accepted: date"
 25b83cffddff334d78c55db4d67c65b1d8999b2f,Optimization of Person Re-Identification through Visual Descriptors,
-258da7c0f7bdfad019f9affbd3469081d1c12661,Adaptive Image Denoising by Mixture Adaptation,"Adaptive Image Denoising by Mixture Adaptation
-Enming Luo, Student Member, IEEE, Stanley H. Chan, Member, IEEE, and Truong Q. Nguyen, Fellow, IEEE"
 25e3fd1074968896fca45be20ca1d678438081fc,Group Invariant Deep Representations for Image Instance Retrieval,
 25bb4212af72d64ec20cac533f58f7af1472e057,Person Re-Identification by Camera Correlation Aware Feature Augmentation,"Person Re-Identiﬁcation by Camera
 Correlation Aware Feature Augmentation
@@ -34823,11 +29541,6 @@ uthor={Chen, Ying-Cong and Zhu, Xiatian and Zheng, Wei-Shi and Lai,
 Jian-Huang},
 (DOI: 10.1109/TPAMI.2017.2666805)}"
 25982e2bef817ebde7be5bb80b22a9864b979fb0,Facial Feature Tracking Under Varying Facial Expressions and Face Poses Based on Restricted Boltzmann Machines,"(a)26facialfeaturepointsthatwetrack(b)oneexamplesequenceFigure1.Facialfeaturepointtrackingunderexpressionvariationandocclusion.Inrecentyears,thesemodelshavebeenusedexplicitlytohandletheshapevariations[17][5].Thenonlinearityem-beddedinRBManditsvariantsmakesthemmoreeffectiveandefﬁcienttorepresentthenonrigiddeformationsofob-jectscomparedtothelinearmethods.Theirlargenumberofhiddennodesanddeeparchitecturesalsocanimposesufﬁ-cientconstraintsaswellasenoughdegreesoffreedomsintotherepresentationsofthetargetobjects.Inthispaper,wepresentaworkthatcaneffectivelytrackfacialfeaturepointsusingfaceshapepriormodelsthatareconstructedbasedonRBM.Thefacialfeaturetrackercantrack26facialfeaturepoints(Fig.1(a))eveniffaceshavedifferentfacialexpressions,varyingposes,orocclu-sion(Fig.1(b)).Unlikethepreviousworksthattrackfacialfeaturepointsindependentlyorbuildashapemodeltocap-turethevariationsoffaceshapeorappearanceregardlessofthefacialexpressionsandfaceposes,theproposedmodelcouldcapturethedistinctionsaswellasthevariationsoffaceshapesduetofacialexpressionandposechangeinauniﬁedframework.Speciﬁcally,weﬁrstconstructamodel1"
-25ed9bd6c5febac832f3d68b96123e6ba013df83,Object segmentation by alignment of poselet activations to image contours,"Object Segmentation by Alignment of Poselet Activations to Image Contours
-Thomas Brox1, Lubomir Bourdev2,3, Subhransu Maji2, and Jitendra Malik2∗
-University of California at Berkeley
-University of Freiburg, Germany
-Adobe Systems Inc., San Jose, CA"
 25894be540936562953f37fbbcff69e5ac17a494,Semantic Image Retrieval via Active Grounding of Visual Situations,"Semantic Image Retrieval
 via Active Grounding of Visual Situations
 Max H. Quinn1, Erik Conser1, Jordan M. Witte1, and Melanie Mitchell1,2
@@ -34893,10 +29606,6 @@ SPARSITY REGULARIZER
 OTNIEL Y. VIKTORISA, 2ITO WASITO, 2ARIDA F. SYAFIANDINI
 Faculty of Computer  of Computer Science, Universitas Indonesia, Kampus UI Depok, Indonesia
 E-mail:  ,"
-25403c52a7c3092866773b0e765ab55841d3cb67,Joint Prediction of Activity Labels and Starting Times in Untrimmed Videos,"Joint Prediction of Activity Labels and Starting Times in Untrimmed Videos
-Tahmida Mahmud1, Mahmudul Hasan2, Amit K. Roy-Chowdhury1
-University of California, Riverside, CA-92521, USA
-Comcast Labs, Washington, DC-20005, USA"
 25474c21613607f6bb7687a281d5f9d4ffa1f9f3,Recognizing disguised faces,"This article was downloaded by: [Carnegie Mellon University]
 On: 03 May 2012, At: 06:22
 Publisher: Psychology Press
@@ -34940,9 +29649,6 @@ Assam Don Bosco University"
 Michel F. Valstar, Bihan Jiang, Marc Mehu, Maja Pantic, and Klaus Scherer"
 25811285a1c1fd514b315d6a05adc2cb4abe9618,"DynaSLAM: Tracking, Mapping, and Inpainting in Dynamic Scenes","DynaSLAM: Tracking, Mapping and Inpainting in Dynamic Scenes
 Berta Bescos, Jos´e M. F´acil, Javier Civera and Jos´e Neira"
-25f1a5121cb7fb67749a6f6dbc27fd48f177d5fb,Context-Aware Hypergraph Modeling for Re-identification and Summarization,"Context-Aware Hypergraph Modeling for
-Re-identiﬁcation and Summarization
-Santhoshkumar Sunderrajan, Member, IEEE, and B. S. Manjunath, Fellow, IEEE"
 250ebcd1a8da31f0071d07954eea4426bb80644c,DenseBox: Unifying Landmark Localization with End to End Object Detection,"DenseBox: Unifying Landmark Localization with
 End to End Object Detection
 Lichao Huang1
@@ -34951,8 +29657,6 @@ Yafeng Deng2
 Institute of Deep Learning
 Baidu Research
 Yinan Yu3"
-25e05a1ea19d5baf5e642c2a43cca19c5cbb60f8,Label Distribution Learning,"Label Distribution Learning
-Xin Geng*, Member, IEEE"
 250449a9827e125d6354f019fc7bc6205c5fd549,Adversarial Reconstruction Loss,"PAIRWISE AUGMENTED GANS WITH
 ADVERSARIAL RECONSTRUCTION LOSS
 Aibek Alanov1,2,3∗, Max Kochurov1,2∗, Daniil Yashkov5, Dmitry Vetrov1,3,4
@@ -34961,30 +29665,8 @@ Skolkovo Institute of Science and Technology
 National Research University Higher School of Economics
 Joint Samsung-HSE lab
 5Federal Research Center ""Informatics and Management"" of the Russian Academy of Sciences"
-253d2fd2891a97d4caa49d87094dac1ec18c7752,Bio-authentication for Layered Remote Health Monitor Framework,"JOURNAL OF MEDICAL INFORMATICS & TECHNOLOGIES Vol. 23/2014, ISSN 1642-6037
-Remote Health Monitor, Security Issues,
-Multi-Factor Biometric Authentication,
-Keystroke Analysis, Face Recognition
-Tapalina BHATTASALI1, Khalid SAEED2, Nabendu CHAKI1, Rituparna CHAKI3
-BIO-AUTHENTICATION FOR LAYERED REMOTE
-HEALTH MONITOR FRAMEWORK
-Aged people, patients with chronic disease, patients at remote location need continuous monitoring under
-healthcare professionals. Remote health monitor is likely to be an effective approach to provide healthcare service
-in a simple and cost effective way. However, effective implementation of this type of framework needs consid-
-eration of variety of security threats. In this paper, a layer based remote health monitor framework is proposed
-to analyze health condition of patients from remote places. Beside this, a multi-modal biometric authentication
-mechanism is proposed here to reduce misuse of health data and biometrics templates in heterogeneous cloud
-environment. Main focus of the paper is to design semi-continuous authentication mechanism after establishing
-mutual 1:1 trust relationship among the participants in cloud environment. Behavioral biometrics keystroke
-nalysis is fused with physiological biometrics face recognition to enhance accuracy of authentication. Instead of
-onsidering traditional performance evaluation parameters for biometrics, this paper considers a few performance
-metrics for determining efﬁciency of semi-continuous veriﬁcation of the proposed framework.
-. INTRODUCTION
-Remote health monitor provides healthcare service for patients from remote locations to support"
 25afa24d85e693351bad795ee1c3e801d10c4a15,"Anisotropic Gaussian Filters for Face Class Modeling August 31 , 2006","Anisotropic Gaussian Filters for Face Class Modeling
 August 31, 2006"
-2597b0dccdf3d89eaffd32e202570b1fbbedd1d6,Towards Predicting the Likeability of Fashion Images,"Towards predicting the likeability of fashion images
-Jinghua Wang, Abrar Abdul Nabi, Gang Wang, Member, IEEE, Chengde Wan, Tian-Tsong Ng, Member, IEEE,"
 258972e9df3cdf0b8babbf607eaef7cce689226a,Multimodal Affect Recognition: Current Approaches and Challenges,"We are IntechOpen,
 the world’s leading publisher of
 Open Access books
@@ -35005,10 +29687,6 @@ in Web of Science™ Core Collection (BKCI)
 Interested in publishing with us?
 Contact
 Numbers displayed above are based on latest data collected."
-2594bf77a1fef68d86be74a2cb79c55499cb2bec,Learning Invariant Color Features for Person Reidentification,"Learning Invariant Color Features for
-Person Re-Identiﬁcation
-Rahul Rama Varior, Student Member, IEEE,
-Gang Wang, Member, IEEE Jiwen Lu, Member, IEEE"
 25c57d1916c926bea3d92548f1c9836cffc23fe5,Automatic Ground Truths: Projected Image Annotations for Omnidirectional Vision,"Automatic Ground Truths: Projected Image
 Annotations for Omnidirectional Vision
 Victor Stamatescu∗, Peter Barsznica∗, Manjung Kim ∗, Kin K. Liu∗, Mark McKenzie†,
@@ -35176,9 +29854,6 @@ Recognition in Large Dataset
 Sameh MEGRHI1, Marwa JMAL 2, Azeddine BEGHDADI1 and Wided Mseddi1,2
 L2TI, Institut Galil´ee, Universit´e Paris 13, France;
 SERCOM, Ecole Polytechnique de Tunisie"
-558c4917dc9a1d34f62c0ab713b1b9a37ad04853,Action Recognition Using Multilevel Features and Latent Structural SVM,"Action Recognition Using Multilevel Features and
-Latent Structural SVM
-Xinxiao Wu, Dong Xu, Member, IEEE, Lixin Duan, Jiebo Luo, Fellow, IEEE, and Yunde Jia, Member, IEEE"
 5556234869c36195ffdcd29349e5dcdf695023e9,Minimum Distance between Pattern Transformation Manifolds: Algorithm and Applications,"JULY 2009
 Minimum Distance between
 Pattern Transformation Manifolds:
@@ -35299,10 +29974,6 @@ pplications of current interest.
 OBJECTIVES"
 55c68c1237166679d2cb65f266f496d1ecd4bec6,Learning to score the figure skating sports videos,"Learning to Score Figure Skating Sport Videos
 Chengming Xu, Yanwei Fu, Zitian Chen,Bing Zhang, Yu-Gang Jiang, Xiangyang Xue"
-5531e728850185b80835a78db2e4fd23e288f359,Towards Reading Hidden Emotions: A Comparative Study of Spontaneous Micro-Expression Spotting and Recognition Methods,"Reading Hidden Emotions: Spontaneous
-Micro-expression Spotting and Recognition
-Xiaobai Li, Student Member, IEEE, Xiaopeng Hong, Member, IEEE, Antti Moilanen, Xiaohua Huang, Student
-Member, IEEE, Tomas Pﬁster, Guoying Zhao, Senior Member, IEEE, and Matti Pietik¨ainen, Fellow, IEEE"
 550edcdc27aff4e7ea8807356a265a0031434a49,Fine-Grained Recognition with Automatic and Efficient Part Attention,"Fine-Grained Recognition with Automatic and Efﬁcient Part Attention
 Xiao Liu, Tian Xia, Jiang Wang, Yi Yang, Feng Zhou and Yuanqing Lin
 Baidu Research
@@ -35316,10 +29987,6 @@ Toby P. Breckon
 Engineering and Computer Science
 Durham University
 Durham, UK"
-5520acfa1f4e678f1abbaab67ec76e903c3d3bdc,SALSA: A Novel Dataset for Multimodal Group Behavior Analysis,"SALSA: A Novel Dataset for Multimodal Group
-Behavior Analysis
-Xavier Alameda-Pineda, Jacopo Staiano, Ramanathan Subramanian, Member, IEEE, Ligia Batrinca,
-Elisa Ricci, Member, IEEE, Bruno Lepri, Oswald Lanz, Member, IEEE, Nicu Sebe, Senior Member, IEEE"
 55202f10bb1d7640b0b279a4cdc8e9925cd9ef81,ICM: An Intuitive Model Independent and Accurate Certainty Measure for Machine Learning,
 559295770dc2e2e3a1348df31ac5c3f3e66f1764,Generating Multiple Hypotheses for Human 3D Pose Consistent with 2D Joint Detections,"Generating Multiple Hypotheses for Human 3D Pose Consistent with 2D Joint Detections
 Johns Hopkins University
@@ -35330,12 +29997,6 @@ Ehsan Jahangiri
 Baltimore, USA"
 558c587373e2ea44898f70de7858da71aa217b8d,Cross-Lingual Image Caption Generation,"Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, pages 1780–1790,
 Berlin, Germany, August 7-12, 2016. c(cid:13)2016 Association for Computational Linguistics"
-5550a6df1b118a80c00a2459bae216a7e8e3966c,A perusal on Facial Emotion Recognition System ( FERS ),"ISSN: 0974-2115
-www.jchps.com                                                                       Journal of Chemical and Pharmaceutical Sciences
-A perusal on Facial Emotion Recognition System (FERS)
-School of Information Technology and Engineering, VIT University, Vellore, 632014, India
-Krithika L.B
-*Corresponding author: E-Mail:"
 55e8cfd4a96bdc77d10459c0aa73991ff098c60e,Nonnegative Discriminant Matrix Factorization,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCSVT.2016.2539779, IEEE
 Transactions on Circuits and Systems for Video Technology
 Copyright (c) 2016 IEEE. Personal use of this material is permitted. However, permission to use this material for any other purposes
@@ -35491,26 +30152,6 @@ uthor={Zhou Yin, Wei-Shi Zheng, Ancong Wu, Hong-Xing Yu, Hai Wan, Xiaowei Guo, F
 Jianhuang Lai},
 journal={ International Joint Conference on Artiﬁcial Intelligence},
 year={2018}"
-4ea253a391f804f0045a20e6ef1ae6e92cd0ba55,5 Image Compression Effects in Face Recognition Systems,"Image Compression Effects in Face Recognition
-Systems
-Kresimir Delac, Mislav Grgic and Sonja Grgic
-University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb
-Croatia
-image  experimental  setups  are  often  researched,  but  only
-. Introduction
-With  the  growing  number  of  face  recognition  applications  in  everyday  life,  image-  and
-video-based recognition methods are becoming important research topic (Zhao et al., 2003).
-Effects  of  pose,  illumination  and  expression  are  issues  currently  most  studied  in  face
-recognition. So far, very little has been done to investigate the effects of compression on face
-recognition, even though the images are mainly stored and/or transported in a compressed
-format.  Still-to-still
-uncompressed image formats. Still-to-video research (Zhou et al., 2003) mostly deals with
-issues of tracking and recognizing faces in a sense that still uncompressed images are used
-s a gallery and compressed video segments as probes.
-In  this  chapter  we  analyze  the  effects  that  standard  image  compression  methods  -  JPEG
-(Wallace, 1991) and JPEG2000 (Skodras et al., 2001) - have on three well known subspace
-ppearance-based face recognition algorithms: Principal Component Analysis - PCA (Turk
-&  Pentland,  1991),  Linear  Discriminant  Analysis  -  LDA  (Belhumeur  et  al.,  1996)  and"
 4e6ff8ff80a1610bb841b669bb7667413ed2982f,Dependence Characteristics of Face Recognition Algorithms,"Dependence Characteristics of Face Recognition Algorithms
 Patrick Grother, P. Jonathon Phillips,
 Stefan Leighy, Alan Heckerty,
@@ -35589,11 +30230,6 @@ Arijit Biswas 3"
 4e6c9be0b646d60390fe3f72ce5aeb0136222a10,Long-Term Temporal Convolutions for Action Recognition,"Long-term Temporal Convolutions
 for Action Recognition
 G¨ul Varol, Ivan Laptev, and Cordelia Schmid, Fellow, IEEE"
-4eb0b82b294f601510cd965adcf0e8c386cbaf22,Face Detection for Augmented Reality Application Using Boosting-based Techniques,"Face Detection for Augmented Reality Application
-Using Boosting-based Techniques
-Youssef  Hbali1, Lahoucine Ballihi2, Mohammed  Sadgal1, El Fazziki Abdelaziz1
-Cadi Ayyad University. B.P. 2390, Avenue Prince My Abdellah, Marrakech, Morocco
-LRIT-CNRST URAC 29, Mohammed V University In Rabat, Faculty of Sciences Rabat, Morocco"
 4e0e49c280acbff8ae394b2443fcff1afb9bdce6,Automatic Learning of Gait Signatures for People Identification,"Automatic learning of gait signatures for people identiﬁcation
 F.M. Castro
 Univ. of Malaga
@@ -35629,10 +30265,6 @@ Clouds
 Yizhak Ben-Shabat · Tamar Avraham · Michael Lindenbaum ·
 Anath Fischer
 Received: date / Accepted: date"
-4e1d7bad6cde28e65b12c5824b1016859e1ae704,Enhanced Face Recognition Using Discrete Cosine Transform,"Enhanced Face Recognition Using Discrete
-Cosine Transform
-Zahraddeen Sufyanu, Member, IAENG, Fatma S. Mohamad, Abdulganiyu A. Yusuf, and Mustafa B.
-Mamat"
 4e19917a786c611ffdecd171fae37183ad55ad49,A survey of practical adversarial example attacks,"Sun et al. Cybersecurity  (2018) 1:9
 https://doi.org/10.1186/s42400-018-0012-9
 SURVEY
@@ -35647,22 +30279,7 @@ Christopher Pramerdorfer, Martin Kampel
 Computer Vision Lab, TU Wien
 Vienna, Austria
 Email:"
-4ea6954b47baec061fa3f3e1228833eba7be07f9,Multi-pseudo Regularized Label for Generated Data in Person Re-Identification.,"Multi-pseudo Regularized Label for Generated Data
-in Person Re-Identiﬁcation
-Yan Huang, Jingsong Xu, Qiang Wu, Member, IEEE Zhedong Zheng, Zhaoxiang Zhang, Senior Member, IEEE
-nd Jian Zhang, Senior Member, IEEE"
 4e82908e6482d973c280deb79c254631a60f1631,Improving Efficiency and Scalability in Visual Surveillance Applications,
-4e4a47e2d285e55f3d0b6d449d6b9893615db5cd,Use of l2/3-norm Sparse Representation for Facial Expression Recognition,"International Journal of Science and Research (IJSR)
-ISSN (Online): 2319-7064
-Impact Factor (2012): 3.358
-Use of ℓ2/3-norm Sparse Representation for Facial
-Expression Recognition
-Sandeep Rangari1, Sandeep Gonnade2
-MATS University, MATS School of Engineering and Technology, Arang, Raipur, India
-MATS University, MATS School of Engineering and Technology, Arang, Raipur, India
-three
-to  discriminate
-represents  emotion,"
 4eaaefc53fd61d27b9ce310c188fe76003a341bd,Assessing Generative Models via Precision and Recall,"Assessing Generative Models via Precision and Recall
 Mehdi S. M. Sajjadi∗
 MPI for Intelligent Systems,
@@ -35762,16 +30379,6 @@ Action Classiﬁcation and Detection
 Mohammadreza Zolfaghari , Gabriel L. Oliveira, Nima Sedaghat, and Thomas Brox
 University of Freiburg
 Freiburg im Breisgau, Germany"
-ea3353efbe7b856ced106718d04ea7d83e2a2310,A Survey of Video Object Tracking,"International Journal of Control and Automation
-Vol. 8, No. 9 (2015), pp. 303-312
-http://dx.doi.org/10.14257/ijca.2015.8.9.29
-A Survey of Video Object Tracking
-Meng Li, Zemin Cai1, Chuliang Wei and Ye Yuan
-Department of Electronic Engineering, College of Engineering, Shantou
-University, China
-Guangdong Provicial Key Laboratory of Digital Signal and Image Processing
-Techniques, China
-Corresponding author,"
 ea572991a75acfc8a8791955f670d2c48db49023,Arbitrary-Shape object localization using adaptive image grids,"Arbitrary-Shape Object Localization using
 Adaptive Image Grids
 Chunluan Zhou and Junsong Yuan
@@ -35783,11 +30390,6 @@ nd Self-Organizing Map
 Miloš ORAVEC, Jarmila PAVLOVIČOVÁ
 Dept. of Telecommunications, Faculty of Electrical Engineering and Information Technology, Slovak University of
 Technology, Ilkovičova 3, 812 19 Bratislava, Slovak Republic"
-eac6aee477446a67d491ef7c95abb21867cf71fc,A Survey of Sparse Representation: Algorithms and Applications,"JOURNAL
-A survey of sparse representation: algorithms and
-pplications
-Zheng Zhang, Student Member, IEEE, Yong Xu, Senior Member, IEEE,
-Jian Yang, Member, IEEE, Xuelong Li, Fellow, IEEE, and David Zhang, Fellow, IEEE"
 ea8cb4a79b211fb288f747bdd64b3fc36e11c0fc,Chapter 10 Automatic Facial Action Unit Recognition by Modeling Their Semantic And Dynamic Relationships,"Chapter 10
 Automatic Facial Action Unit Recognition
 y Modeling Their Semantic And Dynamic
@@ -36045,15 +30647,6 @@ Tim K. Marks
 Michael Jones
 Mitsubishi Electric Research Laboratories (MERL)
 01 Broadway, Cambridge, MA 02139"
-2709bb385ce53c83a5fe952d54a4c5e5786c0849,Fine-Tuning Deep Neural Networks in Continuous Learning Scenarios,"C. K¨ading, E. Rodner, A. Freytag, J. Denzler
-Fine-tuning Deep Neural Networks in Continuous Learning Scenarios
-ACCV 2016 Workshop on Interpretation and Visualization of Deep Neural Nets
-(cid:13) Copyright by Springer. The ﬁnal publication will be available at http://link.springer.com/
-Fine-tuning Deep Neural Networks in Continuous
-Learning Scenarios
-Christoph K¨ading1,2, Erik Rodner1,2, Alexander Freytag1,2, and Joachim Denzler1,2
-Computer Vision Group, Friedrich Schiller University Jena, Germany
-Michael Stifel Center Jena, Germany"
 2713423d87d011c0a5aae99bef57523769121a1d,A Codebook Design Method for Robust VQ-Based Face Recognition Algorithm,"J. Software Engineering & Applications, 2010, 3: 119-124
 A Codebook Design Method for Robust VQ-Based
 Face Recognition Algorithm
@@ -36084,12 +30677,6 @@ more information contact"
 Hui Ding,1 Hao Zhou,2 Shaohua Kevin Zhou,3 Rama Chellappa4
 ,2,4University of Maryland, College Park
 Siemens Healthineers, New Jersey"
-27ae7c8c650ffef74c465640f423d9008014e1ca,Dimensionality Reduction with Adaptive Approximation,"TobepublishedintheProceedingsofIEEEICME2007,Beijing,China
-DIMENSIONALITY REDUCTION WITH ADAPTIVE APPROXIMATION
-Effrosyni Kokiopoulou and Pascal Frossard
-Ecole Polytechnique F´ed´erale de Lausanne (EPFL)
-Signal Processing Institute - ITS
-CH- 1015 Lausanne, Switzerland"
 2734b3a6345396499b2b7c6cc1b43fc7e9b375ee,Full-System Simulation of big.LITTLE Multicore Architecture for Performance and Energy Exploration,"Full-System Simulation of big.LITTLE Multicore
 Architecture for Performance and Energy
 Exploration
@@ -36103,10 +30690,6 @@ Email:"
 Bin Qi1,2, Vijay John1,2, Zheng Liu1,2, and Seiichi Mita2
 Intelligent Information Processing Laboratory, Toyota Technological Institute, Nagoya, Japan,
 Research Centre for Smart Vehicles, Toyota Technological Institute, Nagoya, Japan,"
-27b1670e1b91ab983b7b1ecfe9eb5e6ba951e0ba,Comparison between k-nn and svm method for speech emotion recognition,"Comparison between k-nn and svm method
-for speech emotion recognition
-Muzaffar Khan, Tirupati Goskula, Mohmmed Nasiruddin ,Ruhina Quazi
-Anjuman College of Engineering & Technology ,Sadar, Nagpur, India"
 27b87bdee46964757b83b5afb4184e438cad6b1b,Sequence searching with deep-learnt depth for condition- and viewpoint-invariant route-based place recognition,"Sequence Searching with Deep-learnt Depth for Condition- and Viewpoint-
 invariant Route-based Place Recognition
 Michael Milford, Stephanie Lowry, Niko
@@ -36146,23 +30729,6 @@ Johns Hopkins University"
 Homography Transformations
 Erjin Zhou, Zhimin Cao, and Jian Sun
 Face++, Megvii Inc."
-27cccf992f54966feb2ab4831fab628334c742d8,Neutral Face Happy Face Surprise Face Fear Face Sad Face Angry Face Disgust Face,"International Journal of Computer Applications (0975 – 8887)
-Volume 64– No.18, February 2013
-Facial Expression Recognition by Statistical, Spatial
-Features and using Decision Tree
-Nazil Perveen
-Assistant Professor
-CSIT Department
-GGV BIlaspur, Chhattisgarh
-India
-Darshan Kumar
-Assistant Professor
-Electronics (ECE) Department
-JECRC Jaipur, Rajasthan India
-IshanBhardwaj
-Student of Ph.D.
-Electrical Department
-NIT Raipur, Chhattisgarh India"
 2783efc96a0d59473e4236ccf1db6ed7e958839e,An Overview of Multi-Task Learning in Deep Neural Networks,"An Overview of Multi-Task Learning
 in Deep Neural Networks∗
 Sebastian Ruder
@@ -36454,50 +31020,7 @@ interpretation in smart environment
 Oleg Starostenko *, Ximena Cortés, J. Afredo Sánchez and Vicente Alarcon-Aquino
 Department of Computing, Electronics and Mechatronics, Universidad de las Americas Puebla, Cholula,
 Pue. 72810, Mexico"
-d61578468d267c2d50672077918c1cda9b91429b,Face Image Retrieval Using Pose Specific Set Sparse Feature Representation,"Abdul Afeef N et al, International Journal of Computer Science and Mobile Computing, Vol.3 Issue.9, September- 2014, pg. 314-323
-Available Online at www.ijcsmc.com
-International Journal of Computer Science and Mobile Computing
-A Monthly Journal of Computer Science and Information Technology
-ISSN 2320–088X
-IJCSMC, Vol. 3, Issue. 9, September 2014, pg.314 – 323
-RESEARCH ARTICLE
-Face Image Retrieval Using Pose Specific
-Set Sparse Feature Representation
-Department of Computer Science, Viswajyothi College of Engineering and Technology Kerala, India
-Assistant Professor of Computer Science, Viswajyothi College of Engineering and Technology Kerala, India
-Abdul Afeef N1, Sebastian George2"
-d680cfe583fe61e49656cc7b9dbd480c6159cf0b,Pedestrian Detection in Far-Infrared Daytime Images Using a Hierarchical Codebook of SURF,"Sensors 2015, 15, 8570-8594; doi:10.3390/s150408570
-OPEN ACCESS
-sensors
-ISSN 1424-8220
-www.mdpi.com/journal/sensors
-Article
-Pedestrian Detection in Far-Infrared Daytime Images Using a
-Hierarchical Codebook of SURF
-Bassem Besbes 1, Alexandrina Rogozan 2,*, Adela-Maria Rus 2,3,*, Abdelaziz Bensrhair 2
-nd Alberto Broggi 4
-Diotasoft, 15 Boulevard Emile Baudot, Massy 91300, France; E-Mail:
-LITIS Laboratory, National Institute of Applied Sciences, 76801 Saint-Etienne-du-Rouvray Cedex,
-France; E-Mail:
-Faculty of Computer Science, Babes-Bolyai University, Kogalniceanu no.1,
-Cluj-Napoca RO-400084, Romania
-Dipartimento di Ingegneria dell’ Informazione, Universita di Parma, Parco Area delle Scienze,
-Parma 181/a 43124, Italy; E-Mail:
-* Authors to whom correspondence should be addressed; E-Mails: (A.R.);
-(A.-M.R.); Tel.: +33-2-3295-6670 (A.R.); +40-2-6440-5300 (A.-M.R.).
-Academic Editor: Felipe Jimenez"
 d69df51cff3d6b9b0625acdcbea27cd2bbf4b9c0,Robust Remote Heart Rate Determination for E-Rehabilitation - A Method that Overcomes Motion and Intensity Artefacts,
-d64c362b631f0c94b22952e2d0860054f0854358,Offline Handwritten Devanagari Numeral Recognition Using Artificial Neural Network,"International Journals of Advanced Research in
-Computer Science and Software Engineering
-ISSN: 2277-128X (Volume-7, Issue-8)
-Research  Article
-August
-Offline Handwritten Devanagari Numeral Recognition
-Using Artificial Neural Network
-P E Ajmire
-Associate Professor & Head, Department of Computer Science & Application,  G. S. Science, Arts & Commerce
-College, Khamgaon, Maharashtra, India
-DOI: 10.23956/ijarcsse/V7I7/0157"
 d689cdb4e535be040316722229e6362de6617f9e,GEOMETRIC DEEP PARTICLE FILTER FOR MOTORCYCLE TRACKING : DEVELOPMENT OF INTELLIGENT TRAFFIC SYSTEM IN JAKARTA,"INTERNATIONAL JOURNAL ON SMART SENSING AND INTELLIGENT SYSTEMS VOL. 8, NO. 1, MARCH 2015
 GEOMETRIC DEEP PARTICLE FILTER FOR MOTORCYCLE
 TRACKING: DEVELOPMENT OF INTELLIGENT TRAFFIC
@@ -36586,16 +31109,6 @@ d6ceebb0cde7fb0fbe916472d7b613a2d7d2e1e6,Do faces capture the attention of indiv
 or Autism? Evidence from tracking eye movements
 Deborah M Riby & Peter J B Hancock
 http://dx.doi.org/10.1007/s10803-008-0641-z"
-d6f2ba0856d007112974596a8a1cfd5c81269836,CLASSIFICATION OF TYPES OF SKIN LESIONS WITH TASK DECOMPOSITION METHOD,"Vol-2 Issue-2 2016
-IJARIIE-ISSN (O)-2395-4396
-CLASSIFICATION  OF TYPES OF SKIN
-LESIONS WITH TASK  DECOMPOSITION
-METHOD
-Dr.P.S.Ramaprabha1, Ms.Shalini.E  2, Ms.Shiji  Jenifer.A.S3,  Ms.Prema  dhevi.M4
-1 Professor ,ECE, Panimalar Institute of Technology, TAMILNADU, INDIA
-2 UG Scholar,ECE, Panimalar Institute of Technology, TAMILNADU ,INDIA
-3 UG Scholar,ECE, Panimalar Institute of Technology, TAMILNADU, INDIA
-4 UG Scholar,ECE, Panimalar Institute of Technology, TAMILNADU, INDIA"
 d665213b59f2460faf171d3b03ecd9c96d606883,A MULTIMODAL NONVERBAL HUMAN-ROBOT COMMUNICATION SYSTEM,"VI International Conference on Computational Bioengineering
 ICCB 2015
 M. Cerrolaza and S.Oller (Eds)
@@ -36672,15 +31185,6 @@ Merantix GmbH
 Luc Van Gool
 D-ITET, ETH Zurich
 ESAT, KU Leuven"
-80e7f9bcaca98b65ce12ad7ce28c4b42e0712752,A New Affine Invariant Image Transform Based on Ridgelets,"A New Afﬁne Invariant Image Transform Based
-on Ridgelets
-Esa Rahtu
-Janne Heikkil¨a
-Department of Electrical and Information Engineering
-P.O. Box 4500, 90014 University of Oulu, Finland
-Mikko Salo
-Department of Mathematics and Statistics / RNI
-P.O. Box 68, 00014 University of Helsinki, Finland"
 808b03e28bb45bd446ee7e82f767e48db354fefd,Fast Optical Flow using Dense Inverse Search Supplementary Material,"Fast Optical Flow using Dense Inverse Search
 Supplementary Material
 Till Kroeger1
@@ -36788,8 +31292,6 @@ Performance Parameter Analysis of Face Recognition Based On
 Fuzzy C-Means Clustering, Shape and Corner Detection
 Minj Salen Kujur1, Prof. Prashant Jain2
 Department of Electronics & Communication Engineering college Jabalpur"
-8032a89ba67e2b35e2789983426842f688c49a93,Matching-Constrained Active Contours,"Matching-Constrained Active Contours
-Junyan Wang*, Member, IEEE, Kap Luk Chan, Member, IEEE"
 80265d7c9fe6a948dd8c975bd4d696fb7ba099c9,Face Recognition Based on Human Visual Perception Theories and Unsupervised ANN,"Face Recognition Based on
 Human Visual Perception Theories and
 Unsupervised ANN
@@ -36907,15 +31409,6 @@ stimuli
 Nina Strohminger1,6 · Kurt Gray2 · Vladimir Chituc3 · Joseph Heffner4 ·
 Chelsea Schein2 · Titus Brooks Heagins5
 © Psychonomic Society, Inc. 2015"
-577b62afca4d5e9092228f20098da5df35ad3cdd,Canonical Correlated PCA method For Face Recognition,"International
-OPEN          ACCESS                                                                                                              Journal
-ISSN: 2249-6645                                                                  Of Modern Engineering Research (IJMER)
-Canonical Correlated PCA method For Face Recognition
-S. Krishnaveni 1, N.L.Aravinda 2
-Asst.Prof,ECE Dept, CMR college of Engineering & Technology, JNTUH, India
-Email:
-2Asst.Prof,ECE Dept,, CMR Engineering College, JNTUH, India
-Email:"
 57235f22abcd6bb928007287b17e235dbef83347,Exemplar Guided Unsupervised Image-to-Image Translation with Semantic Consistency,"EXEMPLAR GUIDED UNSUPERVISED
 IMAGE-TO-
 IMAGE TRANSLATION WITH SEMANTIC CONSISTENCY
@@ -36986,11 +31479,6 @@ If you believe that digital publication of certain material infringes any of you
 your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask
 the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam,
 The Netherlands. You will be contacted as soon as possible."
-57bfbd06e94c5def35c1dde901bb4f1c839dbcdf,Deep patch learning for weakly supervised object classification and discovery,"Deep Patch Learning for Weakly Supervised Object
-Classiﬁcation and Discovery
-Peng Tanga, Xinggang Wanga,∗, Zilong Huanga, Xiang Baia, Wenyu Liua
-School of Electronic Information and Communications, Huazhong University of Science
-nd Technology, Wuhan 430074, China"
 5712cfc11c561c453da6a31d515f4340dacc91a4,3D Facial Expression Reconstruction using Cascaded Regression,"SUBMITTED TO PATTERN RECOGNITION LETTERS
 Cascaded Regression using Landmark
 Displacement for 3D Face Reconstruction
@@ -37042,9 +31530,6 @@ Volker Fischer1, Mummadi Chaithanya Kumar2, Jan Hendrik Metzen1 & Thomas Brox2
 Bosch Center for Artiﬁcial Intelligence, Robert Bosch GmbH
 University of Freiburg
 {volker.fischer,"
-573c11e7e00389a033787984223ced536e15c904,Pictorial structures revisited: People detection and articulated pose estimation,"Pictorial Structures Revisited: People Detection and Articulated Pose Estimation
-Mykhaylo Andriluka, Stefan Roth, and Bernt Schiele
-Department of Computer Science, TU Darmstadt"
 57e9b0d3ab6295e914d5a30cfaa3b2c81189abc1,Self-Learning Scene-Specific Pedestrian Detectors Using a Progressive Latent Model,"Self-learning Scene-speciﬁc Pedestrian Detectors
 using a Progressive Latent Model
 Qixiang Ye1,4, Tianliang Zhang 1, Qiang Qiu4, Baochang Zhang2, Jie Chen3, and Guillermo Sapiro4
@@ -37105,16 +31590,6 @@ Tianyu Pang 1 Chao Du 1 Jun Zhu 1"
 57c59011614c43f51a509e10717e47505c776389,Unsupervised Human Action Detection by Action Matching,"Unsupervised Human Action Detection by Action Matching
 Basura Fernando∗ Sareh Shirazi† Stephen Gould∗
 The Australian National University †Queensland University of Technology"
-571b83f7fc01163383e6ca6a9791aea79cafa7dd,SeqFace: Make full use of sequence information for face recognition,"SeqFace: Make full use of sequence information for face recognition
-Wei Hu1 ∗
-Yangyu Huang2
-Guodong Yuan2
-Fan Zhang1
-Ruirui Li1
-Wei Li1
-College of Information Science and Technology,
-Beijing University of Chemical Technology, China
-YUNSHITU Corp., China"
 5782d17ad87262739d69dcbe76cadfa881179a91,Data Analysis Project : What Makes Paris Look like Paris ?,"Data Analysis Project: What Makes Paris Look like
 Paris?
 Machine Learning Department
@@ -37126,11 +31601,6 @@ BEYOND SHARED HIERARCHIES: DEEP MULTITASK
 LEARNING THROUGH SOFT LAYER ORDERING
 Anonymous authors
 Paper under double-blind review"
-572785b5d6f6fa4b174d79725f82c056b0fb4565,"Computer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art","Computer Vision for Autonomous Vehicles:
-Problems, Datasets and State-of-the-Art
-Joel Janaia,∗, Fatma G¨uneya,∗, Aseem Behla,∗, Andreas Geigera,b
-Autonomous Vision Group, Max Planck Institute for Intelligent Systems, Spemannstr. 41, D-72076 T¨ubingen, Germany
-Computer Vision and Geometry Group, ETH Z¨urich, Universit¨atstrasse 6, CH-8092 Z¨urich, Switzerland"
 5740a5f9cbfe790afc0ba9a425cfb71197927470,Supplementary Material for Superpixel Sampling Networks,"Supplementary Material for
 Superpixel Sampling Networks
 Varun Jampani1, Deqing Sun1, Ming-Yu Liu1,
@@ -37178,17 +31648,6 @@ Camino de Vera s/n, Edif. 8G Acc. B 46022 Valencia (Spain)"
 9cc4abd2ec10e5fa94ff846c5ee27377caf17cf0,Improved Techniques for GAN based Facial Inpainting,"Improved Techniques for GAN based Facial
 Inpainting
 Avisek Lahiri*, Arnav Jain*, Divyasri Nadendla and Prabir Kumar Biswas, Senior Member, IEEE"
-9c8a2d66b8fd6973751b8ee2fe6738327968cfcb,Exploring a model of far-from-equilibrium computation,"Exploring a model of far-from-equilibrium
-omputation
-R˘azvan V. Florian
-Center for Cognitive and Neural Studies (Coneural)
-Str. Saturn 24, 400504 Cluj-Napoca, Romania
-July 10, 2005"
-9c889616034adce2af05d74eac44cf43a8106468,Binary Quadratic Programing for Online Tracking of Hundreds of People in Extremely Crowded Scenes,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015
-Binary Quadratic Programing for Online Tracking
-of Hundreds of People in Extremely Crowded
-Scenes
-Afshin Dehghan, Member, IEEE, and Mubarak Shah, Fellow, IEEE"
 9c8da385750db215dc0728dc310251b320d319af,- CL-TR-899 ISSN 1476-2986 Deep embodiment : grounding semantics in perceptual modalities,"Technical Report
 UCAM-CL-TR-899
 ISSN 1476-2986
@@ -37228,10 +31687,6 @@ Dept. of Electrical                Dept. of CSIE                    Dept. of CSI
 Engineering              Chaoyang University              Nankai Institute of
 National University            of Technology                        Technology
 of Kaohsiung"
-9c07704226e536834c4a8c01e1eb428584bacec6,Benchmarking Single-Image Dehazing and Beyond,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015
-Benchmarking Single Image Dehazing and Beyond
-Boyi Li*, Wenqi Ren*, Member, IEEE, Dengpan Fu*, Dacheng Tao, Fellow, IEEE, Dan Feng, Member, IEEE,
-Wenjun Zeng, Fellow, IEEE and Zhangyang Wang†, Member, IEEE."
 9ce0d64125fbaf625c466d86221505ad2aced7b1,Recognizing expressions of children in real life scenarios View project PhD ( Doctor of Philosophy ) View project,"Saliency Based Framework for Facial Expression
 Recognition
 Rizwan Ahmed Khan, Alexandre Meyer, Hubert Konik, Saïda Bouakaz
@@ -37301,13 +31756,6 @@ Mohamad Hanif Md. Saad1
 Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia (UKM), Bangi, Malaysia
 Institute of Visual Informatics, Universiti Kebangsaan Malaysia (UKM), Bangi, Malaysia
 E-mail:"
-9c1f5547d98f5390e2389ce40668da83a9830487,Non-parametric Structured Output Networks,"Non-parametric Structured Output Networks
-Andreas M. Lehrmann
-Disney Research
-Pittsburgh, PA 15213
-Leonid Sigal
-Disney Research
-Pittsburgh, PA 15213"
 9cd8e1ccc5a410c7f31c7e404588597c0bb1952b,What ’ s your type ? Personalized Prediction of Facial Attractiveness  ,"Whats Your Type? Personalized Prediction of
 Facial Attractiveness
 Sam Crognale, Computer Science, Danish Shabbir Electrical Engineering
@@ -37375,10 +31823,6 @@ Introduction: Person re-identiﬁcation, aiming to ﬁnding the images that
 match the target person in a large-scale image library, greatly reduces the
 time cost of human search. Due to its great signiﬁcance to visual super-
 vision, it has rapidly become a research hotspot in the ﬁeld of computer"
-9c731b820c495904a6f7d255d7e6a3bf9e5fc365,Geometric inpainting of 3D structures,"Geometric inpainting of 3D structures
-Pratyush Sahay, A.N. Rajagopalan
-Indian Institute of Technology Madras
-Chennai, India"
 9ca2dfe8a6265c4f6ea12bae0e7ff6ffc9128226,Dialog-based Interactive Image Retrieval,"Dialog-based Interactive Image Retrieval
 Xiaoxiao Guo†
 IBM Research AI
@@ -37421,15 +31865,6 @@ Robotics, Perception and Learning Lab
 Royal Institute of Technology (KTH)
 Stockholm, SE-100 44, Sweden
 Email: {nbore, ekz, patric,"
-9c576520ed9c960270715f790a62b9337ce88bd2,Beyond Pixels: Leveraging Geometry and Shape Cues for Online Multi-Object Tracking,"Beyond Pixels: Leveraging Geometry and Shape Cues for Online
-Multi-Object Tracking
-Sarthak Sharma1∗, Junaid Ahmed Ansari1∗, J. Krishna Murthy2, K. Mahdava Krishna1
-Robotics Research Center, KCIS, IIIT Hyderabad, India
-Mila, Universite de Montreal, Canada
-denotes equal contribution
-Fig. 1. An illustration of the proposed method. The ﬁrst two rows show objects tracks in frames t and t + 1. The bottom row depicts how 3D position
-nd orientation information is propagated from frame t to frame t + 1. This information is used to specify search areas for each object in the subsequent
-frame, and this greatly reduces the number of pairwise costs that are to be computed."
 9cfb3a68fb10a59ec2a6de1b24799bf9154a8fd1,Semi-supervised learning in Spectral Dimensionality Reduction,"Semi-supervised learning in
 Spectral Dimensionality Reduction
 Maryam Mehdizadeh
@@ -37458,11 +31893,6 @@ broad, or from public or private research centers.
 L’archive ouverte pluridisciplinaire HAL, est
 destinée au dépôt et à la diffusion de documents
 scientifiques de niveau recherche, publiés ou non,"
-9c1305383ce2c108421e9f5e75f092eaa4a5aa3c,RETRIEVAL FOR TV SHOW VIDEOS BY ASSOCIATING AUDIO SPEAKER RECOGNITION RESULT TO VISUAL FACES,"SPEAKER RETRIEVAL FOR TV SHOW VIDEOS BY ASSOCIATING AUDIO SPEAKER
-RECOGNITION RESULT TO VISUAL FACES∗
-Yina Han*’, Joseph Razik’, Gerard Chollet’, and Guizhong Liu*
-*School of Electrical and Information Engineering, Xi’an Jiaotong University, Xi’an, China
-’CNRS-LTCI, TELECOM-ParisTech, Paris, France"
 9cd7487e0eed11dabc94dd867178204c53eb2270,Self-Organizing Traffic Lights : A Pedestrian Oriented Approach,"Self-Organizing Trafﬁc Lights: A Pedestrian
 Oriented Approach
 Jessica S. Souza1, Cesar A. M. Ferreira2, Cassio E. dos Santos Jr3, Victor H. C. Melo4, William Robson Schwartz4
@@ -37533,13 +31963,6 @@ version
 http://dx.doi.org/10.1109/TIP.2009.2017163
 Item record
 http://hdl.handle.net/10379/1350"
-92020e6540fe9feb38616334645a0ba28dcac69d,FACE RECOGNITION BASED ON LOCAL DERIVATIVE TETRA PATTERN,"ISSN: 0976-9102 (ONLINE)
-ICTACT JOURNAL ON IMAGE AND VIDEO PROCESSING, FEBRUARY 2017, VOLUME: 07, ISSUE: 03
-FACE RECOGNITION BASED ON LOCAL DERIVATIVE TETRA PATTERN
-A. Geetha1, M. Mohamed Sathik2 and Y. Jacob Vetharaj3
-Department of Computer Applications, Nesamony Memorial Christian College, India
-Department of Computer Science, Sadakathullah Appa College, India
-Department of Computer Science, Nesamony Memorial Christian College, India"
 921aaac9b33ec6a417bfc8bb0e21e11e743342c2,Image enhancement for improving face detection under non-uniform lighting conditions,"978-1-4244-1764-3/08/$25.00 ©2008 IEEE
 ICIP 2008"
 923412acb90ed2acbb29290147a567f39d2dfc95,FACS-BASED EMOTIONAL FACIAL EXPRESSIONS FACSGen : A Tool to Synthesize Emotional Facial Expressions through Systematic Manipulation of Facial Action Units,"J Nonverbal Behav
@@ -37607,9 +32030,6 @@ otherwise indicated. Previously published items are made available in accordance
 with the copyright policy of the publisher.
 http://www.sherpa.ac.uk/romeo/issn/0302-9743/
 https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm"
-92990ef7866ca906b595e2841e340725fb3ff8da,Generating Synthetic Data for Text Recognition,"Generating Synthetic Data for Text Recognition
-Praveen Krishnan and C.V. Jawahar
-CVIT, IIIT Hyderabad, India"
 92a044df6c37571aac25756252dda27676492bb5,IMPLEMENTATION OF REAL-TIME SYSTEM ON FPGA BOARD FOR HUMAN ' S FACE DETECTION AND TRACKING AUTHOR,"IMPLEMENTATION OF REAL-TIME SYSTEM ON FPGA BOARD FOR HUMAN'S
 FACE DETECTION AND TRACKING AUTHOR
 MOHD NORHAFIZ HASHIM
@@ -37665,26 +32085,6 @@ L’archive ouverte pluridisciplinaire HAL, est
 destinée au dépôt et à la diffusion de documents
 scientifiques de niveau recherche, publiés ou non,
 émanant des établissements d’enseignement et de"
-92980965514210b4f6dd074d122078d54684f724,Track Everything: Limiting Prior Knowledge in Online Multi-Object Recognition,"Track Everything: Limiting Prior Knowledge in
-Online Multi-Object Recognition
-Sebastien C. Wong∗, Senior Member, IEEE, Victor Stamatescu†, Member, IEEE, Adam Gatt‡, Member, IEEE,
-David Kearney†, Ivan Lee† Senior Member, IEEE and Mark D. McDonnell†, Senior Member, IEEE ∗ Defence
-Science and Technology Group, Edinburgh, SA, Australia † Computational Learning Systems Laboratory, School
-of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes, SA,
-Australia ‡ Australian Defence Force, Edinburgh, SA, Australia
-An important practical consideration in the design of online
-object recognition systems is the ﬁnite amount of labeled and
-nnotated data available for training. When scarce, this can de-
-grade classiﬁcation performance due to overﬁtting and reduce
-the detection probability of highly tuned object detectors. Even
-when larger data sets are available, these may be biased in such
-way that their image statistics do not accurately reflect the
-data encountered by the system at run time [2]. In the case
-of classiﬁer-based object recognition [3] and detection [4], the
-use of features, which are higher-level representations of an
-object than the raw image, can mitigate these problems by
-providing a degree of invariance across different data sets.
-In the case of tracking and object detection algorithms, the"
 927ac98da38db528b780f14996bb02b05009c9cc,Hand pose estimation through semi-supervised and weakly-supervised learning,"Hand Pose Estimation through Semi-Supervised and Weakly-Supervised Learning
 Natalia Neverovaa,∗, Christian Wolfa, Florian Neboutb, Graham W. Taylorc
 Universit´e de Lyon, INSA-Lyon, CNRS, LIRIS, F-69621, France
@@ -37743,21 +32143,6 @@ Ali Diba1
 , Mohsen Fayyaz2, Vivek Sharma3, A.Hossein Karami4, M.Mahdi Arzani4,
 Rahman Yousefzadeh4, Luc Van Gool1
 ESAT-PSI, KU Leuven, 2University of Bonn, 3CV:HCI, KIT, Karlsruhe, 4Sensifai"
-92a93693f43a49a7b320d5771c6afaff98b27864,Audio-visual signal processing in a multimodal assisted living environment,"INTERSPEECH 2014
-Audio-Visual Signal Processing in a Multimodal Assisted Living Environment
-Alexey Karpov 1,5, Lale Akarun 2, Hülya Yalçın 3, Alexander Ronzhin 1, Barış Evrim Demiröz 2,
-Aysun Çoban 2 and Miloš Železný 4
-St. Petersburg Institute for Informatics and Automation of Russian Academy of Sciences, Russia
-Boğaziçi University, İstanbul, Turkey
-İstanbul Technical University, İstanbul, Turkey
-University of West Bohemia, Pilsen, Czech Republic
-5 University ITMO, St. Petersburg, Russia"
-92115b620c7f653c847f43b6c4ff0470c8e55dab,Training Deformable Object Models for Human Detection Based on Alignment and Clustering,"Training Deformable Object Models for Human
-Detection Based on Alignment and Clustering
-Benjamin Drayer and Thomas Brox
-Department of Computer Science,
-Centre of Biological Signalling Studies (BIOSS),
-University of Freiburg, Germany"
 92b61b09d2eed4937058d0f9494d9efeddc39002,BoxCars: Improving Vehicle Fine-Grained Recognition using 3D Bounding Boxes in Traffic Surveillance,"Under review in IJCV manuscript No.
 (will be inserted by the editor)
 BoxCars: Improving Vehicle Fine-Grained Recognition using
@@ -37801,21 +32186,6 @@ Alice Mado Proverbio, Laura Ornaghi, and Veronica Gabaro
 Department of Psychology, Neuro-MI Center for Neuroscience, University of Milano-Bicocca, Milano, Italy
 Correspondence should be addressed to Alice Mado Proverbio, Department of Psychology, University of Milano-Bicocca, piazza dell’Ateneo Nuovo 1, U6
 Building, Milano, Italy. E-mail:"
-a3dc109b1dff3846f5a2cc1fe2448230a76ad83f,ACTIVE APPEARANCE MODEL AND PCA BASED FACE RECOGNITION SYSTEM,"J.Savitha et al, International Journal of Computer Science and Mobile Computing, Vol.4 Issue.4, April- 2015, pg. 722-731
-Available Online at www.ijcsmc.com
-International Journal of Computer Science and Mobile Computing
-A Monthly Journal of Computer Science and Information Technology
-ISSN 2320–088X
-IJCSMC, Vol. 4, Issue. 4, April 2015, pg.722 – 731
-RESEARCH ARTICLE
-ACTIVE APPEARANCE MODEL AND PCA
-BASED FACE RECOGNITION SYSTEM
-Mrs. J.Savitha M.Sc., M.Phil.
-Ph.D Research Scholar, Karpagam University, Coimbatore, Tamil Nadu, India
-Email:
-Dr. A.V.Senthil Kumar
-Director, Hindustan College of Arts and Science, Coimbatore, Tamil Nadu, India
-Email:"
 a3f1db123ce1818971a57330d82901683d7c2b67,Poselets and their applications in high-level computer vision,"Poselets and Their Applications in High-Level
 Computer Vision
 Lubomir Bourdev
@@ -37880,42 +32250,9 @@ Doctor of Philosophy
 Conrad Sanderson, BEng (Hons)
 August 2002
 [revised February 2003]"
-a308ad39f3cc25096f493280319621a25c2c7f46,Monocular 3D Scene Modeling and Inference: Understanding Multi-Object Traffic Scenes,"Monocular 3D Scene Modeling and Inference:
-Understanding Multi-Object Trafﬁc Scenes
-Christian Wojek1,2, Stefan Roth1, Konrad Schindler1,3, and Bernt Schiele1,2
-Computer Science Department, TU Darmstadt
-MPI Informatics, Saarbr¨ucken
-Photogrammetry and Remote Sensing Group, ETH Z¨urich"
 a32ebfa79097fdf5c9d44d2f74e33b7c8343425c,A Deeper Look at Dataset Bias,"Chapter 2
 A Deeper Look at Dataset Bias
 Tatiana Tommasi, Novi Patricia, Barbara Caputo and Tinne Tuytelaars"
-a3d8b5622c4b9af1f753aade57e4774730787a00,Pose-Aware Person Recognition,"Pose-Aware Person Recognition
-Vijay Kumar (cid:63)
-Anoop Namboodiri (cid:63)
-(cid:63) CVIT, IIIT Hyderabad, India
-Manohar Paluri †
-Facebook AI Research
-C. V. Jawahar (cid:63)"
-a3177f82ea8391d9d733be47e4a0656a7b56e64c,Emotion Researcher ISRE ' s Sourcebook for Research on Emotion and Affect,"Emotion Researcher | ISRE's Sourcebook for Research on Emotion and Affect
-Emotion Researcher
-ISRE's Sourcebook for Research on Emotion and Affect
-Interviews
-Articles
-Spotlight
-Contact
-How To Cite ER
-Table of Contents
-New Editor Search
-THE ROLES OF EMOTIONS IN THE LAW
-Time  for  new  blood  at  the  helm  of Emotion
-Researcher! ISRE is seeking one or more new
-editors,  who  should  take  over  in April 2017. It
-is a fun and highly rewarding job. Nominations
-of suitable candidates are also encouraged.
-Editor’s Column
-In this issue of Emotion Researcher, we focus on the roles emotions play in the law. We will explore
-the emotions of jurors, judges, defendants, attorneys and other legal actors.
-Call for Papers"
 a3ad32249fcc85ef9dfb2ea575b0c636edcb2da9,Local Appearance-based 3D Face Recognition,"Universit¨at Karlsruhe
 Fakult¨at f¨ur Informatik
 Institut f¨ur Theoretische Informatik (ITI)
@@ -37968,36 +32305,11 @@ D. M. Anisuzzaman
 Department of Computer Science and Engineering,
 Ahsanullah University of Science and Technology,
 Dhaka, Bangladesh"
-a3be57fc74460463f03c2a14e81e7e62c05c692e,Object Detection,"Object Detection
-Yali Amit and Pedro Felzenszwalb, University of Chicago
-Related Concepts
-– Object Recognition
-– Image Classiﬁcation
-Deﬁnition
-Object detection involves detecting instances of objects from a particular
-lass in an image.
-Background
-The goal of object detection is to detect all instances of objects from a known
-lass, such as people, cars or faces in an image. Typically only a small number
-of instances of the object are present in the image, but there is a very large
-number of possible locations and scales at which they can occur and that need
-to somehow be explored.
-Each detection is reported with some form of pose information. This could
-e as simple as the location of the object, a location and scale, or the extent
-of the object deﬁned in terms of a bounding box. In other situations the pose
-information is more detailed and contains the parameters of a linear or non-linear
-transformation. For example a face detector may compute the locations of the
-eyes, nose and mouth, in addition to the bounding box of the face. An example"
 a3eab933e1b3db1a7377a119573ff38e780ea6a3,Sparse Representation for accurate classification of corrupted and occluded facial expressions,"978-1-4244-4296-6/10/$25.00 ©2010 IEEE
 ICASSP 2010"
 a32c5138c6a0b3d3aff69bcab1015d8b043c91fb,Video redaction: a survey and comparison of enabling technologies,"Downloaded From: https://www.spiedigitallibrary.org/journals/Journal-of-Electronic-Imaging on 9/19/2018
 Terms of Use: https://www.spiedigitallibrary.org/terms-of-use
 Videoredaction:asurveyandcomparisonofenablingtechnologiesShaganSahAmeyaShringiRaymondPtuchaAaronBurryRobertLoceShaganSah,AmeyaShringi,RaymondPtucha,AaronBurry,RobertLoce,“Videoredaction:asurveyandcomparisonofenablingtechnologies,”J.Electron.Imaging26(5),051406(2017),doi:10.1117/1.JEI.26.5.051406."
-a33262933df8534de571027d78ccd936bb9ec263,Real-Time Deep Learning Method for Abandoned Luggage Detection in Video,"Real-Time Deep Learning Method for Abandoned Luggage Detection in Video
-University of Bucharest, 14 Academiei, Bucharest, Romania
-Sorina Smeureanu∗‡, Radu Tudor Ionescu∗‡
-SecurifAI, 24 Mircea Vod˘a, Bucharest, Romania
-E-mails:"
 a3fcf3d32a5a4fcc83027e3d367ecc0df3ec4f64,Iris Recognition: On the Segmentation of Degraded Images Acquired in the Visible Wavelength,"Iris Recognition: On the Segmentation
 of Degraded Images Acquired
 in the Visible Wavelength
@@ -38009,26 +32321,6 @@ Email: fsriparna r,"
 a3bf7248e38ed6f9456f0f309b36470c5c0dabd0,Predicting the Driver's Focus of Attention: the DR(eye)VE Project,"Predicting the Driver’s Focus of Attention:
 the DR(eye)VE Project
 Andrea Palazzi∗, Davide Abati∗, Simone Calderara, Francesco Solera, and Rita Cucchiara"
-a32f28156b47fd262e04426806037d138bb3ed0b,Fisher ’ s linear discriminant ( FLD ) and support vector machine ( SVM ) in non-negative matrix factorization ( NMF ) residual space for face recognition,"Optica Applicata, Vol. XL, No. 3, 2010
-Fisher’s linear discriminant (FLD)
-nd support vector machine (SVM)
-in non-negative matrix factorization (NMF)
-residual space for face recognition
-CHANGJUN ZHOU, XIAOPENG WEI*, QIANG ZHANG, XIAOYONG FANG
-Key Laboratory of Advanced Design and Intelligent Computing, Dalian University,
-Ministry of Education, Dalian, 116622, China
-*Corresponding author:
-A novel method of Fisher’s linear discriminant (FLD) in the residual space is put forward for
-the  representation  of  face  images  for  face  recognition,  which  is  robust  to  the  slight  local
-feature changes. The residual images are computed by subtracting the reconstructed images from
-the original face images, and the reconstructed images are obtained by performing non-negative
-matrix factorization (NMF) on original images. FLD is applied to the residual images for extracting
-FLD subspace and the corresponding coefficient matrices. Furthermore, features are obtained by
-mapping the residual image to FLD subspace. Finally, the features are utilized to train and test
-support vector machines (SVMs) for face recognition. The computer simulation illustrates that
-this method is effective on the ORL database and the extended Yale face database B.
-Keywords: face recognition, Fisher linear discriminant (FLD), non-negative matrix factorization (NMF),
-residual image."
 a30e987e9909a4e307c35809275cf80431211f22,Automatic Sapstain Detection in Processed Timber Through Image Feature Analysis,"Automatic Sapstain Detection in Processed
 Timber Through Image Feature Analysis
 Jeremiah Deng
@@ -38155,14 +32447,6 @@ teaching and research institutions in France or
 broad, or from public or private research centers.
 L’archive ouverte pluridisciplinaire HAL, est
 destinée au dépôt et à la diffusion de documents"
-79033ec1b2c86034908febd444d6ed3c753e17b3,Face Recognition via Globality-Locality Preserving Projections,"Face Recognition via Globality-Locality Preserving Projections
-Sheng Huanga,∗, Dan Yanga,b, Fei Yangc, Yongxin Geb,d, Xiaohong Zhangb,d, Jiwen Lue
-College of Computer Science at Chongqing University, Chonqing, 400044, China
-School of Software Engineering at Chongqing University Chonqing, 400044, China
-Department of Computer Science at Rutgers University, Piscataway, NJ, 08854, USA
-dMinistry of Education Key Laboratory of Dependable Service Computing in Cyber Physical Society at Chongqing
-University Chonqing, 400044, China
-eAdvanced Digital Sciences Center (ADSC), 138632, Singapore"
 79b669abf65c2ca323098cf3f19fa7bdd837ff31,Efficient tensor based face recognition,"Deakin Research Online
 This is the published version:
 Rana, Santu, Liu, Wanquan, Lazarescu, Mihai and Venkatesh, Svetha 2008, Efficient tensor
@@ -38243,9 +32527,6 @@ October 2016"
 Arman Boehm(cid:91), Dongqu Chen§, Mario Frank(cid:91), Ling Huang†,
 Cynthia Kuo(cid:93), Tihomir Lolic(cid:91), Ivan Martinovic(cid:63), Dawn Song(cid:91)
 (cid:91) University of California, Berkeley; † Intel Labs; (cid:93) Nokia Research; (cid:63) Oxford University; § Yale University"
-79bd7fd2b40aadea84bced07f813ffc28c88bc85,Low-Rank Matrix Recovery With Simultaneous Presence of Outliers and Sparse Corruption,"Low Rank Matrix Recovery with Simultaneous
-Presence of Outliers and Sparse Corruption
-Mostafa Rahmani, Student Member, IEEE and George K. Atia, Member, IEEE"
 7960336aed2aa701c147ccfe36d153046f1500bc,Occlusion Reasoning for Multiple Object Visual Tracking Dissertation Occlusion Reasoning for Multiple Object Visual Tracking Occlusion Reasoning for Multiple Object Visual Tracking,"OCCLUSION REASONING
 FOR MULTIPLE OBJECT VISUAL TRACKING
 ZHENG WU
@@ -38315,9 +32596,6 @@ Center for Visual Computing, CentraleSup´elec, Inria, Universit´e Paris-Saclay
 Grande Voie des Vignes, 92295 Chˆatenay-Malabry, France
 Center for Processing Speech and Images, Dept. Elektrotechniek, KU Leuven,
 Kasteelpark Arenberg 10, 3001 Leuven, Belgium"
-79c959833ff49f860e20b6654dbf4d6acdee0230,Hide-and-Seek: A Data Augmentation Technique for Weakly-Supervised Localization and Beyond,"Hide-and-Seek: A Data Augmentation Technique
-for Weakly-Supervised Localization and Beyond
-Krishna Kumar Singh, Hao Yu, Aron Sarmasi, Gautam Pradeep, and Yong Jae Lee, Member, IEEE"
 7903bccf6f98436f4916419e5450d1bb890876ea,Analysis of Spatiotemporal Ensemble Data Using Machine Learning,"Institut für Visualisierung und Interaktive Systeme
 Universität Stuttgart
 Universitätsstraße 38
@@ -38470,19 +32748,6 @@ Throughout this chapter, (cid:107)·(cid:107) denotes the standard Euclidean nor
 Problem (1) generalizes the more thoroughly studied class of composite convex optimization prob-
 lems [30], a class that has witnessed huge interest in machine learning, signal processing, statistics,
 nd other related areas. We refer the interested reader to [2, 3, 21, 37] for several convex examples"
-1dc4b5e93233fc632b070c8ff282ef0fe9141f64,2-D Structure-Based Gait Recognition in Video Using Incremental GMM-HMM,"-D Structure-Based Gait Recognition in Video
-Using incremental GMM-HMM
-Rui Pu1, Yunhong Wang1
-Laboratory of Intelligence Recognition and Image Processing, Beijing Key
-Laboratory of Digital Media, School of Computer Science and Engineering, Beihang
-University, Beijing 100191, China"
-1d5901662dc4fa5be2375f35be07b4116fd450ea,The Effects of Prediction on the Perception for Own-Race and Other-Race Faces,"RESEARCH ARTICLE
-The Effects of Prediction on the Perception
-for Own-Race and Other-Race Faces
-Guangming Ran1,2, Qi Zhang3, Xu Chen1,2*, Yangu Pan1,2
-. Faculty of Psychology, Southwest University (SWU), Chongqing, 400715, China, 2. Research Center of
-Mental Health Education, Southwest University (SWU), Chongqing, 400715, China, 3. School of Education
-Science, Guizhou Normal University (GNU), Guizhou, 550001, China"
 1d58d83ee4f57351b6f3624ac7e727c944c0eb8d,Enhanced Local Texture Feature Sets for Face Recognition Under Difficult Lighting Conditions,"Enhanced Local Texture
 Feature Sets for Face
 Recognition under Difficult
@@ -38719,10 +32984,6 @@ Video Analytics On Surveillance Cameras
 Pratik Dubal(cid:63), Rohan Mahadev(cid:63), Suraj Kothawade(cid:63),
 Kunal Dargan, and Rishabh Iyer
 AitoeLabs (www.aitoelabs.com)"
-1da83903c8d476c64c14d6851c85060411830129,Iterated Support Vector Machines for Distance Metric Learning,"Iterated Support Vector Machines for Distance
-Metric Learning
-Wangmeng Zuo, Member, IEEE, Faqiang Wang, David Zhang, Fellow, IEEE, Liang Lin, Member, IEEE,
-Yuchi Huang, Member, IEEE, Deyu Meng, and Lei Zhang, Senior Member, IEEE"
 1d1e78bb93590a86ecfd2516f4e5789cc05d76f5,Generative Models,"FACE AUTHENTICATION BASED ON
 LOCAL FEATURES AND
 GENERATIVE MODELS
@@ -38730,19 +32991,6 @@ Fabien Cardinaux (a)
 IDIAP–RR 05-85
 JANUARY 2006
 ESEARCHREPRORTIDIAPRue du Simplon 4IDIAP Research Institute1920 Martigny − Switzerlandwww.idiap.chTel: +41 27 721 77 11Email: Box 592Fax: +41 27 721 77 12"
-1d87a5a458e5fdcfc70e1a444903bb6d7bb0ca38,Biometric Approach to Facial Signature Authentication using Thermal Imaging B,"www.semargroup.org,
-www.ijsetr.com
-ISSN 2319-8885
-Vol.03,Issue.26
-September-2014,
-Pages:5165-5171
-Biometric Approach to Facial Signature Authentication using Thermal Imaging
-BOMMAGANI SURESH
-, G.S.NAVEENKUMAR
-PG Scholar, Dept of ECE, Mallareddy College of Engineering and Technology, Secunderabad, India,
-Assoc Prof, Dept of ECE, Mallareddy College of Engineering and Technology, Secunderabad, India,
-Email:
-E-mail:"
 1d524c57214384ad6a003c54b1918130744b69d2,Identifying Human-Object Interactions in Motionless Images by Modeling the Mutual Context of Objects and Human Poses,"International Journal of Science and Research (IJSR)
 ISSN (Online): 2319-7064
 Impact Factor (2012): 3.358
@@ -38769,14 +33017,6 @@ POSTECH, Korea"
 with First Name Attributes
 Huizhong Chen, Student Member, IEEE, Andrew C. Gallagher, Senior Member, IEEE, and
 Bernd Girod, Fellow, IEEE"
-1d251acc459931d927f5befdfb5b9cdf643cd8bc,Bayesian Compression for Natural Language Processing,"Bayesian Compression for Natural Language Processing
-Nadezhda Chirkova1∗, Ekaterina Lobacheva1∗, Dmitry Vetrov1,2
-Samsung-HSE Laboratory, National Research University Higher School of Economics
-Samsung AI Center
-Moscow, Russia"
-1dca6a54d201dd56b41a5475aaf498a207083b0e,Ego-surfing first person videos,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
-Ego-Surﬁng First-Person Videos
-Ryo Yonetani, Member, IEEE, Kris M. Kitani, Member, IEEE, and Yoichi Sato, Member, IEEE"
 1d9bd24e65345258259ee24332141e371c6e4868,Learning Image Descriptors with Boosting,"Learning Image Descriptors with Boosting
 Tomasz Trzcinski, Mario Christoudias, and Vincent Lepetit"
 1d5d68bee741d81771e9224fe53806e85ed469aa,RATM: Recurrent Attentive Tracking Model,"RATM: Recurrent Attentive Tracking Model
@@ -38798,18 +33038,6 @@ Cordelia Schmid†"
 1df554e992baf60f2d0b7c1b563250ba19b8f8ff,3D Face Recognition Based on 3D Ridge Lines in Range Data,"-4244-1437-7/07/$20.00 ©2007 IEEE
 I - 137
 ICIP 2007"
-1d4e0427dffec6ac75b96a564986046ea2b00980,Eye Controlled Robotic Motion Using Video Tracking In Real Time,"ISSN(Online): 2319-8753
-ISSN (Print):  2347-6710
-International Journal of Innovative Research in Science,
-Engineering and Technology
-(An ISO 3297: 2007 Certified Organization)
-Website: www.ijirset.com
-Vol. 6, Issue 7, July 2017
-Eye Controlled Robotic Motion Using Video
-Tracking In Real Time
-Kriti Bhattacharjee 1, Dr. Manoj Soni 2
-P.G. Student, Department of Mechanical and Automation Engineering, IGDTUW, New Delhi, India1
-Associate Professor, Department of Mechanical and Automation Engineering, IGDTUW, New Delhi, India2"
 1daf18f2b1bed861a9483de129223755260193fa,Near-Eye Display Gaze Tracking via Convolutional Neural Networks,"Near-Eye Display Gaze Tracking via Convolutional Neural Networks
 Robert Konrad
 Shikhar Shrestha
@@ -38819,26 +33047,6 @@ Features
 Jesús García-Ramírez, Ivan Olmos-Pineda, J. Arturo Olvera-López, and
 Manuel Martín-Ortíz
 Benemérita Universidad Autónoma de Puebla, Faculty of Computer Science, Puebla, México"
-1dff919e51c262c22630955972968f38ba385d8a,Toward an Affect-Sensitive Multimodal Human – Computer Interaction,"Toward an Affect-Sensitive Multimodal
-Human–Computer Interaction
-MAJA PANTIC, MEMBER, IEEE, AND LEON J. M. ROTHKRANTZ
-Invited Paper
-The ability to recognize affective states of a person we are com-
-municating with is the core of emotional intelligence. Emotional
-intelligenceisa facet of human intelligence thathas been argued to be
-indispensable and perhaps the most important for successful inter-
-personal social interaction. This paper argues that next-generation
-human–computer interaction (HCI) designs need to include the
-essence of emotional intelligence—the ability to recognize a user’s
-ffective states—in order to become more human-like, more effec-
-tive, and more efficient. Affective arousal modulates all nonverbal
-ommunicative cues (facial expressions, body movements, and vocal
-nd physiological reactions). In a face-to-face interaction, humans
-detect and interpret those interactive signals of their communicator
-with little or no effort. Yet design and development of an automated
-system that accomplishes these tasks is rather difficult. This paper
-surveys the past work in solving these problems by a computer
-nd provides a set of recommendations for developing the first"
 1d1f83023686d43fd4e8805c8e517dffb02d118c,Compiler Enhanced Scheduling for OpenMP for Heterogeneous Multiprocessors,"Compiler Enhanced Scheduling for OpenMP for
 Heterogeneous Multiprocessors
 Jyothi Krishna V S
@@ -38913,11 +33121,6 @@ Universiti Sains Malaysia, Malaysia,
 Universiti Sains Malaysia, Malaysia,
 Universiti Sains Malaysia, Malaysia,
 Universiti Sains Malaysia, Malaysia,"
-d3d887aebeeae44cefd5c2bdbb388d9ce109e335,Image Manipulation with Perceptual Discriminators,"Image Manipulation with
-Perceptual Discriminators
-Diana Sungatullina(cid:63), Egor Zakharov(cid:63), Dmitry Ulyanov, and Victor Lempitsky
-Skolkovo Institute of Science and Technology, Moscow, Russia
-{d.sungatullina, egor.zakharov, dmitry.ulyanov,"
 d3797366259182070c598e95cef8fff1ddb21f65,Distance-based Camera Network Topology Inference for Person Re-identification,"Distance-based Camera Network Topology Inference for Person Re-identiﬁcation
 Yeong-Jun Cho and Kuk-Jin Yoon
 Computer Vision Laboratory, GIST, South Korea
@@ -39027,17 +33230,6 @@ School of Computer Science, University of Guelph
 School of Engineering, University of Guelph
 Vector Institute for Artiﬁcial Intelligence
 Canadian Institute for Advanced Research"
-d33fcdaf2c0bd0100ec94b2c437dccdacec66476,Neurons With Paraboloid Decision Boundaries for Improved Neural Network Classification Performance.,"Neurons with Paraboloid Decision Boundaries for
-Improved Neural Network Classiﬁcation
-Performance
-Nikolaos Tsapanos, Anastasios Tefas, Member, IEEE, Nikolaos Nikolaidis, Member, IEEE, and
-Ioannis Pitas, Fellow, IEEE"
-d3c004125c71942846a9b32ae565c5216c068d1e,Recognizing Age-Separated Face Images: Humans and Machines,"RESEARCH ARTICLE
-Recognizing Age-Separated Face Images:
-Humans and Machines
-Daksha Yadav1, Richa Singh2, Mayank Vatsa2*, Afzel Noore1
-. West Virginia University, Morgantown, West Virginia, United States of America, 2. IIIT Delhi, New Delhi,
-Delhi, India"
 d31e47f45041736c93ec23ba1dbaef6c311e76d6,TÜB İ TAK UZAY at TRECVID 2009 : High-Level Feature Extraction and Content-Based Copy Detection,"TÜBİTAK UZAY at TRECVID 2009: High-Level Feature Extraction and
 Content-Based Copy Detection
 Ahmet Saracoğlu1,2, Ersin Esen1,2, Medeni Soysal1,2, Tuğrul K. Ateş1,2, Berker Loğoğlu1, Mashar Tekin1,
@@ -39118,33 +33310,10 @@ Camera Network Topology Inference in Camera Networks
 Yeong-Jun Cho, Jae-Han Park*, Su-A Kim*, Kyuewang Lee and Kuk-Jin Yoon
 Computer Vision Laboratory, GIST, South Korea
 {yjcho, qkrwogks, suakim, kyuewang,"
-8f00c57218b413440bc99bcd1b2a9dce369f0f4f,Role of Active Pixels for Efficient Face Recognition on Mobile Environment,"Role of Active Pixels for Efficient Face Recognition on Mobile
-Environment
-Mallikarjuna Rao G1
-Gokaraju Rangaraju Institute of
-Engineering and
-Technology,Bachupally,
-Hyderabad-78. A.P, India
-Praveen Kumar1
-Gokaraju Rangaraju Institute of
-Engineering and
-Technology,Bachupally, Hyderabad-
-78. A.P, India
-Vijaya Kumari  G2
-Jawaharlal Nehru Technological
-University Hyderabad, Computer
-Science Department,
-Hyderabad ,A.P,   India
-Amit Pande3
-Computer Science Department,
-University of California-Davis,"
 8ff3c7b46ab36f1d01e96681baf512859cc80a4d,Dynamics of alpha oscillations elucidate facial affect recognition in schizophrenia.,"Dynamics of alpha oscillations elucidate facial affect
 recognition in schizophrenia
 Tzvetan G. Popov & Brigitte S. Rockstroh & Petia Popova &
 Almut M. Carolus & Gregory A. Miller"
-8fbe68810cbc53521395829620060cf9558231cc,Learning Discriminant Person-Specific Facial Models Using Expandable Graphs,"Learning Discriminant Person-Speciﬁc
-Facial Models Using Expandable Graphs
-Stefanos Zafeiriou, Anastasios Tefas, Member, IEEE, and Ioannis Pitas, Fellow, IEEE"
 8fc21217ee89c505930b540b716b11bab89d3bcd,Memory Efficient Nonuniform Quantization for Deep Convolutional Neural Network,"Memory Efﬁcient Nonuniform Quantization for
 Deep Convolutional Neural Network
 Fangxuan Sun and Jun Lin"
@@ -39201,9 +33370,6 @@ Yuhua Chen1 Wen Li1 Christos Sakaridis1 Dengxin Dai1
 Luc Van Gool1,2
 Computer Vision Lab, ETH Zurich
 VISICS, ESAT/PSI, KU Leuven"
-8f89aed13cb3555b56fccd715753f9ea72f27f05,Attended End-to-end Architecture for Age Estimation from Facial Expression Videos.,"Attended End-to-end Architecture for Age
-Estimation from Facial Expression Videos
-Wenjie Pei, Hamdi Dibeklio˘glu, Member, IEEE, Tadas Baltruˇsaitis and David M.J. Tax"
 8fc730d22f33d08be927e5449f359dc15b5c3503,Measuring and modeling the perception of natural and unconstrained gaze in humans and machines,"CBMM Memo No. 059
 November 28, 2016
 Measuring and modeling the perception of natural
@@ -39267,13 +33433,6 @@ Equinox Corporation
 07 East Redwood Street
 New York, NY 10019
 Baltimore, MD 21202"
-8f3e3f0f97844d3bfd9e9ec566ac7a54f6931b09,"A Survey on Human Emotion Recognition Approaches, Databases and Applications","Electronic Letters on Computer Vision and Image Analysis 14(2):24-44; 2015
-A Survey on Human Emotion Recognition Approaches,
-Databases and Applications
-C.Vinola*, K.Vimaladevi†
-* Department of Computer Science and Engineering, Francis Xavier Engineering College, Tirunelveli,Tamilnadu,India
-Department of Computer Science and Engineering, P.S.R Engineering College, Sivakasi, Tamilnadu,India
-Received 7th Aug 2015; accepted 30th Nov 2015"
 8f077eeeb9678a31e77a17a5c28c36699cf13f83,Gender classification of faces using adaboost,"Gender Classification of Faces Using Adaboost*
 Rodrigo Verschae1,2,3, Javier Ruiz-del-Solar1,2, and Mauricio Correa1,2
 Department of Electrical Engineering, Universidad de Chile
@@ -39340,10 +33499,6 @@ Network of Excellence
 01 June, 2004
 6 months
 D2.2.1"
-8f4c8a80e94a883356ee4c4425324dac5457661a,Noise Robust Face Image Super-Resolution Through Smooth Sparse Representation,"This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination.
-Noise Robust Face Image Super-Resolution
-Through Smooth Sparse Representation
-Junjun Jiang, Member, IEEE, Jiayi Ma, Member, IEEE, Chen Chen, Xinwei Jiang, and Zheng Wang"
 8fa3478aaf8e1f94e849d7ffbd12146946badaba,Attributes for classifier feedback,"Attributes for Classiﬁer Feedback
 Amar Parkash1 and Devi Parikh2
 Indraprastha Institute of Information Technology (Delhi, India)
@@ -39407,14 +33562,6 @@ Marina del Rey, CA 90292
 Allon G. Percus
 Claremont Graduate U.
 Claremont, CA 91711"
-912f1f57a010194047b6438cc1ea6bec95c6c2b8,ContextVP: Fully Context-Aware Video Prediction,"ContextVP: Fully Context-Aware Video
-Prediction
-Wonmin Byeon1,2,3,4, Qin Wang2,
-Rupesh Kumar Srivastava4, and Petros Koumoutsakos2
-NVIDIA, Santa Clara, CA, USA
-ETH Zurich, Zurich, Switzerland
-The Swiss AI Lab IDSIA, Manno, Switzerland
-NNAISENSE, Lugano, Switzerland"
 91d83d20cc22bde6b4b06afc87f76a1b0140d4e2,Image Classification Based on Quantum KNN Algorithm,"Noname manuscript No.
 (will be inserted by the editor)
 Image Classiﬁcation Based on Quantum KNN
@@ -39445,12 +33592,6 @@ Time Based Re-ranking for Web Image Search
 Ms. A.Udhayabharadhi *, Mr. R.Ramachandran **
 * MCA Student, Sri Manakula Vinayagar Engineering College, Pondicherry-605106
 ** Assistant Professor dept of MCA, Sri Manakula Vinayagar Engineering College, Pondicherry-605106"
-91c014ff243ea747ea3a84a9efd4a3e38a7217ee,Reinforced Temporal Attention and Split-Rate Transfer for Depth-Based Person Re-identification,"Reinforced Temporal Attention and Split-Rate
-Transfer for Depth-Based Person
-Re-Identiﬁcation
-Nikolaos Karianakis1, Zicheng Liu1, Yinpeng Chen1, and Stefano Soatto2
-Microsoft, Redmond, USA
-University of California, Los Angeles, USA"
 91ddac7d1d63c52cbe30fe27674b9c1e54bc584c,Development of EyeBlink and Face Corpora for Research in Human Computer Interaction,"(IJACSA) International Journal of Advanced Computer Science and Applications,
 Vol. 6, No. 5, 2015
 Development of Eye-Blink and Face Corpora for
@@ -39511,9 +33652,6 @@ FEEDTUM Database, CK+ Database."
 91811203c2511e919b047ebc86edad87d985a4fa,Expression Subspace Projection for Face Recognition from Single Sample per Person,"Expression Subspace Projection for Face
 Recognition from Single Sample per Person
 Hoda Mohammadzade, Student Member, IEEE, and Dimitrios Hatzinakos, Senior Member, IEEE"
-91ee88754cc7a193d51656a3b53e16389bf4aadb,Fast and accurate algorithm for eye localisation for gaze tracking in low-resolution images,"Fast and Accurate Algorithm for Eye Localization
-for Gaze Tracking in Low Resolution Images
-Anjith George, Member, IEEE, and Aurobinda Routray, Member, IEEE"
 91d513af1f667f64c9afc55ea1f45b0be7ba08d4,Automatic Face Image Quality Prediction,"Automatic Face Image Quality Prediction
 Lacey Best-Rowden, Student Member, IEEE, and Anil K. Jain, Life Fellow, IEEE"
 91e58c39608c6eb97b314b0c581ddaf7daac075e,Pixel-wise Ear Detection with Convolutional Encoder-Decoder Networks,"Pixel-wise Ear Detection with Convolutional
@@ -39543,15 +33681,6 @@ Departm
 ment of Electrical and Electronic Engineering
 he University of Hong Kong, Pokfulam,
 Hong Kong"
-91f2b2aeb7e65d0b673ed7e782488b3365027979,NUS-PRO: A New Visual Tracking Challenge,"NUS-PRO: A New Visual Tracking Challenge
-Annan Li, Member, IEEE, Min Lin, Member, IEEE, Yi Wu, Member, IEEE,
-Ming-Hsuan Yang, Senior Member, IEEE, and Shuicheng Yan, Senior Member, IEEE"
-914fd65d29094e434346806bdddeb17d9468610d,SCENE TEXT RECOGNITION IN MOBILE APPLICATIONS BY CHARACTER DESCRIPTOR AND STRUCTURE CONFIGURATION,"IJRET: International Journal of Research in Engineering and Technology        eISSN: 2319-1163 | pISSN: 2321-7308
-SCENE TEXT RECOGNITION IN MOBILE APPLICATIONS BY
-CHARACTER DESCRIPTOR AND STRUCTURE CONFIGURATION
-Sathish Kumar Penchala1, Pallavi S.Umap2
-Assistant Professor, Dept. of Computer Engineering, Dr. D.Y.Patil SOET., Lohegaon, Pune-47, Maharashtra, India
-ME 2nd year, Dept. of Computer Engineering, Dr.D.Y.Patil SOET., Lohegaon, Pune-47, Maharashtra India"
 9168b36568b8abffab5b9de029be5941f673dca2,Improving 3 D Facial Action Unit Detection with Intrinsic Normalization,"YUDIN, ET AL.: IMPROVING 3D AU DETECTION WITH INTRINSIC NORMALIZATION
 Improving 3D Facial Action Unit Detection
 with Intrinsic Normalization
@@ -39605,8 +33734,6 @@ Decomposition
 Muwei Jian,  Kin-Man Lam*, Senior Member, IEEE
 (SVD)
 for  performing  both"
-9131c990fad219726eb38384976868b968ee9d9c,Deep Facial Expression Recognition: A Survey,"Deep Facial Expression Recognition: A Survey
-Shan Li and Weihong Deng∗, Member, IEEE"
 91a5897565818631a32ce4edae5548d2baf99d77,APPROACH TO RECOGNIZING FACES UNDER VARYING POSE GIVEN A SINGLE-VIEW,"The Pennsylvania State University
 The Graduate School
 College of Engineering
@@ -39663,26 +33790,6 @@ Zaid Harchaouia,b
 NYU
 Inria∗
 Cordelia Schmida"
-208f0e4195e22e8079ee894397b7a3d1ce99091b,Identifying implementation bugs in machine learning based image classifiers using metamorphic testing,"Identifying Implementation Bugs in Machine Learning Based
-Image Classifiers using Metamorphic Testing
-Anurag Dwarakanath
-Accenture Technology Labs
-Bangalore, India
-Raghotham M. Rao
-Accenture Technology Labs
-Bangalore, India
-Manish Ahuja
-Accenture Technology Labs
-Bangalore, India
-R. P. Jagadeesh Chandra Bose
-Accenture Technology Labs
-Bangalore, India
-Samarth Sikand
-Accenture Technology Labs
-Bangalore, India
-Neville Dubash
-Accenture Technology Labs
-Bangalore, India"
 20f9a09defe5b02b98c464ca6df36b3b6358f60b,The State-of-the-Art in Visual Object Tracking,Volume 36 Number 3 September 2012
 2049ca79ce94ddfe0cc3d39bf770f580a740f3ac,Activity analysis : finding explanations for sets of events,ActivityAnalysis:FindingExplanationsforSetsofEventsbyDimaJamalAlDamenSubmittedinaccordancewiththerequirementsforthedegreeofDoctorofPhilosophy.TheUniversityofLeedsSchoolofComputingSeptember2009Thecandidateconﬁrmsthattheworksubmittedisherownandthattheappropriatecredithasbeengivenwherereferencehasbeenmadetotheworkofothers.Thiscopyhasbeensuppliedontheunderstandingthatitiscopyrightmaterialandthatnoquotationfromthethesismaybepublishedwithoutproperacknowledgement.
 20928315086a49e0cdea0ec66f2e78e9c564f794,Person Detection for Indoor Videosurveillance Using Spatio-temporal Integral Features,"Person Detection for Indoor Videosurveillance
@@ -39782,10 +33889,6 @@ Elena Battini S˝onmez1, Bulent Sankur2 and Songul Albayrak3
 Computer Science Department, Bilgi University, Dolapdere, Istanbul, TR
 Electric and Electronic Engineering Department, Bo¯gazici University, Istanbul, TR
 Computer Engineering Department, Yıldız Teknik University, Istanbul, TR"
-20532b1f80b509f2332b6cfc0126c0f80f438f10,A Deep Matrix Factorization Method for Learning Attribute Representations,"A deep matrix factorization method for learning
-ttribute representations
-George Trigeorgis, Konstantinos Bousmalis, Student Member, IEEE, Stefanos Zafeiriou, Member, IEEE
-Bj¨orn W. Schuller, Senior member, IEEE"
 205b34b6035aa7b23d89f1aed2850b1d3780de35,Log-domain polynomial filters for illumination-robust face recognition,"014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP)
 978-1-4799-2893-4/14/$31.00 ©2014 IEEE
 Shenzhen Key Lab. of Information Sci&Tech,
@@ -39839,28 +33942,6 @@ Corporate Research and Development Center, Toshiba Corporation
 203fcd66c043e44fefd783b8f54105f0a577fc25,Analyzing Content and Customer Engagement in Social Media with Deep Learning,"Analyzing Content and Customer Engagement in
 Social Media with Deep Learning
 (The bulk of this work was done by a student.)"
-20a052963f2c46aff817f34a09c396c44b3e46da,Visually Grounded Meaning Representations,"Visually Grounded Meaning Representations
-Carina Silberer, Member, IEEE, Vittorio Ferrari, Member, IEEE, Mirella Lapata, Member, IEEE"
-2004afb2276a169cdb1f33b2610c5218a1e47332,Deep Convolutional Neural Network Used in Single Sample per Person Face Recognition,"Hindawi
-Computational Intelligence and Neuroscience
-Volume 2018, Article ID 3803627, 11 pages
-https://doi.org/10.1155/2018/3803627
-Research Article
-Deep Convolutional Neural Network Used in Single Sample per
-Person Face Recognition
-Junying Zeng , Xiaoxiao Zhao , Junying Gan , Chaoyun Mai
-nd Fan Wang
-, Yikui Zhai,
-School of Information Engineering, Wuyi University, Jiangmen 529020, China
-Correspondence should be addressed to Xiaoxiao Zhao;
-Received 27 November 2017; Revised 23 May 2018; Accepted 26 July 2018; Published 23 August 2018
-Academic Editor: Jos´e Alfredo Hern´andez-P´erez
-Copyright © 2018 Junying Zeng et al. 0is is an open access article distributed under the Creative Commons Attribution License,
-which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
-Face recognition (FR) with single sample per person (SSPP) is a challenge in computer vision. Since there is only one sample to be
-trained, it makes facial variation such as pose, illumination, and disguise dif‌f‌icult to be predicted. To overcome this problem, this paper
-proposes a scheme combined traditional and deep learning (TDL) method to process the task. First, it proposes an expanding sample
-method based on traditional approach. Compared with other expanding sample methods, the method can be used easily and"
 2056ba48e687d619c0ce69d0be323d48c5b90701,Similarity Mapping with Enhanced Siamese Network for Multi-Object Tracking.,"Similarity Mapping with Enhanced Siamese Network
 for Multi-Object Tracking
 Minyoung Kim
@@ -39965,11 +34046,6 @@ destinée au dépôt et à la diffusion de documents
 scientifiques de niveau recherche, publiés ou non,
 émanant des établissements d’enseignement et de
 recherche français ou étrangers, des laboratoires"
-20f64a00593ae2c6ebbe87b41394335152f9b165,A Hybrid of Principal Component Analysis and Partial Least Squares for Face Recognition across Pose,"A Hybrid of Principal Component Analysis and Partial
-Least Squares for Face Recognition across Pose
-Ajay Jaiswal, Nitin Kumar, and R.K. Agrawal
-School of Computer and Systems Sciences
-Jawaharlal Nehru University, New Delhi, India"
 2084e54505cfe4fd81005167b1b11d10b5f837d1,Person Re-Identification by Discriminative Selection in Video,"Person Re-Identification by Discriminative Selection in Video Ranking
 Wang, T; Gong, S; Zhu, X; Wang, S
 •(cid:9)“The final publication is available at http://link.springer.com/chapter/10.1007%2F978-3-319-
@@ -39997,22 +34073,6 @@ Antoine Deleforge∗ Radu Horaud∗ Yoav Y. Schechner‡ Laurent Girin∗†
 INRIA Grenoble Rhˆone-Alpes, Montbonnot Saint-Martin, France
 Univ. Grenoble Alpes, GIPSA-Lab, France
 Dept. Electrical Eng., Technion-Israel Inst. of Technology, Haifa, Israel"
-c45a6a816c32d4041f9be8b937fa92d6dddfe476,FACE RECOGNITION BASED ATTENDANCE MARKING SYSTEM,"K.Senthamil Selvi et al, International Journal of Computer Science and Mobile Computing, Vol.3 Issue.2, February- 2014, pg. 337-342
-Available Online at www.ijcsmc.com
-International Journal of Computer Science and Mobile Computing
-A Monthly Journal of Computer Science and Information Technology
-ISSN 2320–088X
-IJCSMC, Vol. 3, Issue. 2, February 2014, pg.337 – 342
-RESEARCH ARTICLE
-FACE RECOGNITION BASED
-ATTENDANCE MARKING SYSTEM
-K.Senthamil Selvi1, P.Chitrakala2, A.Antony Jenitha3
-M. Tech Scholar, Department of Information and Technology,
-Hindustan University, Chennai, Tamilnadu, India
-Assistant Professor, Department of Information and Technology,
-Hindustan University, Chennai, Tamilnadu, India
-M. Tech Scholar, Department of Information and Technology,
-Hindustan University, Chennai, Tamilnadu, India"
 c4dcf41506c23aa45c33a0a5e51b5b9f8990e8ad,Understanding Activity : Learning the Language of Action,"Understanding Activity: Learning the Language of Action
 Randal Nelson and Yiannis Aloimonos
 Univ. of Rochester and Maryland
@@ -40070,13 +34130,6 @@ Steve Branson · Grant Van Horn · Catherine Wah ·
 Pietro Perona · Serge Belongie
 Received: 7 March 2013 / Accepted: 8 January 2014 / Published online: 20 February 2014
 © Springer Science+Business Media New York 2014"
-c450b742717dd56039466c3f761982355bd0576a,Literature Assessment for Pose-Invariant Face Recognition,"International Journal of Scientific Research Engineering & Technology (IJSRET)
-Volume 2 Issue 10   pp 653-658 January 2014
-www.ijsret.org            ISSN 2278 – 0882
-Literature Assessment for Pose-Invariant Face Recognition
-S.Jebha, P.KANNAN
-PG Scholar Department of ECE, PET Engineering College, India
-Professor Department of ECE, PET Engineering College, India"
 c4baa3d2fe702d3e96c500274f7fd9e63f8b3d6d,Pedestrian Detection Optimization Based on Random Filtering,"Pedestrian Detection Optimization Based on
 Random Filtering
 Victor Hugo Cunha de Melo, Samir Le˜ao, William Robson Schwartz
@@ -40120,12 +34173,6 @@ c4827fe8002ea61a2748b78369afe3a0747d1a0c,Towards Optimal Naive Bayes Nearest Nei
 R´egis Behmo1, Paul Marcombes1,2, Arnak Dalalyan2, and V´eronique Prinet1
 NLPR / LIAMA, Institute of Automation, Chinese Academy of Sciences(cid:2)
 IMAGINE, LIGM, Universit´e Paris-Est"
-c4a5932f33e6f4ccbfc7218fac58350a530d0ad6,Face Recognition using Discriminant Face Features Extraction method,"Face Recognition using Discriminant Face Features Extraction method
-Miss. Poonam S. Sharma1, Prof. Nitin R. Chopde2
-Student of Master of Engineering in (CSE), G.H. Raisoni college of Engineering and Technology,
-2Assistant professor Department of (CSE), G.H. Raisoni College of Engineering and Technology,
-Amravati, India
-Amravati, India"
 c43490eb0a3ce18fb2326ef1d0828664b60e73e2,Is This Car Looking at You? How Anthropomorphism Predicts Fusiform Face Area Activation when Seeing Cars,"RESEARCH ARTICLE
 Is This Car Looking at You? How
 Anthropomorphism Predicts Fusiform Face
@@ -40146,26 +34193,6 @@ Department of Communications and Information Engineering, University of Murcia,
 (J.C.-J.); (M.V.-V.); (A.F.S.)
 * Correspondence: Tel.: +34-868-884-644
 Received: 30 June 2017; Accepted: 21 August 2017; Published: 24 August 2017"
-c46bcb02f92612cf525fd84c6cc79b0638c2eac9,New Fuzzy LBP Features for Face Recognition,"New Fuzzy LBP Features for Face Recognition
-Abdullah Gubbia, Mohammed Fazle Azeemb Zahid Ansaric
-Department of Electronics and Communications, P.A. College of Engineering, Mangalore, India,
-Contact:
-Department of Electrical Engineering, Aligarh Muslim University, Aligarh, India,
-Department of Computer Science, P.A. College of Engineering, Mangalore, India,
-zahid
-Contact:
-Contact:
-There are many Local texture features each very in way they implement and each of the Algorithm trying
-improve the performance. An attempt is made in this paper to represent a theoretically very simple and com-
-putationally effective approach for face recognition. In our implementation the face image is divided into 3x3
-sub-regions from which the features are extracted using the Local Binary Pattern (LBP) over a window, fuzzy
-membership function and at the central pixel. The LBP features possess the texture discriminative property
-nd their computational cost is very low. By utilising the information from LBP, membership function, and
-entral pixel, the limitations of traditional LBP is eliminated. The bench mark database like ORL and Shef‌f‌ield
-Databases are used for the evaluation of proposed features with SVM classiﬁer. For the proposed approach K-fold
-nd ROC curves are obtained and results are compared.
-Keywords : Face Recognition, Fuzzy Logic, Information Set, Local Binary Pattern, SVM.
-. INTRODUCTION"
 c48c452f26e54f37faaf025ca3c76b33ce3e40f6,Incremental learning of latent structural SVM for weakly supervised image classification,"INCREMENTAL LEARNING OF LATENT STRUCTURAL SVM FOR WEAKLY SUPERVISED
 IMAGE CLASSIFICATION
 Thibaut Durand (1)
@@ -40278,19 +34305,10 @@ DEIR, University of Sassari, via Torre Tonda 34, 07100 Sassari, Italy
 Phone +39 079 2017321
 DAP, University of Sassari, piazza Duomo 6, 07041 Alghero (SS), Italy"
 8e112ad656ff90720ae609841bd0fcb2caa90d65,"""Show Me the Cup"": Reference with Continuous Representations",[cs.CL]  28 Jun 2016
-8edcd935362c899e630349784e4ff8adb3a69cdc,Person re-identification using deformable patch metric learning,"Person Re-identiﬁcation using Deformable Patch Metric Learning
-Sławomir B ˛ak
-Peter Carr
-Disney Research
-Pittsburgh, PA, USA, 15213"
 8eabd39cf43596e56f377aa26f985ef20f0aeb4e,On the Recent Use of Local Binary Patterns for Face Authentication,"INTERNATIONAL JOURNAL OF IMAGE AND VIDEO PROCESSING, SPECIAL ISSUE ON FACIAL IMAGE PROCESSING
 On the Recent Use of Local Binary Patterns for
 Face Authentication
 S´ebastien Marcel, Yann Rodriguez and Guillaume Heusch"
-8ea56e4697430d1dbc728bad5a6e8ebafcced835,Adaptive stochastic gradient descent on the Grassmannian for robust low-rank subspace recovery,"Adaptive Stochastic Gradient Descent on the
-Grassmannian for Robust Low-Rank Subspace
-Recovery
-Jun He, Member, IEEE, Yue Zhang, Student Member, IEEE"
 8e33183a0ed7141aa4fa9d87ef3be334727c76c0,Robustness of Face Recognition to Image Manipulations,"– COS429 Written Report, Fall 2017 –
 Robustness of Face Recognition to Image Manipulations
 Cathy Chen (cc27), Zachary Liu (zsliu), and Lindy Zeng (lindy)
@@ -40363,13 +34381,6 @@ during learning process; (2) keeping learning new knowledge"
 Turkish Journal of Psychiatry
 Neuroimaging Findings in Auti sm: A Brief Review
 Halime Tuna ULAY1, Aygün ERTUĞRUL2"
-8e461978359b056d1b4770508e7a567dbed49776,LOMo: Latent Ordinal Model for Facial Analysis in Videos,"LOMo: Latent Ordinal Model for Facial Analysis in Videos
-Karan Sikka1,∗
-Gaurav Sharma2,3,†
-Marian Bartlett1,∗,‡
-UCSD, USA
-MPI for Informatics, Germany
-IIT Kanpur, India"
 8e9ff8224753b22e3b1f8bbe271382d6fdb8ddfa,Scale optimization for full-image-CNN vehicle detection,"Scale Optimization for Full-Image-CNN Vehicle Detection
 Yang Gao, Shouyan Guo, Kaimin Huang, Jiaxin Chen, Qian Gong, Yang Zou, Tong Bai and Gary Overetta"
 8e6526b46a52a18028336a8d026e9d466aa12edf,Moving Poselets: A Discriminative and Interpretable Skeletal Motion Representation for Action Recognition,"Moving Poselets: A Discriminative and Interpretable Skeletal Motion
@@ -40568,13 +34579,6 @@ synchrony, alliance, fighting capacity
 Author for correspondence:
 Daniel M. T. Fessler
 e-mail:"
-8e64f7f38db57ddc197cc7a9c51b914920ee99cc,AN OPTIMIZED FRAMEWORK FOR DETECTION AND TRACKING,"The International Journal of Multimedia & Its Applications (IJMA) Vol.6, No.4, August 2014
-AN OPTIMIZED FRAMEWORK FOR DETECTION
-AND TRACKING OF VIDEO OBJECTS IN
-CHALLENGING BACKGROUNDS
-Sukanyathara J1 and Alphonsa Kuriakose2
-Department of Computer Science & Engineering,
-Viswajyothi College of Engineering & Technology, MG University, Kerala, India"
 8e6adaf03ac84acc16e428869b66a5a1e94ed753,Privacy-preserving classifiers recognize shared mobility behaviours from WiFi network imperfect data,"Privacy-preserving classiﬁers recognize shared
 mobility behaviours from WiFi network imperfect
 Orestes Manzanilla-Salazar∗ and Brunilde Sansò†
@@ -40799,22 +34803,9 @@ Institute of Psychology, Faculty of Social Sciences, Erasmus University Rotterda
 Netherlands
 School of Social and Behavioral Sciences, Tilburg University, The Netherlands
 Sensation, Perception and Behaviour, Unilever R&D Vlaardingen, The Netherlands"
-a1b1442198f29072e907ed8cb02a064493737158,Crowdsourcing Facial Responses to Online Videos,"Crowdsourcing Facial Responses
-to Online Videos
-Daniel McDuff, Student Member, IEEE, Rana El Kaliouby, Member, IEEE, and
-Rosalind W. Picard, Fellow, IEEE"
 a139c62c27a884cf447ad020cb7b154e63477681,A Data-driven Model for Interaction-Aware Pedestrian Motion Prediction in Object Cluttered Environments,"A Data-driven Model for Interaction-aware Pedestrian Motion Prediction in
 Object Cluttered Environments
 Mark Pfeiffer, Giuseppe Paolo, Hannes Sommer, Juan Nieto, Roland Siegwart, and Cesar Cadena"
-a1e97c4043d5cc9896dc60ae7ca135782d89e5fc,"Re-identification of Humans in Crowds using Personal, Social and Environmental Constraints","IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
-Re-identiﬁcation of Humans in Crowds using
-Personal, Social and Environmental Constraints
-Shayan Modiri Assari, Member, IEEE, Haroon Idrees, Member, IEEE, and Mubarak Shah, Fellow, IEEE"
-a175f20189f028a1420b76ae42f6dfe99d8d6847,Where and Why Are They Looking ? Jointly Inferring Human Attention and Intentions in Complex Tasks,"Where and Why Are They Looking? Jointly Inferring Human Attention and
-Intentions in Complex Tasks
-Ping Wei1,2, Yang Liu2, Tianmin Shu2, Nanning Zheng1, and Song-Chun Zhu2
-School of Electronic and Information Engineering, Xi’an Jiaotong University, China
-Center for Vision, Cognition, Learning, and Autonomy, University of California, Los Angeles"
 a133374b9630bbe6eb2b7de8c3204aa57e75c582,A Deep Network Solution for Attention and Aesthetics Aware Photo Cropping.,"A Deep Network Solution for Attention and
 Aesthetics Aware Photo Cropping
 Wenguan Wang, Jianbing Shen, Senior Member, IEEE, and Haibin Ling"
@@ -40938,9 +34929,6 @@ d1a0425f764ce8847d20d278e4a4267c8258c4dc,3D Human Pose Estimation with Siamese E
 Embedding
 M´arton V´egesa,∗, Viktor Vargaa, Andr´as L˝orincza
 E¨otv¨os Lor´and University, Budapest, Hungary"
-d1bfb6a9182e5712d8aef46b2fe93ef4ad4fe705,Local Color Contrastive Descriptor for Image Classification,"Local Color Contrastive Descriptor for Image
-Classiﬁcation
-Sheng Guo, Student Member, IEEE, Weilin Huang, Member, IEEE, and Yu Qiao, Senior Member, IEEE"
 d170adb2c508edaedb731ada8cb995172a839a1f,Cascade of Boolean detector combinations,"Mahkonen et al. EURASIP Journal on Image and Video
 Processing  (2018) 2018:61
 https://doi.org/10.1186/s13640-018-0303-9
@@ -41006,12 +34994,6 @@ Thomas Kemp
 Sony Europe Ltd.†
 Akira Nakamura
 Sony Corporation‡"
-d12c343e60f9cc1a0c6c94c138f38e6bffe22001,Diverse Sampling for Self-Supervised Learning of Semantic Segmentation,"Diverse Sampling for Self-Supervised Learning of Semantic Segmentation
-Mohammadreza Mostajabi ∗
-Nicholas Kolkin ∗
-Toyota Technological Institute at Chicago
-{mostajabi, nick.kolkin,
-Gregory Shakhnarovich"
 d1c103c63d930d3ae7397618f486117a48e35f16,Does gaze direction modulate facial expression processing in children with autism spectrum disorder?,"BIROn - Birkbeck Institutional Research Online
 Enabling open access to Birkbeck’s published research output
 Does gaze direction modulate facial expression
@@ -41032,21 +35014,10 @@ Does gaze direction modulate facial expression processing in children
 with autism spectrum disorder?
 Deposit Guide
 Contact:"
-d1dd0c714950cbd89f76ec6b039201eadf74cade,Person Re-identification Using Robust Brightness Transfer Functions Based on Multiple Detections,"Person Re-identiﬁcation Using Robust
-Brightness Transfer Functions Based
-on Multiple Detections
-Amran Bhuiyan(B), Behzad Mirmahboub, Alessandro Perina,
-nd Vittorio Murino
-Pattern Analysis and Computer Vision (PAVIS),
-Istituto Italiano di Tecnologia, Genova, Italy"
 d1e66107eb084ea0ef5a97f3363f8787b8df91ed,Max-Margin Regularization for Reducing Accidentalness in Chamfer Matching,"Max-margin Regularization for Reducing
 Accidentalness in Chamfer Matching
 Angela Eigenstetter*, Pradeep Yarlagadda* and Bj¨orn Ommer
 Interdisciplinary Center for Scientiﬁc Computing, University of Heidelberg, Germany"
-d138270d3c06e85fa2c3da6f953818da4b72313a,An Analytical Framework for Estimating Scale-Out and Scale-Up Power Efficiency of Heterogeneous Manycores,"An Analytical Framework for Estimating
-Scale-Out and Scale-Up Power Efﬁciency
-of Heterogeneous Manycores
-Jun Ma, Guihai Yan, Member, IEEE, Yinhe Han, Member, IEEE, and Xiaowei Li, Senior Member, IEEE"
 d1295a93346411bb833305acc0e092c9e3b2eff1,The eMPaThy iMBalance hyPoThesis oF aUTisM : a TheoReTical aPPRoach To cogniTiVe and eMoTional eMPaThy in aUTisTic deVeloPMenT,"the Psychological record, 2009, 59, 489-510
 The eMPaThy iMBalance hyPoThesis oF aUTisM:
 TheoReTical aPPRoach To cogniTiVe and
@@ -41106,11 +35077,6 @@ Univ Lille Nord de France, 59000 Lille, France
 IFSTTAR, COSYS, LEOST, 59650 Villeneuve d’Ascq, France
 Normandie Univ., UNICAEN, ENSICAEN, GREYC UMR CNRS 6072,
 Caen, France"
-d1503151b39038a87acbd9ecce073ddc211a597d,Efficient Semantic Segmentation using Gradual Grouping,"Efﬁcient Semantic Segmentation using Gradual Grouping
-Nikitha Vallurupalli1, Sriharsha Annamaneni1, Girish Varma1,
-C V Jawahar1, Manu Mathew2, Soyeb Nagori2
-Center for Visual Information Technology, Kohli Center on Intelligent Systems, IIIT-Hyderabad, India
-Texas Instruments, Bangalore, India"
 d1dfdc107fa5f2c4820570e369cda10ab1661b87,Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation,"Super SloMo: High Quality Estimation of Multiple Intermediate Frames
 for Video Interpolation
 Huaizu Jiang1
@@ -41140,10 +35106,6 @@ Yu-Siang Wang1, Chenxi Liu2, Xiaohui Zeng3, Alan Yuille2
 : National Taiwan University
 : Johns Hopkins University
 : Hong Kong University of Science and Technology"
-d168c2bd29fcad2083586430dd76f54da69bc8a6,Person Re-Identification by Iterative Re-Weighted Sparse Ranking,"Person Re-Identiﬁcation by Iterative
-Re-Weighted Sparse Ranking
-Giuseppe Lisanti, Iacopo Masi, Andrew D. Bagdanov, Member, IEEE, and
-Alberto Del Bimbo, Member, IEEE"
 d1c0592f4f9f0ff2e14e0591d87539e5141b7361,Mobile Emotion Recognition Engine,"Mobile Emotion Recognition Engine
 Alberto Scicali1"
 d122d66c51606a8157a461b9d7eb8b6af3d819b0,AUTOMATED RECOGNITION OF FACIAL EXPRESSIONS,"Vol-3 Issue-4 2017
@@ -41179,17 +35141,6 @@ Audi Electronics Venture GmbH, Germany
 d1d6f1d64a04af9c2e1bdd74e72bd3ffac329576,Neural Face Editing with Intrinsic Image Disentangling,"Neural Face Editing with Intrinsic Image Disentangling
 Zhixin Shu1 Ersin Yumer2 Sunil Hadap2 Kalyan Sunkavalli2 Eli Shechtman 2 Dimitris Samaras1,3
 Stony Brook University 2Adobe Research 3 CentraleSup´elec, Universit´e Paris-Saclay"
-6f7de9849be93eff1c5f133defd9d70e5ff437ac,AttentionNet: Aggregating Weak Directions for Accurate Object Detection,"AttentionNet: Aggregating Weak Directions for Accurate Object Detection
-Donggeun Yoo
-Sunggyun Park
-KAIST
-KAIST
-Joon-Young Lee∗
-KAIST
-Anthony S. Paek
-Lunit Inc.
-In So Kweon
-KAIST"
 6f3391fda6b25796b5e051f822f91243f69276cb,Performance Comparison of Various Face Detection Techniques,"International Journal of Scientific Research Engineering & Technology (IJSRET)
 Volume 2 Issue1   pp 019-0027 April 2013
 ISSN 2278 - 0882
@@ -41232,17 +35183,6 @@ is showed. The biometric pattern of the system is a set of feature points repres
 pattern extraction and matching is described. Also, a deep analysis of similarity metrics performance is presented for the biometric
 system. A database with samples of retina images from users on different moments of time is used, thus simulating a hard and real
 environment of veriﬁcation. Even in this scenario, the system allows to establish a wide conﬁdence band for the metric threshold"
-6fe149e588a5bf15bf89edfedb1a29cc31384ddc,Fully Convolutional Networks for Automated Segmentation of Abdominal Adipose Tissue Depots in Multicenter Water-Fat MRI,"Fully Convolutional Networks for Automated Segmentation
-of Abdominal Adipose Tissue Depots in Multicenter
-Water-Fat MRI
-Taro Langner1*, Anders Hedstr¨om2, Katharina Paulmichl3,4, Daniel Weghuber3,4,
-Anders Forslund5, Peter Bergsten5,6, H˚akan Ahlstr¨om1,2, Joel Kullberg1,2
-Dept. of Radiology, Uppsala University, Uppsala, Sweden
-Antaros Medical, BioVenture Hub, M¨olndal, Sweden
-Dept. of Pediatrics, Paracelsus Medical University, 5020 Salzburg, Austria
-Obesity Research Unit, Paracelsus Medical University, 5020 Salzburg, Austria
-5Dept. of Women’s and Children’s Health, Uppsala University, Uppsala, SE 751 05, Sweden
-6Dept. of Medical Cell Biology, Uppsala University, Uppsala, SE 751 23, Sweden"
 6f9873e2a7bc279c4f0a45c1a6e831ef3ba78ae7,Improving GAN Training via Binarized Representation Entropy (BRE) Regularization,"Published as a conference paper at ICLR 2018
 IMPROVING GAN TRAINING VIA
 BINARIZED REPRESENTATION ENTROPY (BRE)
@@ -41259,36 +35199,11 @@ Facial Recognition Utilizing Patch Based Game Theory
 Foysal Ahmad, Kaushik Roy, Brian O‟Connor, Joseph Shelton, Pablo Arias, Albert Esterline, and Gerry
 Dozier
 theory.  Texture  based"
-6fc8c988dd841c6c4f5e96b1b1458b6aa564b2de,Crowd Counting via Scale-Adaptive Convolutional Neural Network,"Crowd counting via scale-adaptive convolutional neural network
-Lu Zhang∗†
-Tencent Youtu
-Miaojing Shi∗
-Qiaobo Chen†
-Inria Rennes & Tencent Youtu
-Shanghai Jiaotong University"
-6f2bc1a4fbe3e00881b56c145a568264bd3c76f1,Spectral Regression dimension reduction for multiple features facial image retrieval,"Int. J. Biometrics, Vol. 4, No. 1, 2012
-Spectral Regression dimension reduction for
-multiple features facial image retrieval
-Bailing Zhang*
-Department of Computer Science
-nd Software Engineering,
-Xi’an Jiaotong-Liverpool University,
-Suzhou 215123, China
-E-mail:
-*Corresponding author
-Yongsheng Gao
-School of Engineering,
-Grifﬁth University,
-QLD 4111, Australia
-E-mail:"
 6f1be86c77492af422e936028858c9180b52b698,Indoor Scene Understanding in 2.5/3D: A Survey,"JOURNAL OF LATEX CLASS FILES, VOL. 6, NO. 1, JULY 2015
 Indoor Scene Understanding in 2.5/3D: A Survey
 Muzammal Naseer, Salman H Khan, Fatih Porikli"
 6f7ce89aa3e01045fcd7f1c1635af7a09811a1fe,A novel rank order LoG filter for interest point detection,"978-1-4673-0046-9/12/$26.00 ©2012 IEEE
 ICASSP 2012"
-6f53466b17a2f9da4dbd1d870e822a1f8e837044,Image Aesthetic Assessment: An experimental survey,"Image Aesthetic Assessment:
-An Experimental Survey
-Yubin Deng, Chen Change Loy, Member, IEEE, and Xiaoou Tang, Fellow, IEEE"
 6f5151c7446552fd6a611bf6263f14e729805ec7,Facial Action Unit Recognition Using Filtered Local Binary Pattern Features with Bootstrapped and Weighted ECOC Classifiers,".=?E= )?JE 7EJ 4A?CEJE KIEC
 ?= *E=HO 2=JJAH .A=JKHAI MEJD
 -++ +=IIEAHI
@@ -41358,10 +35273,6 @@ Institut f¨ur Neuroinformatik, Ruhr-Universit¨at Bochum,44780 Bochum, Germany"
 An Experimental and Reproducible Research
 Survey
 Manuel G¨unther and Laurent El Shafey and S´ebastien Marcel"
-6f288a12033fa895fb0e9ec3219f3115904f24de,Learning Expressionlets via Universal Manifold Model for Dynamic Facial Expression Recognition,"Learning Expressionlets via Universal Manifold
-Model for Dynamic Facial Expression Recognition
-Mengyi Liu, Student Member, IEEE, Shiguang Shan, Senior Member, IEEE, Ruiping Wang, Member, IEEE,
-Xilin Chen, Senior Member, IEEE"
 6f77ff9990973a6cdad6b5b6022323bff9d03965,Action Recognition in Still Images Using Word Embeddings from Natural Language Descriptions,"017 IEEE Winter Conference on Applications of Computer Vision Workshops
 Action Recognition in Still Images Using Word Embeddings from Natural
 Language Descriptions
@@ -41388,9 +35299,6 @@ University of Fribourg, Switzerland
 Two-Branch Deep Convolutional Neural Network
 Architecture
 Erfan Zangeneh, Mohammad Rahmati, and Yalda Mohsenzadeh"
-6f41b528abc34c249038f612a6c1033790ace628,Discriminant Subspace Analysis: An Adaptive Approach for Image Classification,"Discriminant Subspace Analysis: An Adaptive
-Approach for Image Classiﬁcation
-Yijuan Lu, Member, IEEE, and Qi Tian, Senior Member, IEEE"
 6f1a784ebb8df0689361afe26a2e5f7a1f4c66ca,A unified probabilistic framework for measuring the intensity of spontaneous facial action units,"A Uniﬁed Probabilistic Framework For Measuring The Intensity of
 Spontaneous Facial Action Units
 Yongqiang Li1, S. Mohammad Mavadati2, Mohammad H. Mahoor and Qiang Ji
@@ -41406,14 +35314,6 @@ Sunnyvale, CA 94089, USA
 LUO ET AL.: ORINET: A FULLY CONVOLUTIONAL NETWORK FOR 3D HUMAN POSE
 OriNet: A Fully Convolutional Network for 3D
 Human Pose Estimation"
-6fa39c0221c8bcae9146d31646cd9f70aba7190c,Review on Histopathological Slide Analysis using Digital Microscopy,"International Journal of Advanced Science and Technology
-Vol.62, (2014), pp.65-96
-http://dx.doi.org/10.14257/ijast.2014.62.06
-Review on Histopathological Slide Analysis using Digital Microscopy
-Sangita Bhattacharjee1, Jashojit Mukherjee1, Sanjay Nag1, Indra Kanta Maitra2 and
-Samir K. Bandyopadhyay1
-Department of Computer Science and Engineering, University of Calcutta, India
-B. P. Poddar Institute of Management and Technology, Kolkata, India"
 6f08885b980049be95a991f6213ee49bbf05c48d,Author ' s personal copy Multi-Kernel Appearance Model ☆,"This article appeared in a journal published by Elsevier. The attached
 opy is furnished to the author for internal non-commercial research
 nd education use, including for instruction at the authors institution
@@ -41531,9 +35431,6 @@ uma complexidade computacional maior que os demais m´etodos,
 podemos utiliz´a-lo em aplicac¸ ˜oes off-line.
 Palavras-Chave— Reconhecimento de Padr˜oes, landmarks faci-
 is, M´aquina de Vetor Suporte."
-486a82f50835ea888fbc5c6babf3cf8e8b9807bc,Face Search at Scale: 80 Million Gallery,"MSU TECHNICAL REPORT MSU-CSE-15-11, JULY 24, 2015
-Face Search at Scale: 80 Million Gallery
-Dayong Wang, Member, IEEE, Charles Otto, Student Member, IEEE, Anil K. Jain, Fellow, IEEE"
 48ac5466c5d0c90fa2c6c38c51c22627f966d687,Real Time People Detection Combining Appearance and Depth Image Spaces Using Boosted Random Ferns,"Real Time People Detection Combining
 Appearance and Depth Image Spaces using
 Boosted Random Ferns
@@ -41568,36 +35465,6 @@ France"
 489decd84645b77d31001d17a66abb92bb96c731,Learning View-Specific Deep Networks for Person Re-Identification,"Learning View-Speciﬁc Deep Networks for Person
 Re-Identiﬁcation
 Zhanxiang Feng, Jianhuang Lai, and Xiaohua Xie"
-48a442646483d9777a2c5864a8e5f6d1a4851396,Kickstarting the Commons: The YFCC100M and the YLI Corpora,"Kickstarting the Commons:
-The YFCC100M and the YLI Corpora
-Julia Bernd1, Damian Borth2, Carmen Carrano3, Jaeyoung Choi1, Benjamin Elizalde1,
-Gerald Friedland1, Luke Gottlieb1, Karl Ni3, Roger Pearce3, Doug Poland3, Khalid Ashraf4,
-David A. Shamma5, and Bart Thomee5
-International Computer Science Institute, Berkeley, CA, USA
-German Research Center for Artiﬁcial Intelligence (DFKI), Kaiserslautern, Germany
-Lawrence Livermore National Laboratory, Livermore, CA, USA
-University of California–Berkeley, CA, USA
-5 Yahoo Labs, San Francisco, CA, USA"
-4839f861709e6ae6d4d032228473ce1764acbdcc,Finding Egocentric Image Topics through Convolutional Neural Network Based Representations,"Finding Egocentric Image Topics through Convolutional Neural Network Based Representations
-Kai Zhen, David Crandall
-School of Informatics and Computing, Indiana University.
-Life-logging cameras create huge collections of photos, even for a single
-person on a single day [1, 6], which makes it difﬁcult for users to browse
-or organize their photos effectively. Unlike text corpora in which words
-reate intermediate representations that carry semantic meaning for higher-
-level concepts such as topics, images have no such obvious intermediate
-representation to connect raw pixels and semantics. Egocentric photos are
-particularly challenging because they were taken opportunistically, so they
-re often blurry and poorly-composed compared to consumer-style images.
-This paper applies topic modeling on deep features to extract visual
-“concept clusters” from egocentric datasets. We discretize features to form
-better analogy to the word-document model, which we ﬁnd yields faster
-onvergence during inference. We also ﬁnd that removing frequent, less in-
-formative features helps to prevent outliers and improve the semantic mean-
-ing of extracted topics, analogous to removing stop words in the text mining
-domain. In a generative process similar to that proposed in LDA [2], we
-model an image as being generated by ﬁrst choosing topics, and then sam-
-pling features (visual words) from selected topics,"
 48b38d157272f03f6b44c0df61130534d11d8569,Natural Language Guided Visual Relationship Detection,"oard)(person-behind-kid)(skate board-on-street)(person-sit on-street)...ImageVisual relationshipsFigure1:Visualrelationshipsrepresenttheinteractionsbe-tweenobservedobjects.Eachrelationshiphasthreeele-ments:subject,predicateandobject.HereisanexampleimagefromVisualGenome[17].Ourproposedmethodisabletoeffectivelydetectnumerouskindsofdifferentrela-tionshipsfromsuchimage.objectsinimages.Therelationshipscanberepresentedinatripletformofhsubject-predicate-objecti,e.g.,hkid-on-skateboardi,asshowninFig.1.Anaturalapproachforthistaskistotreatitasaclassiﬁcationproblem:eachkindofrelationships/phraseisarelationcategory[32],asshowninFig.2.Totrainsuchreliableandrobustmodel,sufﬁ-cienttrainingsamplesforeachpossiblehsubject-predicate-objecticombinationareessential.ConsidertheVisualRe-lationshipDataset(VRD)[24],withN=100objectcate-goriesandK=70predicates,thenthereareN2K=700kcombinationsintotal.However,itcontainsonly38kre-lationships,whichmeansthateachcombinationhaslessthan1sampleonaverage.Thepreviousclassiﬁcation-basedworkscanonlydetectthemostcommonrelationships,e.g.,[32]studiedonly13frequentrelationships.Anotherpopularstrategyistodetecttherelationshippredicatesandtheobjectcategoriesindependently.Al-thoughthenumberofcategoriesdecreasesdramatically,thesemanticrelationshipbetweentheobjectsandthepredi-catesareignored.Consequently,thephrasewhichhasthesamepredicatebutdifferentagentsisconsideredasthesametypeofrelationship.Forinstance,the”clock-on-1"
 483f85e1ebef9d10a951b3c01751892aca92a2c2,Adaptive Classification for Person Re-identification Driven by Change Detection,"Adaptive Classiﬁcation for Person Re-Identiﬁcation Driven by Change
 Detection
@@ -41644,12 +35511,6 @@ optimization problem to solve (i.e., the objective function f ). Here, we introd
 of “regularization,” with the goal of avoiding overﬁtting the function learned to the data set
 t hand, even for very high-dimensional data.
 Recap"
-488e475eeb3bb39a145f23ede197cd3620f1d98a,Pedestrian Attribute Classification in Surveillance: Database and Evaluation,"Pedestrian Attribute Classiﬁcation in Surveillance: Database and Evaluation
-Jianqing Zhu, Shengcai Liao, Zhen Lei, Dong Yi, Stan Z. Li∗
-Center for Biometrics and Security Research & National Laboratory of Pattern Recognition
-Institute of Automation, Chinese Academy of Sciences (CASIA)
-95 Zhongguancun East Road, 100190, Beijing, China
-{jqzhu, scliao, zlei, dyi,"
 48d299fe3303c80f840816fc76971a42b4a8b624,Predicting Important Objects for Egocentric Video Summarization,"http://dx.doi.org/10.1007/s11263-014-0794-5
 Predicting Important Objects for Egocentric Video Summarization
 Yong Jae Lee · Kristen Grauman
@@ -41666,26 +35527,10 @@ Xiao Lin
 Virginia Tech
 Devi Parikh
 Georgia Tech"
-482769e4c4cf832128b52f1bdff873af1eee8ba8,Robust Face Detection using Fusion of Haar and Daubechies Orthogonal Wavelet Template,"International Journal of Computer Applications (0975 – 8887)
-Volume 46– No.6, May 2012
-Robust Face Detection using Fusion of Haar and
-Daubechies Orthogonal Wavelet Template
-Chirag I Patel
-Sanjay Garg
-Research scholar, Institute of Technology,
-Professor, Institute of Technology,
-Nirma University, Ahmedabad, Gujarat, India
-Nirma University, Ahmedabad, Gujarat, India"
 485e0d178bafa959ac956aa8de6556a2439c6663,Learning from Examples to Generalize over Pose and Illumination,"Learning from Examples to Generalize over Pose
 nd Illumination
 Marco K. M¨uller and Rolf P. W¨urtz
 Institute f¨ur Neural Computation, Ruhr-University, 44780 Bochum, Germany"
-48bf7357723abf7770400d68f914d6a7ca5a1a5f,Real-Time Head Pose Tracking with Online Face Template Reconstruction,"Real-Time Head Pose Tracking with Online
-Face Template Reconstruction
-Songnan Li, Member, IEEE,
-King Ngi Ngan, Fellow, IEEE,
-Raveendran Paramesran, Senior Member, IEEE,
-nd Lu Sheng"
 48499deeaa1e31ac22c901d115b8b9867f89f952,Interim Report of Final Year Project HKU-Face : A Large Scale Dataset for Deep Face Recognition,"Interim Report of Final Year Project
 HKU-Face: A Large Scale Dataset for
 Deep Face Recognition
@@ -41718,10 +35563,6 @@ Anonymous Author(s)
 Afﬁliation
 Address
 email"
-486e5c2996726ec0f7c37077a2752dc4bd8c1413,Linearized Smooth Additive Classifiers,"Linearized Smooth Additive Classiﬁers
-Subhransu Maji
-Toyota Technological Institute at Chicago,
-Chicago, IL 60637, USA"
 484c2617471fd742c4806f9281e5add45c6831a7,LSTM Self-Supervision for Detailed Behavior Analysis,"LSTM Self-Supervision for Detailed Behavior Analysis
 Biagio Brattoli1∗, Uta B¨uchler1∗, Anna-Sophia Wahl2, Martin E. Schwab2, Bj¨orn Ommer1
 HCI / IWR, Heidelberg University, Germany
@@ -41755,26 +35596,6 @@ Conversations in Typically Developed Adults
 Masashi Suda, Yuichi Takei, Yoshiyuki Aoyama, Kosuke Narita, Noriko Sakurai, Masato Fukuda*,
 Masahiko Mikuni
 Department of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Gunma, Japan"
-48319e611f0daaa758ed5dcf5a6496b4c6ef45f2,Non Binary Local Gradient Contours for Face Recognition,"Non Binary Local Gradient Contours for Face Recognition
-Abdullah Gubbia, Mohammad Fazle Azeemb, M Sharmila Kumaric
-Department of Electronics and Communication, P.A. College of Engnineering, Mangalore,
-Nadupadavu, Mangalore, India, Contact:
-Senior IEEE Member, Department of Electrical and Electronics Engineering, Aligarh Muslim
-University, India, Contact:
-Department of Computer Science and Engineering, P A College of Engineering, Nadupadavu,
-Mangalore, India. Contact:
-As the features from the traditional Local Binary patterns (LBP) and Local Directional Patterns (LDP) are
-found to be ineffective for face recognition, we have proposed a new approach derived on the basis of Information
-sets whereby the loss of information that occurs during the binarization is eliminated. The information sets
-s a product. Since face is having smooth texture in a limited area, the extracted features must be highly
-discernible. To limit the number of features, we consider only the non overlapping windows. By the application
-of the information set theory we can reduce the number of feature of an image. The derived features are shown
-to work fairly well over eigenface, ﬁsherface and LBP methods.
-Keywords: Local Binary Pattern, Local Directional Pattern, Information Sets, Gradient Contour, Support
-Vector Machine, KNN, Face Recognition.
-. INTRODUCTION
-In face recognition, the major issue to be ad-
-dressed is the extraction of features which are"
 48bc87ccc6b6e2d318f91d5f1886432806fec553,Multiaccuracy: Black-Box Post-Processing for Fairness in Classification,"Multiaccuracy: Black-Box Post-Processing for Fairness in
 Michael P. Kim∗†
 Classiﬁcation
@@ -41840,18 +35661,6 @@ l’Exposici(cid:19)o, 59-69, 08800 Vilanova i la Geltru, Spain
 Dept. Mathematics, Universitat de Barcelona, Gran Via de les Corts Catalanes
 Computer Vision Center, Campus UAB, Edi(cid:12)ci 0, 08193, Bellaterra, Spain
 585, 08007, Barcelona, Spain"
-f496235629c02c98ad83b37d3d054ccfd0de0131,Learning Cross-Modal Deep Embeddings for Multi-Object Image Retrieval using Text and Sketch,"Learning Cross-Modal Deep Embeddings for
-Multi-Object Image Retrieval using Text and Sketch
-Sounak Dey, Anjan Dutta, Suman K. Ghosh, Ernest Valveny, Josep Llad´os
-Computer Vision Center, Computer Science Department
-Autonomous University of Barcelona
-Email: {sdey, adutta, sghosh, ernest,
-Barcelona, Spain
-Umapada Pal
-CVPR Unit
-Indian Statistical Institute
-Kolkata, India
-Email:"
 f4ce7c36586c27783a1b0e737c2834f39f9d029d,Advanced non linear dimensionality reduction methods for multidimensional time series : applications to human motion analysis,"Advanced Nonlinear
 Dimensionality Reduction
 Methods for Multidimensional
@@ -41898,17 +35707,6 @@ Optical-Flow Estimation in the Wild
 Nima Sedaghat
 University of Freiburg
 Germany"
-f4afc9ebafce950b81081e25efc2d8f5fb1f17e7,Tag-aware image classification via Nested Deep Belief nets,"TAG-AWARE IMAGE CLASSIFICATION VIA NESTED DEEP BELIEF NETS
-Zhaoquan Yuan1,2,  Jitao
-Sang1,2, Changsheng Xu1,2
-National Lab of Pattern Recognition,
-China-Singapore
-Institute
-of Automation,
-CAS, Beijing 100190, China
-Institute
-of Digital Media, Singapore
-{zqyuan, jtsang,"
 f43b60a33c585827bfa354d3d49fb148a1c26c3f,Identifying Well-formed Natural Language Questions,"Identifying Well-formed Natural Language Questions
 Manaal Faruqui Dipanjan Das
 Google AI Language"
@@ -41925,43 +35723,6 @@ Ludwig Schmidt
 Vaishaal Shankar
 UC Berkeley
 June 4, 2018"
-f44f13a8245bed66fff16a50d6ecc6d56151029d,Thermal-Infrared Pedestrian ROI Extraction through Thermal and Motion Information Fusion,"Sensors 2014, 14, 6666-6676; doi:10.3390/s140406666
-OPEN ACCESS
-sensors
-ISSN 1424-8220
-www.mdpi.com/journal/sensors
-Article
-Thermal-Infrared Pedestrian ROI Extraction through Thermal
-nd Motion Information Fusion
-Antonio Fernández-Caballero 1,2,*, María T. López 1,2 and Juan Serrano-Cuerda 2
-Departamento de Sistemas Informáticos, Universidad de Castilla-La Mancha, 02071-Albacete,
-Spain; E-Mail:
-Instituto de Investigación en Informática de Albacete, 02071-Albacete, Spain;
-E-Mail:
-*  Author to whom correspondence should be addressed; E-Mail:
-Tel.: +34-967-599-200; Fax: +34-967-599-224.
-Received: 14 March 2014; in revised form: 2 April 2014 / Accepted: 4 April 2014 /
-Published: 10 April 2014"
-f4b729d218139f1e93cc9d4df05fbf699d2e9d07,Introduction to the Special Issue on Recent Advances in Biometric Systems,"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 37, NO. 5, OCTOBER 2007
-Guest Editorial
-Introduction to the Special Issue on Recent
-Advances in Biometric Systems
-W E ARE pleased to present 14 papers in this special
-issue devoted to recent advances in biometric systems.
-A total of 78 papers were submitted for consideration for the
-special issue. Those that appear in this special issue result from
-careful review process and consideration of timing for the
-special issue. Other papers, which were originally submitted for
-onsideration for the special issue, may be undergoing major
-revisions and resubmission and appear at a later time in a
-regular issue of this journal or possibly in some other journal.
-In particular, several submissions in the area of iris biometrics
-ould not be considered for this special issue due to their
-experimental results being based primarily on the CASIA 1
-iris image dataset [1].
-Papers on a broad variety of topics were submitted to the
-special issue. The large active areas of biometrics such as face,
-ﬁngerprint, voice, signature, and iris were naturally well repre-"
 f4808e78bc648f9e1829c83a68a3e8ed4e7cf325,Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms,"Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms
 {tag}                                                 {/tag}
 International Journal of Computer Applications
@@ -41977,9 +35738,6 @@ f4b40b3dc27897fdc40f419a42d64fd1ff80cc9d,A Dual-Source Approach for 3D Human Pos
 A Dual-Source Approach for 3D Human Pose
 Estimation from a Single Image
 Umar Iqbal*, Andreas Doering*, Hashim Yasin, Björn Krüger, Andreas Weber, and Juergen Gall"
-f43463770d361e55fb6f6eb801a6e8530ab668cd,Corpus Construction and Semantic Analysis of Indonesian Image Description,"The 6th Intl. Workshop on Spoken Language Technologies for Under-Resourced Languages
-9-31 August 2018, Gurugram, India
-0.21437/SLTU.2018-9"
 f44af3b10a67fe62fd26eb82dd228a3cdeb980e1,"Understand, Compose and Respond - Answering Visual Questions by a Composition of Abstract Procedures","Understand, Compose and Respond
 Understand, Compose and Respond - Answering Visual"
 f49f1028052baa1588376a78a9dc64812748555e,Feature Fusion using Extended Jaccard Graph and Stochastic Gradient Descent for Robot,"JOURNAL OF LATEX CLASS FILES
@@ -42018,26 +35776,6 @@ Guest Editors: Christophe Garcia, Jörn Ostermann, and Tim Cootes"
 Classiﬁcation for Face Recognition with Insufﬁcient
 Labeled Samples
 Yuan Gao, Jiayi Ma, and Alan L. Yuille Fellow, IEEE"
-0a6c36de8726b6feaab586046ddc1d1a008f44f9,Filtered channel features for pedestrian detection,"Filtered Channel Features for Pedestrian Detection
-Shanshan Zhang, Rodrigo Benenson, Bernt Schiele
-MPI Informatics, Saarbrücken, Germany
-Figure 1: Integral channel feature detectors pool features via sums over rect-
-ngular regions. We can equivalently re-write this operation as convolution
-with a ﬁlter bank followed by single pixel reads. We aim to answer: What
-is the effect of selecting different ﬁlter banks?
-Pedestrian detection is an active research area, with 1000+ papers pub-
-lished in the last decade, and well established benchmark datasets. It is con-
-sidered a canonical case of object detection, and has served as playground
-to explore ideas that might be effective for generic object detection. Al-
-though many different ideas have been explored, and detection quality has
-een steadily improving [2], arguably it is still unclear how effective parts,
-omponents, and features learning are for this task.
-Current top performing pedestrian detection methods all point to an in-
-termediate layer (such as max-pooling or ﬁltering) between the low-level
-feature maps and the classiﬁcation layer [5, 6, 7]. In this paper we explore
-the simplest of such intermediary: a linear transformation implemented as
-onvolution with a ﬁlter bank. We propose a framework for ﬁltered chan-
-nel features (see ﬁgure 1) that uniﬁes multiple top performing methods"
 0a60e76e6983e1647469172a50907023913b0c9f,Longitudinal study of amygdala volume and joint attention in 2- to 4-year-old children with autism.,"ORIGINAL ARTICLE
 Longitudinal Study of Amygdala Volume and Joint
 Attention in 2- to 4-Year-Old Children With Autism
@@ -42058,31 +35796,7 @@ Participants: Fifty autistic and 33 control (11 devel-
 opmentally delayed, 22 typically developing) children be-
 tween 18 and 35 months (2 years) of age followed up at
 2 to 59 months (4 years) of age."
-0a60d9d62620e4f9bb3596ab7bb37afef0a90a4f,Chimpanzee Faces in the Wild: Log-Euclidean CNNs for Predicting Identities and Attributes of Primates,"Chimpanzee Faces in the Wild: Log-Euclidean CNNs for Predicting Identities and Attributes of Primates. GCPR 2016
-(cid:13) Copyright by Springer. The final publication will be available at link.springer.com
-A. Freytag, E. Rodner, M. Simon, A. Loos, H. K¨uhl and J. Denzler
-Chimpanzee Faces in the Wild:
-Log-Euclidean CNNs for Predicting Identities
-nd Attributes of Primates
-Alexander Freytag1,2, Erik Rodner1,2, Marcel Simon1, Alexander Loos3,
-Hjalmar S. K¨uhl4,5, and Joachim Denzler1,2,5
-Computer Vision Group, Friedrich Schiller University Jena, Germany
-Michael Stifel Center Jena, Germany
-Fraunhofer Institute for Digital Media Technology, Germany
-Max Planck Institute for Evolutionary Anthropology, Germany
-5German Centre for Integrative Biodiversity Research (iDiv), Germany"
 0a3051c8dde80975640d42dca21fac17ed60f987,A Hierarchical Switching Linear Dynamical System Applied to the Detection of Sepsis in Neonatal Condition Monitoring,
-0a4ba4d5bd6e07a31fa4586322fd5e07d9f9975e,Online Bayesian Nonparametrics for Group Detection,"ZANOTTO, BAZZANI, CRISTANI, MURINO: ONLINE BNP FOR GROUP DETECTION
-Online Bayesian Nonparametrics for Group
-Detection
-Matteo Zanotto
-Loris Bazzani
-Marco Cristani
-Vittorio Murino
-Pattern Analysis & Computer Vision
-Istituto Italiano di Tecnologia
-Via Morego 30 - 16163
-Genova, Italy"
 0a6a25ee84fc0bf7284f41eaa6fefaa58b5b329a,Neural Networks Regularization Through Representation Learning,"THÈSEPour obtenir le diplôme de doctorat Spécialité Informatique Préparée au sein de « l'INSA Rouen Normandie » Présentée et soutenue parSoufiane BELHARBIThèse dirigée par Sébastien ADAM, laboratoire LITIS Neural Networks Regularization Through Representation LearningThèse soutenue publiquement le 06 Juillet 2018 devant le jury composé deSébastien ADAMProfesseur à l'Université de Rouen NormandieDirecteur de thèseClément CHATELAINMaître de conférence à l'INSA  Rouen NormandieEncadrant de thèseRomain HÉRAULTMaître de conférence à l'INSA  Rouen NormandieEncadrant de thèseElisa FROMONTProfesseur à l'Université de Rennes 1Rapporteur de thèseThierry ARTIÈRESProfesseur à l'École Centrale MarseilleRapporteur de thèseJohn LEEProfesseur à l'Université Catholique de LouvainExaminateur de thèseDavid PICARDMaître de conférences à l'École Nationale Supérieure de l'Électronique et de ses ApplicationsExaminateur de thèseFrédéric JURIEProfesseur à l' Université de Caen NormandieInvité"
 0a1e3d271fefd506b3a601bd1c812a9842385829,Face Recognition Using 3D Directional Corner Points,"Face Recognition using 3D Directional Corner Points
 Author
@@ -42174,19 +35888,6 @@ A Review Paper on Face Recognition Techniques
 Sujata G. Bhele1 and V. H. Mankar2
 in  real
 interesting  area"
-0a391c4d7aafa73324549f212cf28640ed471a81,From Caregivers to Peers: Puberty Shapes Human Face Perception.,"663142 PSSXXX10.1177/0956797616663142Picci, ScherfPuberty Shapes Human Face Perception
-research-article2016
-Research Article
-From Caregivers to Peers: Puberty
-Shapes Human Face Perception
-Giorgia Picci and K. Suzanne Scherf
-Department of Psychology, Pennsylvania State University
-1 –13
-© The Author(s) 2016
-Reprints and permissions:
-sagepub.com/journalsPermissions.nav
-DOI: 10.1177/0956797616663142
-pss.sagepub.com"
 0a8ab703839ae585c2f27099616c40974cbeeda2,"Fast, Exact and Multi-Scale Inference for Semantic Image Segmentation with Deep Gaussian CRFs","Fast, Exact and Multi-Scale Inference for Semantic
 Image Segmentation with Deep Gaussian CRFs
 Siddhartha Chandra
@@ -42203,24 +35904,11 @@ Mauricio Villegas and Roberto Paredes
 Institut Tecnol`ogic d’Inform`atica
 Universitat Polit`ecnica de Val`encia
 Cam´ı de Vera s/n, 46022 Val`encia, Spain"
-0adb5923fb1955f7ca0a85454afe17e5d25425df,Crowd motion monitoring using tracklet-based commotion measure,"CROWD MOTION MONITORING USING TRACKLET-BASED COMMOTION MEASURE
-Hossein Mousavi*
-Moin Nabi* Hamed Kiani
-Alessandro Perina
-Vittorio Murino
-Pattern Analysis and Computer Vision Department (PAVIS)
-Istituto Italiano di Tecnologia
-Genova, Italy"
 0a40415bdfe4bc9ef7e019e4f1442a9fb61f58b2,Automatic Discovery and Geotagging of Objects from Street View Imagery,"Automatic Discovery and Geotagging of Objects from Street View Imagery
 Vladimir A. Krylov
 Eamonn Kenny
 Rozenn Dahyot
 ADAPT Centre, School of Computer Science and Statistics, Trinity College Dublin, Dublin, Ireland"
-0a2aca07c9e15de3d5924e156af9a8e1a67b4cab,Person Reidentification With Reference Descriptor,"Person Reidentiﬁcation With Reference Descriptor
-Le An, Member, IEEE, Mehran Kafai, Member, IEEE, Songfan Yang, Member, IEEE,
-nd Bir Bhanu, Fellow, IEEE
-cross
-identiﬁcation"
 0a6a173a1d1d36285bae97f98f4b901067d40097,Similarity learning on an explicit polynomial kernel feature map for person re-identification,"Similarity Learning on an Explicit Polynomial Kernel Feature Map for Person
 Re-Identiﬁcation
 Dapeng Chen y, Zejian Yuan y, Gang Huaz, Nanning Zhengy, Jingdong Wang x
@@ -42302,20 +35990,6 @@ for person re-identification in camera networks
 Zhong Zhang1,2* and Meiyan Huang1,2"
 0a8c6b40d6ca75bc1995083825e362137b130624,Nonparametric Method for Data-driven Image Captioning,"Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Short Papers), pages 592–598,
 Baltimore, Maryland, USA, June 23-25 2014. c(cid:13)2014 Association for Computational Linguistics"
-0a1138276c52c734b67b30de0bf3f76b0351f097,Discriminant Incoherent Component Analysis,"This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication.
-The final version of record is available at
-http://dx.doi.org/10.1109/TIP.2016.2539502
-Discriminant Incoherent Component Analysis
-Christos Georgakis, Student Member, IEEE, Yannis Panagakis, Member, IEEE, and Maja Pantic, Fellow, IEEE"
-0ab55cacf597b25ca649ded6ee5c05a76fb437bc,Quality-Based Multimodal Classification Using Tree-Structured Sparsity,"Quality-based Multimodal Classiﬁcation Using Tree-Structured Sparsity
-Soheil Bahrampour
-Asok Ray
-Pennsylvania State University
-Pennsylvania State University
-Nasser M. Nasrabadi
-Army Research Laboratory
-Kenneth W. Jenkins
-Pennsylvania State University"
 0a87d781fe2ae2e700237ddd00314dbc10b1429c,"Distribution Statement "" A "" ( Approved for public release , Distribution Unlimited ) Working Paper An Artificial Intelligence / Machine Learning Perspective on Social Simulation New Data and New Challenges","Distribution Statement A:  Approved for public release; distribution unlimited.
 Multi-scale HOG Prescreening Algorithm for Detection of Buried
 Explosive Hazards in FL-IR and FL-GPR Data
@@ -42341,16 +36015,6 @@ Department of Computer Science
 Federal university of Ouro Preto
 Ouro Preto, Brazil
 Email:"
-0af48a45e723f99b712a8ce97d7826002fe4d5a5,Toward Wide-Angle Microvision Sensors,"Toward Wide-Angle Microvision Sensors
-Sanjeev J. Koppal, Member, IEEE, Ioannis Gkioulekas, Student Member, IEEE,
-Travis Young, Member, IEEE, Hyunsung Park, Student Member, IEEE,
-Kenneth B. Crozier, Member, IEEE, Geoffrey L. Barrows, Member, IEEE, and
-Todd Zickler, Member, IEEE"
-0ad90ad5d2050ebaba5b5cddeb474c7d889bec3e,A Unified Semantic Embedding: Relating Taxonomies and Attributes,"A Uniﬁed Semantic Embedding:
-Relating Taxonomies and Attributes
-Sung Ju Hwang∗
-Disney Research
-Pittsburgh, PA"
 0a7a7b3f05918fb4fc33f04cb7e31232fa197f76,Fitting a Morphable Model to 3D Scans of Faces,"Fitting a Morphable Model to 3D Scans of Faces
 Volker Blanz
 Universit¤at Siegen,
@@ -42374,13 +36038,6 @@ Alp Guler1, Nikolaos Kardaris2, Siddhartha Chandra1, Vassilis Pitsikalis2, Chris
 Werner3, Klaus Hauer3, Costas Tzafestas2, Petros Maragos2, Iasonas Kokkinos1
 (1) INRIA GALEN & Centrale Sup´elec Paris,
 (2) National Technical University of Athens, (3) University of Heidelberg"
-0a058caa89d195930224148d3d2897c0c08fc668,Metric Embedding Autoencoders for Unsupervised Cross-Dataset Transfer Learning,"Metric Embedding Autoencoders for
-Unsupervised Cross-Dataset Transfer Learning
-Alexey Potapov1,3, Sergey Rodionov1,2, Hugo Latapie4, and Enzo Fenoglio4
-SingularityNET Foundation
-Novamente LLC
-ITMO University, St. Petersburg, Russia
-Chief Technology & Architecture Of‌f‌ice, Cisco"
 0a9d38f74095c6840540dabb00c754f4b0c2d131,Multimodal Language Analysis in the Wild: CMU-MOSEI Dataset and Interpretable Dynamic Fusion Graph,"Multimodal Language Analysis in the Wild:
 CMU-MOSEI Dataset and Interpretable Dynamic Fusion Graph
 Amir Zadeh1, Paul Pu Liang2, Jonathan Vanbriesen1, Soujanya Poria3,
@@ -42570,18 +36227,6 @@ This is the author’s personal copy of the final, accepted version of the paper
 the version published in Computer Graphics Form.
 Copyright © 2012 The Eurographics Association and Blackwell Publishing Ltd.
 Preprint"
-2643a611f10ce8acfef41e1e49d1be04d5d34190,Comparative Study of Diverse Face Recognition Approaches along with Intrinsic Worth and Recognition Rate,"International Journal of Computer Applications (0975 – 8887)
-Volume 179 – No.21, February 2018
-Comparative Study of Diverse Face Recognition
-Approaches along with Intrinsic Worth and Recognition
-Shivang Shukla
-Department of Computer Science
-Medi-Caps Institute of Science and Technology
-Indore, Madhya Pradesh, India
-Sourabh Dave
-Department of Information Technology
-Medi-Caps Inst. Of Science and Technology
-Indore, Madhya Pradesh, India"
 26a72e9dd444d2861298d9df9df9f7d147186bcd,Collecting and annotating the large continuous action dataset,"DOI 10.1007/s00138-016-0768-4
 ORIGINAL PAPER
 Collecting and annotating the large continuous action dataset
@@ -42681,26 +36326,6 @@ Keywords: Artificial intelligence; Machine learning; Convolutional neural networ
 264a84f4d27cd4bca94270620907cffcb889075c,Deep motion features for visual tracking,"Deep Motion Features for Visual Tracking
 Susanna Gladh, Martin Danelljan, Fahad Shahbaz Khan, Michael Felsberg
 Computer Vision Laboratory, Department of Electrical Engineering, Link¨oping University, Sweden"
-26c884829897b3035702800937d4d15fef7010e4,Facial Expression Recognition by Supervised Independent Component Analysis Using MAP Estimation,"IEICE TRANS. INF. & SYST., VOL.Exx–??, NO.xx XXXX 200x
-PAPER
-Facial Expression Recognition by Supervised Independent
-Component Analysis using MAP Estimation
-Fan CHEN
-, Nonmember and Kazunori KOTANI
-, Member
-SUMMARY Permutation ambiguity of the classical Inde-
-pendent Component Analysis (ICA) may cause problems in fea-
-ture extraction for pattern classiﬁcation. Especially when only a
-small subset of components is derived from data, these compo-
-nents may not be most distinctive for classiﬁcation, because ICA
-is an unsupervised method. We include a selective prior for de-
-mixing coef‌f‌icients into the classical ICA to alleviate the problem.
-Since the prior is constructed upon the classiﬁcation information
-from the training data, we refer to the proposed ICA model with
-selective prior as a supervised ICA (sICA). We formulated the
-learning rule for sICA by taking a Maximum a Posteriori (MAP)
-scheme and further derived a ﬁxed point algorithm for learning
-the de-mixing matrix. We investigate the performance of sICA"
 26d52680d610a2a19483e5fe9bb1421cc26207e6,An Asynchronous Hidden Markov Model for Audio-Visual Speech Recognition,"An Asynchronous  Hidden  Markov  Model
 for  Audio-Visual  Speech Recognition
 Samy Bengio
@@ -42712,10 +36337,6 @@ Douwe Kiela
 Facebook AI Research
 Allan Jabri1
 UC Berkeley"
-26c89f890da91119ffa16d5a23fba963257ef3fc,Tattoo Image Search at Scale: Joint Detection and Compact Representation Learning,"Tattoo Image Search at Scale: Joint Detection
-nd Compact Representation Learning
-Hu Han, Member, IEEE, Jie Li, Anil K. Jain, Fellow, IEEE,
-Shiguang Shan, Senior Member, IEEE and Xilin Chen, Fellow, IEEE"
 26c7eda262dfda1c3a3597a3bf1f2f1cc4013425,Some Like It Hot — Visual Guidance for Preference Prediction,"Some like it hot - visual guidance for preference prediction
 Rasmus Rothe
 CVL, ETH Zurich
@@ -42723,10 +36344,6 @@ Radu Timofte
 CVL, ETH Zurich
 Luc Van Gool
 KU Leuven, ETH Zurich"
-267bb08aa4eeefa1ef653716ca0ab572748a3a4e,Vision-Based Real-Time Aerial Object Localization and Tracking for UAV Sensing System,"Vision-based Real-Time Aerial Object Localization
-nd Tracking for UAV Sensing System
-Yuanwei Wu, Student Member,
-IEEE, Yao Sui, Member, IEEE, and Guanghui Wang, Member, IEEE"
 26e570049aaedcfa420fc8c7b761bc70a195657c,Hybrid Facial Regions Extraction for Micro-expression Recognition System,"J Sign Process Syst
 DOI 10.1007/s11265-017-1276-0
 Hybrid Facial Regions Extraction for Micro-expression
@@ -42793,26 +36410,6 @@ Richard Moore
 Mat Cook
 Alex Kipman
 Microsoft Research Cambridge & Xbox Incubation"
-15b44a1c3602385b6cf3eeb049cb2d6c12bb7d74,Automatic semantic annotation of images based on Web data,"010 Sixth International
-Conference
-on Information
-Assurance
-nd Security
-Automatic
-semantic annotation
-of images based on Web data
-Guiguang Ding
-School of Software
-University
-of Tsinghua
-Beijing,
-China
-edu.cn
-School of Software
-University
-Beijing,
-China
-of Tsinghua"
 15f57134b42638cbd57d0d8c4437e8b6b6a8bac4,Learning Visual Reasoning Without Strong Priors,"Learning Visual Reasoning Without Strong Priors
 Ethan Perez12, Harm de Vries1, Florian Strub3,
 Vincent Dumoulin1, Aaron Courville14
@@ -42841,18 +36438,6 @@ Jose Oramas M., Tinne Tuytelaars
 KU Leuven, ESAT-PSI, iMinds"
 15e6e1551ce9a4094c57db70985e420e57c6997a,Asymmetric cross-view dictionary learning for person re-identification,"978-1-5090-4117-6/17/$31.00 ©2017 IEEE
 ICASSP 2017"
-1548cea1fa9be7a23d4d1e38086336913d501e44,Semantic 3 D Reconstruction of Heads Supplementary Material,"Semantic 3D Reconstruction of Heads
-Supplementary Material
-Fabio Maninchedda1, Christian H¨ane2,(cid:63), Bastien Jacquet3,(cid:63),
-Ama¨el Delaunoy(cid:63), Marc Pollefeys1,4
-ETH Zurich
-UC Berkeley
-Kitware SAS
-Microsoft
-Fig. 1: From left to right: Input image; Input labels and depth; Depth map fusion
-(TV-Flux fusion from [9]); Statistical model of [7] ﬁtted into our raw input data;
-Our semantic reconstruction; Our result skin class only; Our model textured.
-(cid:63) Work done while authors were at the Department of Computer Science, ETH Z¨urich"
 155033f2f096934042d659d10912ef29aa1cdbd1,Visual classification of coarse vehicle orientation using Histogram of Oriented Gradients features,"Visual Classiﬁcation of Coarse Vehicle Orientation
 using Histogram of Oriented Gradients Features
 Paul E. Rybski and Daniel Huber and Daniel D. Morris and Regis Hoffman"
@@ -42894,11 +36479,6 @@ of the requirements for the degree of
 Doctor of Philosophy
 BOSTON
 UNIVERSITY"
-15df73918e084a146cd215b839a3eec1cc813a78,Projection Peak Analysis for Rapid Eye Localization,"PROJECTION PEAK ANALYSIS FOR RAPID EYE LOCALIZATION
-Research Center of Intelligent Robotics, Shanghai Jiaotong University, Shanghai, 200240, China
-Jingwen Dai, Dan Liu and Jianbo Su
-Keywords:
-Eye localization, Threshold, Segmentation, Projection peak."
 15292f380f5996f539f4d5e93dba3082d53338fb,Feature Space Optimization for Semantic Video Segmentation,"Feature Space Optimization for Semantic Video Segmentation
 Abhijit Kundu∗
 Georgia Tech
@@ -42908,16 +36488,6 @@ Intel Labs
 Intel Labs
 Figure 1. Semantic video segmentation on the Cityscapes dataset [6]. Input frame on the left, semantic segmentation computed by our
 pproach on the right."
-156b194d0cee545337524bd993ae640ed227b79e,RADON TRANSFORM AND SYMBOLIC LINEAR DISCRIMINANT ANALYSIS BASED 3 D FACE RECOGNITION USING KNN AND SVM,"ISSN   2320 - 2602
-Volume 2, No.12, December 2013
-P. S. Hiremath et al., International Journal of  Advances in Computer Science and Technology, 2(12), December 2013, 267-274
-International Journal of  Advances in Computer Science and Technology
-Available Online at http://warse.org/pdfs/2013/ijacst022122013.pdf
-RADON TRANSFORM AND SYMBOLIC LINEAR DISCRIMINANT
-ANALYSIS BASED 3D FACE RECOGNITION USING KNN AND SVM
-P. S. Hiremath, Manjunatha Hiremath1
-Department of Computer Science,
-Gulbarga University, Gulbarga, Karnataka, India"
 159b52158512481df7684c341401efbdbc5d8f02,Object Detection with Active Sample Harvesting,"Object Detection
 with Active Sample Harvesting
 Thèse no 7312
@@ -42984,10 +36554,6 @@ data points; b) Apply spectral clustering on the afﬁnity matrix to recover
 the data segmentation. Dividing the problem in two steps is, on the one
 hand, appealing because the ﬁrst step can be solved using convex optimiza-"
 15728d6fd5c9fc20b40364b733228caf63558c31,EXPANDING THE BREADTH AND DETAIL OF OBJECT RECOGNITION,(cid:13) 2013 Ian N. Endres
-15f70a0ad8903017250927595ae2096d8b263090,Learning Robust Deep Face Representation,"Learning Robust Deep Face Representation
-University of Science and Technology Beijing
-Xiang Wu
-Beijing, China"
 15383ae2d86eb8c5e172168f94ef915a7a238b72,Learning Semantic Prediction using Pretrained Deep Feedforward Networks,"Learning Semantic Prediction using
 Pretrained Deep Feedforward Networks
 J¨org Wagner1,2, Volker Fischer1, Michael Herman1 and Sven Behnke2
@@ -43038,46 +36604,6 @@ The OU-ISIR Gait Database comprising the
 Large Population Dataset with Age and
 performance evaluation of age estimation
 Chi Xu1,2, Yasushi Makihara2*, Gakuto Ogi2, Xiang Li1,2, Yasushi Yagi2 and Jianfeng Lu1"
-1542b8a1805d73a755d4b2eb402c5c861e6acd02,PMCTrack: Delivering Performance Monitoring Counter Support to the OS Scheduler,"PMCTrack: Delivering performance
-monitoring counter support to the OS
-scheduler
-J. C. Saez1, A. Pousa2, R. Rodr´ıguez-Rodr´ıguez1, F. Castro1,
-M. Prieto-Matias1
-ArTeCS Group, Facultad de Inform´atica, Complutense University of Madrid
-III-LIDI, Facultad de Inform´atica, National University of La Plata
-Email:
-Hardware performance monitoring counters (PMCs) have proven effective in
-haracterizing application performance. Because PMCs can only be accessed
-directly at the OS privilege level, kernel-level tools must be developed to enable
-the end user and userspace programs to access PMCs. A large body of work
-has demonstrated that the OS can perform effective runtime optimizations in
-multicore systems by leveraging performance-counter data. Special attention has
-een paid to optimizations in the OS scheduler. While existing performance
-monitoring tools greatly simplify the collection of PMC application data from
-userspace, they do not provide an architecture-agnostic kernel-level mechanism
-that is capable of exposing high-level PMC metrics to OS components, such as
-the scheduler. As a result, the implementation of PMC-based OS scheduling
-schemes is typically tied to speciﬁc processor models."
-15cf1f17aeba62cd834116b770f173b0aa614bf4,Facial Expression Recognition using Neural Network with Regularized Backpropagation Algorithm,"International Journal of Computer Applications (0975 – 8887)
-Volume 77 – No.5, September 2013
-Facial Expression Recognition using Neural Network with
-Regularized Back-propagation Algorithm
-Ashish Kumar Dogra
-Research Scholar
-Department of ECE,
-Lovely Professional University,
-Phagwara, India
-Nikesh Bajaj
-Assistant Professor
-Department of ECE,
-Lovely Professional University,
-Phagwara, India
-Harish Kumar Dogra
-Research Scholar
-Department of ECE,
-Gyan Ganga Institute of
-Technology & Sciences,
-Jabalpur, India"
 159b87e6e68b18f4daa3505bfc415be9b21a7db6,Tracking The Invisible Man - Hidden-object Detection for Complex Visual Scene Understanding,
 150326137da214210b46e0b7f22e30f7e6529006,Pedestrian Detection at Warp Speed: Exceeding 500 Detections per Second,"Pedestrian Detection at Warp Speed: Exceeding 500 Detections per Second
 Floris De Smedt∗, Kristof Van Beeck∗, Tinne Tuytelaars and Toon Goedem´e
@@ -43120,19 +36646,8 @@ Zürich, Switzerland"
 15cf11ddfc046b2ed2766c375e8ad067baaf8347,Active Pedestrian Safety by Automatic Braking and Evasive Steering,"Active Pedestrian Safety
 y Automatic Braking and Evasive Steering
 C. Keller, T. Dang, H. Fritz, A. Joos, C. Rabe and D. M. Gavrila"
-157d2c6dd8c9999b251099ef4211cff8030ae486,Invariance properties of Gabor filter-based features-overview and applications,"Invariance Properties of Gabor Filter Based
-Features – Overview and Applications
-Joni-Kristian Kamarainen∗, Ville Kyrki, Member, IEEE, Heikki K¨alvi¨ainen, Member, IEEE"
 15696370ff33b6e5a81bf5131d80065d6e59804f,Semantically guided location recognition for outdoors scenes,"Semantically Guided Location Recognition for Outdoors Scenes
 Arsalan Mousavian and Jana Koˇseck´a and Jyh-Ming Lien"
-1536579229a334640735725e0b886f8d03aca1e8,Rank of Experts: Detection Network Ensemble,"Rank of Experts: Detection Network Ensemble
-Seung-Hwan Bae1, Youngwan Lee2, Youngjoo Jo2, Yuseok Bae2, Joong-won Hwang2
-Computer Vision Laboratory, Incheon National University, South Korea
-Electronics and Telecommunications Research Institute, Daejeon, South Korea"
-1553084dcbf2235428e7dbf57b57e567c5ea4d1f,AISHELL-2: Transforming Mandarin ASR Research Into Industrial Scale,"AISHELL-2: Transforming Mandarin ASR Research Into Industrial Scale
-Jiayu Du1, Xingyu Na1, Xuechen Liu1, Hui Bu2
-AISHELL foundation∗
-Beijing Shell Shell Technology Co. Ltd., Beijing, China"
 157eb982da8fe1da4c9e07b4d89f2e806ae4ceb6,Connecting the dots in multi-class classification: From nearest subspace to collaborative representation,"MITSUBISHI ELECTRIC RESEARCH LABORATORIES
 http://www.merl.com
 Connecting the Dots in Multi-Class Classiﬁcation: From
@@ -43310,23 +36825,6 @@ Non-Overlapping Cameras using Constrained
 Dominant Sets
 Yonatan Tariku Tesfaye*, Student Member, IEEE, Eyasu Zemene*, Student Member, IEEE,
 Andrea Prati, Senior member, IEEE, Marcello Pelillo, Fellow, IEEE, and Mubarak Shah, Fellow, IEEE"
-beb3fd2da7f8f3b0c3ebceaa2150a0e65736d1a2,Adaptive Histogram Equalization and Logarithm Transform with Rescaled Low Frequency DCT Coefficients for Illumination Normalization,"RESEARCH PAPER
-International Journal of Recent Trends in Engineering Vol 1, No. 1, May 2009,
-Adaptive Histogram Equalization and Logarithm
-Transform with Rescaled Low Frequency DCT
-Coefficients for Illumination Normalization
-Virendra P. Vishwakarma, Sujata Pandey and M. N. Gupta
-Department of Computer Science and Engineering
-Amity School of Engineering Technology, 580, Bijwasan, New Delhi-110061, India
-(Affiliated to Guru Gobind Singh Indraprastha University, Delhi, India)
-Email:
-illumination  normalization.  The
-lighting  conditions.  Most  of  the"
-be993d793e393127e3fb34d27fda255894edaedc,UnFlow: Unsupervised Learning of Optical Flow With a Bidirectional Census Loss,"UnFlow: Unsupervised Learning of Optical Flow
-with a Bidirectional Census Loss
-Simon Meister, Junhwa Hur, Stefan Roth
-Department of Computer Science
-TU Darmstadt, Germany"
 be6f29e129a99529f7ed854384d1f4da04c4ca1f,Spatially Consistent Nearest Neighbor Representations for Fine-Grained Classification. (Représentations d'images basées sur un principe de voisins partagés pour la classification fine),"Spatially Consistent Nearest Neighbor Representations
 for Fine-Grained Classification
 Valentin Leveau
@@ -43369,11 +36867,6 @@ ment les uns des autres, alors qu’ils sont souvent liés.
 Ces relations sont parfois prises en compte, au moyen
 d’un schéma ascendant dépendant fortement de descrip-
 teurs bas-niveaux, induisant des relations non-pertinentes"
-be48b5dcd10ab834cd68d5b2a24187180e2b408f,Constrained Low-Rank Learning Using Least Squares-Based Regularization,"FOR PERSONAL USE ONLY
-Constrained Low-rank Learning Using Least
-Squares Based Regularization
-Ping Li, Member, IEEE, Jun Yu, Member, IEEE, Meng Wang, Member, IEEE,
-Luming Zhang, Member, IEEE, Deng Cai, Member, IEEE, and Xuelong Li, Fellow, IEEE,"
 bebea83479a8e1988a7da32584e37bfc463d32d4,Discovery of Latent 3D Keypoints via End-to-end Geometric Reasoning,"Discovery of Latent 3D Keypoints via
 End-to-end Geometric Reasoning
 Supasorn Suwajanakorn∗ Noah Snavely
@@ -43449,10 +36942,6 @@ stefanos.kaxiras
 Alexandra Jimborean
 lexandra.jimborean
 Uppsala University"
-bea2c35ef78eb40df52e27cf4098f28a79bcbad5,TabletGaze: Unconstrained Appearance-based Gaze Estimation in Mobile Tablets,"TabletGaze: Unconstrained Appearance-based Gaze
-Estimation in Mobile Tablets
-Qiong Huang, Student Member, IEEE,, Ashok Veeraraghavan, Member, IEEE,,
-nd Ashutosh Sabharwal, Fellow, IEEE"
 be9dde86ebd10ecb05808e034e3cadd210fe0bfb,SLAMIT : A Sub-map based SLAM system On-line creation of multi-leveled map,"Master of Science Thesis in Electrical Engineering
 Department of Electrical Engineering, Linköping University, 2016
 SLAMIT: A Sub-map based
@@ -43539,14 +37028,6 @@ Michal Sindlar
 Cognitive Artiﬁcial Intelligence, Utrecht University, Heidelberglaan 6, 3584 CD, Utrecht
 Marco Wiering
 Intelligent Systems Group, Utrecht University, Padualaan 14, 3508 TB, Utrecht"
-be72b20247fb4dc4072d962ced77ed89aa40372f,"Efficient Facial Representations for Age, Gender and Identity Recognition in Organizing Photo Albums using Multi-output CNN","Ef‌f‌icient Facial Representations for Age, Gender
-nd Identity Recognition in Organizing Photo
-Albums using Multi-output CNN
-Andrey V. Savchenko
-Samsung-PDMI Joint AI Center, St. Petersburg Department of Steklov Institute of
-Mathematics
-National Research University Higher School of Economics
-Nizhny Novgorod, Russia"
 be437b53a376085b01ebd0f4c7c6c9e40a4b1a75,Face Recognition and Retrieval Using Cross Age Reference Coding,"ISSN (Online) 2321 – 2004
 ISSN (Print) 2321 – 5526
 INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH IN ELECTRICAL, ELECTRONICS, INSTRUMENTATION AND CONTROL ENGINEERING
@@ -43568,16 +37049,6 @@ Detection with Loopy Graph Models
 Paper by
 T.-P. Tian and S. Sclaroff
 Slides by A. Vedaldi"
-1910f5f7ac81d4fcc30284e88dee3537887acdf3,Semantic Based Hypergraph Reranking Model for Web Image Search,"Volume 6, Issue 5, May 2016                                   ISSN: 2277 128X
-International Journal of Advanced Research in
-Computer Science and Software Engineering
-Research Paper
-Available online at: www.ijarcsse.com
-Semantic Based Hypergraph Reranking Model for Web
-Image Search
-Amol Darkunde, 2Manoj Jalan, 3Yelmar Mahesh, 4Shivadatta Shinde, 5Dnyanda Patil
-, 2, 3, 4 B. E.  Dept of CSE, 5 Asst. Prof. Dept of CSE
-, 2, 3, 4, 5 Dr.D.Y.Patil College of Engineering, Pune, Maharashtra, India"
 19359fb238888c0eb012a4ab5c6f0fa0e9be493b,Enhanced Facial Expression Recognition using 2DPCA Principal component Analysis and Gabor Wavelets,"Enhanced Facial Expression Recognition
 using 2DPCA Principal component Analysis
 nd Gabor Wavelets.
@@ -43606,10 +37077,6 @@ Andreas Ess1, Konrad Schindler1, Bastian Leibe1,2 and Luc van Gool1,3
 ETH Z¨urich
 KU Leuven, IBBT
 RWTH Aachen"
-199fdc3c0b73d9469d2e732c97e889bfc8bf8bff,"Multi-Class Constrained Normalized Cut With Hard, Soft, Unary and Pairwise Priors and its Applications to Object Segmentation","Multi-Class Constrained Normalized Cut With
-Hard, Soft, Unary and Pairwise Priors and Its
-Applications to Object Segmentation
-Han Hu, Jianjiang Feng, Member, IEEE, Chuan Yu, and Jie Zhou, Senior Member, IEEE"
 195d331c958f2da3431f37a344559f9bce09c0f7,Parsing occluded people by flexible compositions,"Parsing Occluded People by Flexible Compositions
 Xianjie Chen, Alan Yuille
 University of California, Los Angeles.
@@ -43682,10 +37149,6 @@ Tim K. Marks
 Mitsubishi Electric Research Labs
 Michael Jones
 Mitsubishi Electric Research Labs"
-1957956856dc04ebee5815bd62874687e2af7260,Joint Optical Flow and Temporally Consistent Semantic Segmentation,"Joint Optical Flow and Temporally Consistent
-Semantic Segmentation
-Junhwa Hur and Stefan Roth
-Department of Computer Science, TU Darmstadt"
 19296e129c70b332a8c0a67af8990f2f4d4f44d1,Is that you? Metric learning approaches for face identification,"Metric Learning Approaches for Face Identiﬁcation
 Is that you?
 M. Guillaumin, J. Verbeek and C. Schmid
@@ -43761,10 +37224,6 @@ Downloaded from SPIE Digital Library on 22 Dec 2009 to 140.116.214.41. Terms of
 Bruno Ordozgoiti*a, Alberto Mozoa, Jes´us Garc´ıa L´opez de Lacalleb
 Department of Computer Systems, Universidad Polit´ecnica de Madrid
 Department of Applied Mathematics, Universidad Polit´ecnica de Madrid"
-197f945b66995e4d006497808586f828f8a88a86,Part Discovery from Partial Correspondence,"Part Discovery from Partial Correspondence
-Subhransu Maji
-Gregory Shakhnarovich
-Toyota Technological Institute at Chicago, IL, USA"
 19c53302bda8a82ec40d314a85b1713f43058a1a,Deep learning models of biological visual information processing,"Turcsány, Diána (2016) Deep learning models of
 iological visual information processing. PhD thesis,
 University of Nottingham.
@@ -43839,11 +37298,6 @@ Wonsik Kim, Bhavya Goyal, Kunal Chawla, Jungmin Lee, Keunjoo Kwon
 Samsung Research,
 Samsung Electronics
 {wonsik16.kim, bhavya.goyal, kunal.chawla, jm411.lee,"
-192723085945c1d44bdd47e516c716169c06b7c0,Vision and Attention Theory Based Sampling for Continuous Facial Emotion Recognition,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation
-Vision and Attention Theory Based Sampling
-for Continuous Facial Emotion Recognition
-Albert C. Cruz, Student Member, IEEE, Bir Bhanu, Fellow, IEEE, and
-Ninad S. Thakoor, Member, IEEE"
 197eafb6abb6b7d2813eec0891b143e27fc57386,Smile! Studying expressivity of happiness as a synergic factor in collaborative information seeking,"Smile! Studying expressivity of happiness as a synergic factor in collaborative
 information seeking.
 Rutgers University has made this article freely available.  Please share how this access benefits you.
@@ -43871,24 +37325,6 @@ Computer Engineering Department
 Istanbul 34230, Turkey
 Technical report TR-ITS.2007.01
 January 26, 2007"
-19bc52323383732c3c7d73e11726f6232515d2f9,KAIST Multi-Spectral Day/Night Data Set for Autonomous and Assisted Driving,"This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination.
-KAIST Multi-Spectral Day/Night Data Set for
-Autonomous and Assisted Driving
-Yukyung Choi
-, Namil Kim, Soonmin Hwang, Kibaek Park, Jae Shin Yoon,
-Kyounghwan An, Member, IEEE, and In So Kweon, Member, IEEE
-i.e., a thermal"
-191753aa338f24bb41f7bacb4326e0c0a1b90459,"Visual People Detection – Different Models , Comparison and Discussion","Visual People Detection – Different Models, Comparison and Discussion
-Bernt Schiele, Mykhaylo Andriluka, Nikodem Majer, Stefan Roth and Christian Wojek
-Department of Computer Science, TU Darmstadt"
-19441b8be551e8134dd9eb33238309bc2de0a42f,Playing for Benchmarks,"Playing for Benchmarks
-Stephan R. Richter
-TU Darmstadt
-Zeeshan Hayder
-Vladlen Koltun
-Intel Labs
-Figure 1. Data for several tasks in our benchmark suite. Clockwise from top left: input video frame, semantic segmentation, semantic
-instance segmentation, 3D scene layout, visual odometry, optical flow. Each task is presented on a different image."
 19d4855f064f0d53cb851e9342025bd8503922e2,Learning SURF Cascade for Fast and Accurate Object Detection,"Learning SURF Cascade for Fast and Accurate Object Detection
 Jianguo Li, Yimin Zhang
 Intel Labs China"
@@ -43982,13 +37418,6 @@ e151c99b5e55bfc03047a2c6c2118cd9e4ad829b,Perspectives on Deep Multimodel Robot L
 Robot Learning
 Wolfram Burgard, Abhinav Valada, Noha Radwan, Tayyab Naseer, Jingwei Zhang,
 Johan Vertens, Oier Mees, Andreas Eitel and Gabriel Oliveira"
-e1e60501677ae67c6a682bac2c17e4fc904ee380,Performance Analysis of Local Binary Pattern Variants in Texture Classification,"Performance Analysis of Local Binary Pattern
-International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
-Volume 06, Issue 05, May 2017, ISSN: 2278 – 1323
-Variants in Texture Classification
-Ch. Sudha Sree1, M. V. P Chandra Sekhara Rao2
-,2Department of CA, Department of CSE, R.V.R &J.C College of Engineering
-Guntur, India"
 e19ebad4739d59f999d192bac7d596b20b887f78,Learning Gating ConvNet for Two-Stream based Methods in Action Recognition,"Learning Gating ConvNet for Two-Stream based Methods in Action
 Recognition
 Jiagang Zhu1,2, Wei Zou1, Zheng Zhu1,2"
@@ -44005,24 +37434,6 @@ Dr.A.V.Senthil Kumar.,
 Director, Hindustan College of Arts and Science,
 Coimbatore, Tamil Nadu, India."
 e1cb110c45c4416f7aff490db2674abe1460259e,Hard-Aware Point-to-Set Deep Metric for Person Re-identification,"Hard-AwarePoint-to-SetDeepMetricforPersonRe-identiﬁcationRuiYu1,ZhiyongDou1,SongBai1,ZhaoxiangZhang2,YongchaoXu1(),andXiangBai1("
-e1140b86c64549cbcd138f868c82ee8aad77d103,Occlusion Handling using Semantic Segmentation and Visibility-Based Rendering for Mixed Reality,"Occlusion Handling using Semantic Segmentation and
-Visibility-Based Rendering for Mixed Reality
-Menandro Roxas
-Tomoki Hori
-Taiki Fukiage
-Tokyo, Japan
-Yasuhide Okamoto
-Takeshi Oishi
-(cid:140)e University of Tokyo"
-e1f815c50a6c0c6d790c60a1348393264f829e60,PEDESTRIAN DETECTION AND TRACKING IN SURVEILLANCE VIDEO By PENNY CHONG,"PEDESTRIAN DETECTION AND TRACKING IN
-SURVEILLANCE VIDEO
-PENNY CHONG
-A project report submitted in partial fulfilment of the
-requirements for the award of Bachelor of Science (Hons.)
-Applied Mathematics with Computing
-Lee Kong Chian Faculty of Engineering and Science
-Universiti Tunku Abdul Rahman
-April 2016"
 e10662a59b5f8e1f5684409023f11ca727647320,Performance Evaluation of Deep Learning Networks for Semantic Segmentation of Traffic Stereo-Pair Images,"Performance Evaluation of Deep Learning Networks for
 Semantic Segmentation of Traffic Stereo-Pair Images
 Vlad Taran, Nikita Gordienko, Yuriy Kochura, Yuri Gordienko, Alexandr Rokovyi, Oleg
@@ -44087,10 +37498,6 @@ Centre, University of Central Lancashire, Preston PR1 2HE, U.K.
 Keywords:
 Face  Recognition,  Shape  Matching  and  Modelling,  Isometric  Embedding  Representation,  Non-Rigid
 Deformation Registration."
-e1725b71f3f127d6a49d24f14bee05aada1e2f96,Part-Based Deep Hashing for Large-Scale Person Re-Identification,"Part-based Deep Hashing for Large-scale
-Person Re-identiﬁcation∗
-Fuqing Zhu, Xiangwei Kong, Member, IEEE, Liang Zheng, Member, IEEE, Haiyan Fu, Member, IEEE,
-Qi Tian, Fellow, IEEE,"
 e1e2b6a8944a4e6f195b6f7371ee9e6b0684ae6b,Generating Personalized Virtual Agent in Speech Dialogue System for People with Dementia,"Generating Personalized Virtual Agent
 in Speech Dialogue System for People
 with Dementia
@@ -44118,22 +37525,6 @@ CNN Inference Engine for mW IoT End-Nodes
 Renzo Andri∗, Lukas Cavigelli∗, Davide Rossi†, Luca Benini∗†
 Integrated Systems Laboratory, ETH Zurich, Zurich, Switzerland
 DEI, University of Bologna, Bologna, Italy"
-e1660c10ae661cf951602232b36047b19198f599,Web Image Search Using Attribute Assisted Re-Ranking Model,"Vol-2 Issue-1 2016
-IJARIIE-ISSN(O)-2395-4396
-Web Image  Search Using  Attribute Assisted  Re-
-Ranking  Model
-Ganesh  R Nagare1, Ashok  V Markad 2
-Information Technology, Amrutvahini College of Engineering, Maharashtra, India"
-e1f790bbedcba3134277f545e56946bc6ffce48d,Image Retrieval Using Attribute Enhanced Sparse Code Words,"International Journal of Innovative Research in Science,
-Engineering and Technology
-(An ISO 3297: 2007 Certified Organization)
-Vol. 3, Issue 5, May 2014
-Sparse Code Words
-ISSN: 2319-8753
-Image Retrieval Using Attribute Enhanced
-M.Balaganesh1, N.Arthi2
-Associate Professor, Department of Computer Science and Engineering, SRV Engineering College, sembodai, india1
-P.G. Student, Department of Computer Science and Engineering, SRV Engineering College, sembodai, India 2"
 e18cc09c3d3d79df6cd40ea5cf13ad40eacb8a73,Visual Transfer Learning: Informal Introduction and Literature Overview,"Visual Transfer Learning: Informal Introduction
 nd Literature Overview
 Erik Rodner
@@ -44225,10 +37616,6 @@ Lunit Inc., Seoul, South Korea
 b9e82ee9bb4cf016b5ed44b7acd2b42e1a5a6be2,Face recognition by applying wavelet subband representation and kernel associative memory,"Face Recognition by Applying Wavelet Subband
 Representation and Kernel Associative Memory
 Bai-Ling Zhang, Haihong Zhang, and Shuzhi Sam Ge, Senior Member, IEEE"
-b9b7b37d7edf4482a6f440e282c3418ab1913afa,ThiNet: Pruning CNN Filters for a Thinner Net.,"ACCEPTED BY IEEE TRANS. PAMI
-ThiNet: Pruning CNN Filters for a Thinner Net
-Jian-Hao Luo, Hao Zhang, Hong-Yu Zhou, Chen-Wei Xie, Jianxin Wu, Member, IEEE,
-nd Weiyao Lin, Senior Member, IEEE"
 b9f8c8db31ab3882f513246b8d39386cea8cf764,Near Real-Time Object Recognition for Pepper based on Deep Neural Networks Running on a Backpack,"Near Real-Time Object Recognition for Pepper
 ased on Deep Neural Networks Running on a
 Backpack
@@ -44280,10 +37667,6 @@ imec-DistriNet, KU Leuven
 imec-DistriNet, KU Leuven"
 b908edadad58c604a1e4b431f69ac8ded350589a,Deep Face Feature for Face Alignment,"Deep Face Feature for Face Alignment
 Boyi Jiang, Juyong Zhang, Bailin Deng, Yudong Guo and Ligang Liu"
-b9305c065b3c95fd0844d16a09fb9cc7c321cf58,Detecting Humans in Dense Crowds Using Locally-Consistent Scale Prior and Global Occlusion Reasoning,"Detecting Humans in Dense Crowds Using
-Locally-Consistent Scale Prior and Global
-Occlusion Reasoning
-Haroon Idrees, Member, IEEE, Khurram Soomro, Member, IEEE, and Mubarak Shah, Fellow, IEEE"
 40377a1bc15a9ec28ea54cc53d5cf0699365634f,Строительство автомобильных дорог на основе 3D-моделей,"НЕКООПЕРАТИВНАЯ БИОМЕТРИЧЕСКАЯ ИДЕНТИФИКАЦИЯ ПО 3D-
 МОДЕЛЯМ ЛИЦА С ИСПОЛЬЗОВАНИЕМ ВИДЕОКАМЕР ВЫСОКОГО
 РАЗРЕШЕНИЯ
@@ -44346,11 +37729,6 @@ ALGORITHM FOR FACE RECOGNITION
 Saurabh Asija1, Rakesh Singh2
 Research Scholar (Computer Engineering Department), Punjabi University, Patiala.
 Asst. Professor (Computer Engineering Department), Punjabi University, Patiala."
-40bd5d4b01c89e84fe2b0f6b1cc22657bf4e8d80,Toward Unconstrained Fingerprint Recognition: A Fully Touchless 3-D System Based on Two Views on the Move,"Toward Unconstrained Fingerprint Recognition:
-Fully Touchless 3-D System
-Based on Two Views on the Move
-Ruggero Donida Labati, Member, IEEE, Angelo Genovese, Member, IEEE,
-Vincenzo Piuri, Fellow, IEEE, and Fabio Scotti, Senior Member, IEEE"
 400aa5cb2fec558f7827c3638993bae34752ff31,Assessing post-detection filters for a generic pedestrian detector in a tracking-by-detection scheme,"(cid:13)2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including
 reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists,
 or reuse of any copyrighted component of this work in other works.
@@ -44401,19 +37779,6 @@ L. D. College of Engineering
 L. D. College of Engineering
 L. D. College of Engineering
 L. D. College of Engineering"
-40536b0cc73fda29a335c6ecf9ce891dcb6d04cd,Face Detection Algorithms : A Comparative Study,"Face Detection Algorithms: A Comparative Study
-Kapil Kumar Gupta1, M. Rizwan Beg 2 , Jitendra Kumar Niranjan3
-1 Department of Computer Science & Engg., Integral University,
-Lucknow, Uttar Pradesh, 226001, India
-Department of Computer Science & Engg., Integral University,
-Lucknow, Uttar Pradesh, 226001, India
-Department of Computer Science & Engg, IMS Engineering College
-Ghaziabad, Uttar Pradesh 201009, India"
-405a70c184e00eefcf797a0e842578ea0b51f6cd,Learning a Family of Detectors via Multiplicative Kernels,"This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination.
-Learning a Family of Detectors
-via Multiplicative Kernels
-Quan Yuan, Member, IEEE, Ashwin Thangali, Student Member, IEEE,
-Vitaly Ablavsky, Student Member, IEEE, and Stan Sclaroff, Senior Member, IEEE"
 40fb4e8932fb6a8fef0dddfdda57a3e142c3e823,A mixed generative-discriminative framework for pedestrian classification,"A Mixed Generative-Discriminative Framework for Pedestrian Classiﬁcation
 Markus Enzweiler1
 Dariu M. Gavrila2,3
@@ -44483,10 +37848,6 @@ Ouriel Grynszpan, Institut des"
 404c7839afe2fec48a06f83d2a532c05ad8ba0d3,Vehicle Classification using Transferable Deep Neural Network Features,"Vehicle Classiﬁcation using Transferable Deep
 Neural Network Features
 Yiren Zhou, Ngai-Man Cheung"
-40f127fa4459a69a9a21884ee93d286e99b54c5f,Optimizing Apparent Display Resolution Enhancement for Arbitrary Videos,"Optimizing Apparent Display Resolution
-Enhancement for Arbitrary Videos
-Michael Stengel*, Member, IEEE, Martin Eisemann, Stephan Wenger,
-Benjamin Hell, Marcus Magnor, Member, IEEE"
 405b43f4a52f70336ac1db36d5fa654600e9e643,What can we learn about CNNs from a large scale controlled object dataset?,"What can we learn about CNNs from a large scale controlled object dataset?
 Ali Borji
 Saeed Izadi
@@ -44532,16 +37893,6 @@ BioID AG, Berlin, Germany
 WWW home page: http://www.bioid.com"
 40205181ed1406a6f101c5e38c5b4b9b583d06bc,Using Context to Recognize People in Consumer Images,"Using Context to Recognize People in Consumer Images
 Andrew C. Gallagher and Tsuhan Chen"
-40a0e080a01094cdb2174e9154540c217d3f9440,IMPROVED SECURITY ASPECTS ON MICROSOFTS TWO-LAYER CAPTCHA,"Vol-2 Issue-5 2017
-IJARIIE-ISSN(O)-2395-4396
-IMPROVED SECURITY ASPECTS ON
-MICROSOFTS
-TWO -LAYER CAPTCHA
-Rachana.B.S, Dhruthi.S, Swarna.R, Chandan.A
-Rachana.B.S, Asst.Prof, ISE, APSCE, B’lore, Karnataka, INDIA
-Dhruthi S, Student, ISE,, APSCE, Karnataka, India
-Swarna R, Student, ISE, APSCE, Karnataka, India
-Chandana A, Student, ISE, APSCE, Karnataka, India"
 40a34d4eea5e32dfbcef420ffe2ce7c1ee0f23cd,Bridging Heterogeneous Domains With Parallel Transport For Vision and Multimedia Applications,"Bridging Heterogeneous Domains With Parallel Transport For Vision and
 Multimedia Applications
 Raghuraman Gopalan
@@ -44578,13 +37929,6 @@ Ning Zhang"
 Dong Huk Park1, Lisa Anne Hendricks1, Zeynep Akata2,3, Anna Rohrbach1,3,
 Bernt Schiele3, Trevor Darrell1, and Marcus Rohrbach4
 EECS, UC Berkeley, 2University of Amsterdam, 3MPI for Informatics, 4Facebook AI Research"
-40f5ae73e598114edab3ddaefc38fbdbf5c114b9,Optical Flow Based Face Recognition under Expression,"International Journal of Information Science and Intelligent System,      3(2): 1-12,          2014
-Optical Flow Based Face Recognition under
-Expression Variations
-Vimala K1,∗, Dr.V.Kalaivani2, V.Anusuya Devi3
-1Assistant Professor, Department of CSE(PG),National Engineering College , Kovilpatti, India
-2  Associate Professor(SG) and Head, Department of CSE(PG),National Engineering College India ,
-Assistant Professor, Department of CSE(PG),National Engineering College, Kovilpatti, India"
 401e6b9ada571603b67377b336786801f5b54eee,Active image clustering: Seeking constraints from humans to complement algorithms,"Active Image Clustering: Seeking Constraints from
 Humans to Complement Algorithms
 November 22, 2011"
@@ -44634,11 +37978,6 @@ Samuel Schulter1,† Menghua Zhai2,†
 Nathan Jacobs2
 Manmohan Chandraker1,3
 NEC-Labs1, Computer Science University of Kentucky2, UC San Diego3"
-40b5d6a6a38b4f222437d49fcbf8986abbf7b060,Frontal face authentication using morphological elastic graph matching,"IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 9, NO. 4, APRIL 2000
-Frontal Face Authentication Using Morphological
-Elastic Graph Matching
-Constatine Kotropoulos, Member, IEEE, Anastasios Tefas, Student Member, IEEE, and
-Ioannis Pitas, Senior Member, IEEE"
 40c6a2b1cb312f11f8225a733545fdabd436e347,Deep Co-Training for Semi-Supervised Image Recognition,"Deep Co-Training for Semi-Supervised
 Image Recognition
 Siyuan Qiao1 Wei Shen1,2 Zhishuai Zhang1 Bo Wang3 Alan Yuille1
@@ -44656,11 +37995,6 @@ The content must not be changed in any way or sold commercially in any format or
 medium without the formal permission of the author.
 When referring to this work, full bibliographic details including the author, title,
 warding institution and date of the thesis must be given."
-40c3b350008ada8f3f53a758e69992b6db8a8f95,Discriminative decorrelation for clustering and classification,"Discriminative Decorrelation for Clustering and
-Classiﬁcation
-Bharath Hariharan1, Jitendra Malik1, and Deva Ramanan2
-Univerisity of California at Berkeley, Berkeley, CA, USA
-University of California at Irvine, Irvine, CA, USA"
 40dab43abef32deaf875c2652133ea1e2c089223,Facial Communicative Signals: valence recognition in task-oriented human-robot Interaction,"Noname manuscript No.
 (will be inserted by the editor)
 Facial Communicative Signals
@@ -44687,11 +38021,6 @@ Pediatric Care"
 for Subspace Clustering
 from Corrupted and Incomplete Data
 Alexander Petukhov, Inna Kozlov"
-40c1aec7e0830bf9dd8a689d671024567311ae72,Interact as You Intend: Intention-Driven Human-Object Interaction Detection,"A SUBMISSION TO IEEE TRANSACTIONS ON MULTIMEDIA
-Interact as You Intend: Intention-Driven
-Human-Object Interaction Detection
-Bingjie Xu, Junnan Li, Yongkang Wong, Member, IEEE, Qi Zhao, Member, IEEE, and
-Mohan S. Kankanhalli, Fellow, IEEE"
 402f6db00251a15d1d92507887b17e1c50feebca,3D Facial Action Units Recognition for Emotional Expression,"D Facial Action Units Recognition for Emotional
 Expression
 Norhaida Hussain1, Hamimah Ujir, Irwandi Hipiny and Jacey-Lynn Minoi2
@@ -44733,26 +38062,6 @@ Ark Verma
 Promotor: Prof. Dr. Marc Brysbaert
 Proefschrift ingediend tot het behalen van de academische graad
 van Doctor in de Psychologie"
-3caf02979d7cd83d2f3894574c86babf3e201bf3,Seeing to hear? Patterns of gaze to speaking faces in children with autism spectrum disorders,"ORIGINAL RESEARCH ARTICLE
-published: 08 May 2014
-doi: 10.3389/fpsyg.2014.00397
-Seeing to hear? Patterns of gaze to speaking faces in
-hildren with autism spectrum disorders
-Julia R. Irwin1,2* and Lawrence Brancazio1,2
-Haskins Laboratories, New Haven, CT, USA
-Department of Psychology, Southern Connecticut State University, New Haven, CT, USA
-Edited by:
-Jean-Luc Schwartz, National Centre
-for Scientiﬁc Research, France
-Reviewed by:
-Satu Saalasti, Brain and Mind
-Laboratory, Aalto University School of
-Science, Finland
-David House, Royal Institute of
-Technology, Sweden
-*Correspondence:
-Julia R. Irwin, Haskins Laboratories,
-00 George Street, New Haven,"
 3c374cb8e730b64dacb9fbf6eb67f5987c7de3c8,Measuring Gaze Orientation for Human-Robot Interaction,"Measuring Gaze Orientation for Human-Robot
 Interaction
 R. Brochard∗, B. Burger∗, A. Herbulot∗†, F. Lerasle∗†
@@ -44839,9 +38148,6 @@ Privacy-Preserving Mobile Analytics
 Seyed Ali Ossia(cid:63), Ali Shahin Shamsabadi(cid:63), Ali Taheri(cid:63), Hamid R. Rabiee(cid:63),
 Nic Lane‡, Hamed Haddadi†
 (cid:63)Sharif University of Technology, ‡University College London, †Queen Mary University of London"
-3c56acaa819f4e2263638b67cea1ec37a226691d,Body Joint Guided 3-D Deep Convolutional Descriptors for Action Recognition,"Body Joint guided 3D Deep Convolutional
-Descriptors for Action Recognition
-Congqi Cao, Yifan Zhang, Member, IEEE, Chunjie Zhang, Member, IEEE, and Hanqing Lu, Senior Member, IEEE"
 3c8da376576938160cbed956ece838682fa50e9f,Aiding face recognition with social context association rule based re-ranking,"Chapter 4
 Aiding Face Recognition with
 Social Context Association Rule
@@ -44891,8 +38197,6 @@ September 2008"
 3ca194773fe583661b988fbdf33f7680764438b3,Exploring Nearest Neighbor Approaches for Image Captioning,"Exploring Nearest Neighbor Approaches for
 Image Captioning
 Jacob Devlin, Saurabh Gupta, Ross Girshick, Margaret Mitchell, C. Lawrence Zitnick"
-3c77e4ce48d1bbcdb682cdc790806e2d5f2d2e1a,Recognition of Genuine Smiles,"Recognition of Genuine Smiles
-Hamdi Dibeklioğlu, Member, IEEE, Albert Ali Salah, Member, IEEE, and Theo Gevers, Member, IEEE"
 3cd10f6f24c49ce677a18f0984ff4466333d8d13,Correcting rolling-shutter distortion of CMOS sensors using facial feature detection,"© 2010 IEEE. Personal use of this material is permitted. Permission from IEEE
 must  be  obtained  for  all  other  uses,  in  any  current  or  future  media,  including
 reprinting/republishing  this  material  for  advertising  or  promotional  purposes,
@@ -45027,13 +38331,6 @@ NYU
 Cordelia Schmida"
 3cc0d9c1f690addd2c82e60f2a460e3c557ff242,Sort Story: Sorting Jumbled Images and Captions into Stories,"Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, pages 925–931,
 Austin, Texas, November 1-5, 2016. c(cid:13)2016 Association for Computational Linguistics"
-3ce0f48106fd872e2c2327596c2677c4680444a2,Use of Vertical Face Profiles for Text Dependent Audio-Visual Biometric Person Authentication.,"Use of Vertical Face Proﬁles for Text Dependent Audio-Visual Biometric Person
-Authentication
-Vinod Pathangay and B. Yegnanarayana
-Department of Computer Science and Engineering
-Indian Institute of Technology Madras
-Chennai- 600 036, India
-(cid:1)vinod,"
 3c49dafc82ee24e70e338b896868cd9f82f0edd7,BIOLOGICALLY MOTIVATED 3 D FACE RECOGNITION by,"BIOLOGICALLY MOTIVATED 3D FACE RECOGNITION
 Albert Ali Salah
 B.S, in Computer Engineering, Bo˘gazi¸ci University, 1998
@@ -45044,12 +38341,6 @@ the requirements for the degree of
 Doctor of Philosophy
 Graduate Program in
 Bo˘gazi¸ci University"
-e644867bc141453d1f0387c76ff5e7f7863c5f4f,Learning Pixel-Level Semantic Affinity with Image-Level Supervision for Weakly Supervised Semantic Segmentation,"Learning Pixel-level Semantic Afﬁnity with Image-level Supervision
-for Weakly Supervised Semantic Segmentation
-Jiwoon Ahn
-DGIST, Korea
-Suha Kwak
-POSTECH, Korea"
 e6e5a6090016810fb902b51d5baa2469ae28b8a1,Title Energy-Efficient Deep In-memory Architecture for NAND Flash Memories,"Title
 Energy-Efficient Deep In-memory Architecture for NAND
 Flash Memories
@@ -45107,11 +38398,6 @@ Tae-Kyun Kim9, Jiˇr´ı Matas1, Carsten Rother3
 CTU in Prague, 2TU Dresden, 3Heidelberg University, 4Toyota Research Institute
 5University of Southern Denmark, 6MVTec Software, 7Taiwan Tech
 8FORTH Heraklion, 9Imperial College London, 10TU Munich"
-e6dc1200a31defda100b2e5ddb27fb7ecbbd4acd,Flexible Manifold Embedding: A Framework for Semi-Supervised and Unsupervised Dimension Reduction,"Flexible Manifold Embedding: A Framework
-for Semi-Supervised and Unsupervised
-Dimension Reduction
-Feiping Nie, Dong Xu, Member, IEEE, Ivor Wai-Hung Tsang, and Changshui Zhang, Member, IEEE
-, the linear regression function ("
 e605242319ba495bc5f47abe9f1c08d508d83627,Importance-Aware Semantic Segmentation for Autonomous Driving System,Proceedings of the Twenty-Sixth International Joint Conference on Artiﬁcial Intelligence (IJCAI-17)
 e63a0ea338dfc7293ddd68074baf250e99d0c6d5,Nonlinear Supervised Dimensionality Reduction via Smooth Regular Embeddings,"Nonlinear Supervised Dimensionality Reduction via
 Smooth Regular Embeddings
@@ -45175,9 +38461,6 @@ PES Institute of Technology; Rajajinagar, Bangalore, Karnataka, India.
 PES University; Banashankari, Bangalore, Karnataka, India.
 * Corresponding author. Tel.: +91-9731054855; email:
 Manuscript submitted May 15, 2018; accepted July 8, 2018."
-e68083909381a8fbd0e4468aa06204ac00a0e6fc,Visual Identification by Signature Tracking,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 25, NO. 2, FEBRUARY 2003
-Visual Identification by Signature Tracking
-Mario E. Munich, Member, IEEE, and Pietro Perona, Member, IEEE"
 e624c73e3057a1de75e9d6d7e813771154ff1375,Incorporating Scalability in Unsupervised Spatio- Temporal Feature Learning,"INCORPORATING SCALABILITY IN UNSUPERVISED SPATIO-TEMPORAL FEATURE
 LEARNING
 Sujoy Paul, Sourya Roy and Amit K. Roy-Chowdhury
@@ -45196,10 +38479,6 @@ Univ. Lille, CNRS, Centrale Lille, Inria,
 UMR 9189 - CRIStAL, F-59000 Lille, France
 Bilal Piot
 DeepMind"
-e6d48d23308a9e0a215f7b5ba6ae30ee5d2f0ef5,Multi-person Tracking by Online Learned Grouping Model with Non-linear Motion Context,"IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, VOL. XX, NO. XX, MONTH YEAR
-Multi-person Tracking by Online Learned Grouping
-Model with Non-linear Motion Context
-Xiaojing Chen, Zhen Qin, Le An, Member, IEEE, and Bir Bhanu, Fellow, IEEE"
 e63f4867c73eff9ff7cdf31246585a6915acef57,Digging Into Self-Supervised Monocular Depth Estimation,"Digging Into Self-Supervised
 Monocular Depth Estimation
 Cl´ement Godard
@@ -45220,12 +38499,6 @@ Xuelin Qian1, Yanwei Fu1, Tao Xiang2, Wenxuan Wang1
 Jie Qiu3, Yang Wu3, Yu-Gang Jiang1, Xiangyang Xue1
 Fudan University; 2Queen Mary University of London;
 Nara Institute of Science and Technology;"
-e68ef9597613cd2b6cf76e81c13eb061ee468485,Latent Convolutional Models,"Published as a conference paper at ICLR 2019
-LATENT CONVOLUTIONAL MODELS
-ShahRukh Athar
-Skolkovo Institute of Science and Technology (Skoltech), Russia
-Evgeny Burnaev
-Victor Lempitsky∗"
 e6d8ebfd88ee333deccce32b09ee41d271af6dc4,Grasp2Vec: Learning Object Representations from Self-Supervised Grasping,"Grasp2Vec: Learning Object Representations
 from Self-Supervised Grasping
 Eric Jang *,1, Coline Devin *,2,†, Vincent Vanhoucke1, and Sergey Levine1,2
@@ -45407,27 +38680,13 @@ Christian Th´eriault(1), Nicolas Thome(1), Matthieu Cord(1), Patrick P´erez(2)
 (1)UPMC-Sorbonne Universities, Paris, France (2)Technicolor, France"
 10be82098017fc2d60b0572cea8032afabad5d1a,A Dataset for Multimodal Question Answering in the Cultural Heritage Domain,"Proceedings of the Workshop on Language Technology Resources and Tools for Digital Humanities (LT4DH),
 pages 10–17, Osaka, Japan, December 11-17 2016."
-10d334a98c1e2a9e96c6c3713aadd42a557abb8b,Scene Text Recognition Using Part-Based Tree-Structured Character Detection,"Scene Text Recognition using Part-based Tree-structured Character Detection
-Cunzhao Shi, Chunheng Wang, Baihua Xiao, Yang Zhang, Song Gao and Zhong Zhang
-State Key Laboratory of Management and Control for Complex Systems, CASIA, Beijing, China"
-106732a010b1baf13c61d0994552aee8336f8c85,Expanded Parts Model for Semantic Description of Humans in Still Images,"Expanded Parts Model for Semantic Description
-of Humans in Still Images
-Gaurav Sharma, Member, IEEE, Fr´ed´eric Jurie, and Cordelia Schmid, Fellow, IEEE"
 10d710c01acb10c4aea702926d21697935656c3d,Infrared Colorization Using Deep Convolutional Neural Networks,"Infrared Colorization Using Deep Convolutional
 Neural Networks
 Matthias Limmer∗, Hendrik P.A. Lensch†
 Daimler AG, Ulm, Germany
 Department of Computer Graphics, Eberhard Karls Universität, Tübingen, Germany"
-106b54ed74f0fffaf6408a9b847d4ac0aa0ffef9,Block-Diagonal Sparse Representation by Learning a Linear Combination Dictionary for Recognition,"JOURNAL OF LATEX CLASS FILES, VOL. 11, NO. 4, DECEMBER 2015
-Block-Diagonal Sparse Representation by Learning
-Linear Combination Dictionary for Recognition
-Xinglin Piao, Yongli Hu, Member, IEEE, Yanfeng Sun, Member, IEEE, Junbin Gao, Baocai Yin, Member, IEEE"
 100641ed8a5472536dde53c1f50fa2dd2d4e9be9,Visual attributes for enhanced human-machine communication,"Visual Attributes for Enhanced Human-Machine Communication*
 Devi Parikh1"
-102a2096ba2e2947dc252445f764e7583b557680,Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks,"Precomputed Real-Time Texture Synthesis with
-Markovian Generative Adversarial Networks
-Chuan Li and Michael Wand
-Institut for Informatik, University of Mainz, Germany"
 10114df7ddbb221337cc1e99e1de0eab8e47c95d,Evaluating Feature Importance for Re-identification,"Chapter 9
 Evaluating Feature Importance for
 Re-Identiﬁcation
@@ -45475,11 +38734,6 @@ Research Supervisor: William T. Freeman"
 1059729bcca57731c81d8a9c866ceb8ed3547d8d,Coupled Object Detection and Tracking from Static Cameras and Moving Vehicles,"Coupled Object Detection and Tracking from
 Static Cameras and Moving Vehicles
 Bastian Leibe, Konrad Schindler, Nico Cornelis, and Luc Van Gool"
-101c5b39f4fc4dda1f39bf0c00e196f0a4720af2,Viewpoint Invariant Human Re-Identification in Camera Networks Using Pose Priors and Subject-Discriminative Features,"Viewpoint Invariant Human Re-identiﬁcation in
-Camera Networks Using Pose Priors and
-Subject-Discriminative Features
-Ziyan Wu, Student Member, IEEE, Yang Li, Student Member, IEEE, and Richard J. Radke, Senior
-Member, IEEE"
 106150b707a31f0825bdae44eca4139b715547d6,Robust Semantic Segmentation with Ladder-DenseNet Models,"Robust Semantic Segmentation with Ladder-DenseNet Models
 Ivan Kreˇso
 Marin Orˇsi´c
@@ -45495,11 +38749,6 @@ Takaaki Hori†, Anoop Cherian†, Tim K. Marks†,
 Irfan Essa∗, Dhruv Batra∗ Devi Parikh∗,
 Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA
 School of Interactive Computing, Georgia Tech"
-108b2581e07c6b7ca235717c749d45a1fa15bb24,Using Stereo Matching with General Epipolar Geometry for 2D Face Recognition across Pose,"Using Stereo Matching with General Epipolar
-Geometry for 2D Face Recognition
-cross Pose
-Carlos D. Castillo, Student Member, IEEE, and
-David W. Jacobs, Member, IEEE"
 10c4b2489d7e1ee43a1d19724d3c1e9c33ca3f29,A Question-Answering framework for plots using Deep learning,"A Question-Answering framework for plots using Deep learning
 Revanth Reddy1, Rahul Ramesh1, Ameet Deshpande1 and Mitesh M. Khapra1
 Indian Institute of Technology Madras"
@@ -45587,10 +38836,6 @@ occlusion of targets and observations
 nonymous submission
 Keywords:
 Tracking, graphical models, MAP inference, particle tracking, live cell tracking, intelligent headlights."
-10e7dd3bbbfbc25661213155e0de1a9f043461a2,Cross Euclidean-to-Riemannian Metric Learning with Application to Face Recognition from Video,"Cross Euclidean-to-Riemannian Metric Learning
-with Application to Face Recognition from Video
-Zhiwu Huang, Member, IEEE, Ruiping Wang, Member, IEEE, Shiguang Shan, Senior Member, IEEE,
-Luc Van Gool, Member, IEEE and Xilin Chen, Fellow, IEEE"
 10e3b9fe646c6e81ec824cdc2391cc412a1b2730,Solving Three Czech NLP Tasks End-to-End with Neural Models,"S. Krajˇci (ed.): ITAT 2018 Proceedings, pp. 138–143
 CEUR Workshop Proceedings Vol. 2203, ISSN 1613-0073, c(cid:13) 2018 Jindˇrich Libovický, Rudolf Rosa, Jindˇrich Helcl, and Martin Popel"
 1038aa6c1f63c1de9045f10e47ed573810cb4a52,A Video-Based Method for Objectively Rating Ataxia,"A Video-Based Method for Objectively Rating Ataxia
@@ -45628,26 +38873,6 @@ schangpi,
 Fei Sha
 U. of California
 Los Angeles, CA"
-107010b7f2abe3c0c9df62bcef35eb77f6fc76df,Domain-adversarial training of neural networks,"Journal of Machine Learning Research 17 (2016) 1-35
-Submitted 5/15; Published 4/16
-Domain-Adversarial Training of Neural Networks
-Yaroslav Ganin
-Evgeniya Ustinova
-Skolkovo Institute of Science and Technology (Skoltech)
-Skolkovo, Moscow Region, Russia
-Hana Ajakan
-Pascal Germain
-D´epartement d’informatique et de g´enie logiciel, Universit´e Laval
-Qu´ebec, Canada, G1V 0A6
-Hugo Larochelle
-D´epartement d’informatique, Universit´e de Sherbrooke
-Qu´ebec, Canada, J1K 2R1
-Fran¸cois Laviolette
-Mario Marchand
-D´epartement d’informatique et de g´enie logiciel, Universit´e Laval
-Qu´ebec, Canada, G1V 0A6
-Victor Lempitsky
-Skolkovo Institute of Science and Technology (Skoltech)"
 4c1ef2a628627798939dccc072d33f9e12b48640,Advanced Hybrid Color Space Normalization for Human Face Extraction and Detection,"IJSRD - International Journal for Scientific Research & Development| Vol. 1, Issue 4, 2013 | ISSN (online): 2321-0613
 Advanced Hybrid Color Space Normalization for Human Face
 Extraction and Detection
@@ -45671,26 +38896,6 @@ its Application to Sepsis Classiﬁcation
 Yoshihide Sawada1 and Yoshikuni Sato2 and Toru Nakada2 and Kei Ujimoto2 and Nobuhiro Hayashi3"
 4c39000bbd6761dd9e5609fe310af51facb835a9,Kinects and human kinetics : A new approach for studying pedestrian behavior,"This paper might be a pre-copy-editing or a post-print author-produced .pdf of an article accepted for publication. For the
 definitive publisher-authenticated version, please refer directly to publishing house’s archive system."
-4cf17bca0e19070fbe9bb25644787f65fa6ebe1a,Human Pose Estimation.,"Human pose estimation
-Leonid Sigal, Disney Research, Pittsburgh
-Synonyms
-– Articulated pose estimation
-– Body conﬁguration recovery
-Related Concepts
-– Human pose tracking
-– People tracking
-– Articulated pose tracking
-– Body parsing
-– People parsing
-Deﬁnition
-Human pose estimation is the process of estimating the conﬁguration of the
-ody (pose) from a single, typically monocular, image.
-Background
-Human pose estimation is one of the key problems in computer vision that
-has been studied for well over 15 years. The reason for its importance is the
-bundance of applications that can beneﬁt from such a technology. For example,
-human pose estimation allows for higher level reasoning in the context of human-
-omputer interaction and activity recognition; it is also one of the basic building"
 4c81789b13b016afc5ef47591268533674c2a3f6,Mapless Online Detection of Dynamic Objects in 3D Lidar,"Mapless Online Detection of Dynamic Objects in 3D Lidar
 David J. Yoon, Tim Y. Tang, and Timothy D. Barfoot
 model-free,"
@@ -45751,20 +38956,6 @@ Yang Wang‡
 University of Illinois at Urbana Champaign†
 David Forsyth†
 University of Manitoba‡"
-4c1ce6bced30f5114f135cacf1a37b69bb709ea1,Gaze direction estimation by component separation for recognition of Eye Accessing Cues,"Gaze Direction Estimation by Component Separation for
-Recognition of Eye Accessing Cues
-Ruxandra Vrˆanceanu
-Image Processing and Analysis Laboratory
-University ”Politehnica” of Bucharest, Romania, Address Splaiul Independent¸ei 313
-Corneliu Florea
-Image Processing and Analysis Laboratory
-University ”Politehnica” of Bucharest, Romania, Address Splaiul Independent¸ei 313
-Laura Florea
-Image Processing and Analysis Laboratory
-University ”Politehnica” of Bucharest, Romania, Address Splaiul Independent¸ei 313
-Constantin Vertan
-Image Processing and Analysis Laboratory
-University ”Politehnica” of Bucharest, Romania, Address Splaiul Independent¸ei 313"
 4c4454aa7a2a244c678f507a982fe8827ba419bb,Adversarial Examples for Semantic Image Segmentation,"Workshop track - ICLR 2017
 ADVERSARIAL EXAMPLES FOR
 SEMANTIC IMAGE SEGMENTATION
@@ -45784,33 +38975,11 @@ Jianqing Zhu, Huanqiang Zeng, Jingchang Huang, Shengcai Liao, Zhen Lei, Canhui C
 4cbb370f0bb6af0052bad6855cf1d9776376ceb3,Towards Safe Autonomous Driving: Capture Uncertainty in the Deep Neural Network For Lidar 3D Vehicle Detection,"Towards Safe Autonomous Driving: Capture Uncertainty in the Deep
 Neural Network For Lidar 3D Vehicle Detection
 Di Feng1, Lars Rosenbaum1, Klaus Dietmayer2"
-4cbb4801667e2bee41e849b7d226cfcd1c501139,Stixmantics: A Medium-Level Model for Real-Time Semantic Scene Understanding,"Stixmantics: A Medium-Level Model
-for Real-Time Semantic Scene Understanding
-Timo Scharw¨achter1,2, Markus Enzweiler1, Uwe Franke1, and Stefan Roth2
-Environment Perception, Daimler R&D, Sindelﬁngen, Germany
-Department of Computer Science, TU Darmstadt, Germany"
 4cfdd0c8313ac4f92845dcd658115beb115b97ce,Multi-Task Learning as Multi-Objective Optimization,"Multi-Task Learning as Multi-Objective Optimization
 Ozan Sener
 Intel Labs
 Vladlen Koltun
 Intel Labs"
-4cfae149d6acd8cffc12c06ed796f1f84dce0e73,Face Recognition Based on Image Latent Semantic Analysis Model and SVM,"International Journal of Signal Processing, Image Processing and Pattern Recognition
-Vol. 6, No. 3, June, 2013
-Face Recognition Based on Image Latent Semantic Analysis Model
-nd SVM
-Jucheng Yang 1, 2, Min Luo3 and Yanbin Jiao4
-Ahead Software Company Limited, Nanchang, 330041, China
-College of Computer Science and Information Engineering, Tianjin University of
-Science and Technology, Tianjin, China
-Jiangxi Institute of Computing Technology, Nanchang, China
-School of Information Technology, Jiangxi University of Finance and Economics,
-Nanchang, China"
-4cff5b5099b0227730efa9e9fd724a63dc0c0c2f,Learning Efficient Binary Codes From High-Level Feature Representations for Multilabel Image Retrieval,"Learning Efﬁcient Binary Codes From
-High-Level Feature Representations
-for Multilabel Image Retrieval
-Lei Ma
-, Hongliang Li, Senior Member, IEEE, Fanman Meng, Member, IEEE, Qingbo Wu, Member, IEEE,
-nd King Ngi Ngan, Fellow, IEEE"
 4c0d7c0c4b0a1dd2fd11853ab98ea1fa79e0716b,Feature Extraction for Human Detection using HOG and CS-LBP methods,"International Journal of Computer Applications (0975 – 8887)
 National Conference “Electronics, Signals, Communication and Optimization"" (NCESCO 2015)
 Feature Extraction for Human Detection using HOG and
@@ -45859,11 +39028,6 @@ Christophe Garcia
 France Telecom R&D – TECH/IRIS
 , rue du Clos Courtel – BP 91226
 5512 Cesson Sévigné Cedex, France"
-4cc675422395ed7dc7e4772280f7c57cac6fbaee,Efficient person re-identification by hybrid spatiogram and covariance descriptor,"Efﬁcient Person Re-identiﬁcation by Hybrid Spatiogram and Covariance
-Descriptor
-Mingyong Zeng, Zemin Wu, Chang Tian, Lei Zhang, and Lei Hu
-College of Communications Engineering, PLA University
-of Science and Technology, Nanjing 210007, China"
 4c0ce0ed9cc92115874be4397f6240769d3ed84f,The effect of familiarity on face adaptation.,"doi:10.1068/p6774
 The effect of familiarity on face adaptation
 Sarah Laurence, Graham Hole
@@ -45939,17 +39103,6 @@ Dan Mikami, Kazuhiro Otsuka, Shiro Kumano and Junji Yamato
 NTT Communication Science Laboratories, NTT, 3-1 Morinosato-Wakamiya, Atsugi, Kanagawa, 243-0198, Japan
 Keywords:
 Pose Tracking, Face Pose, Memory-based Prediction, Memory Acquisition."
-4c22a9f6f3f2a6071327a1fa1f6fdc7ffd06987c,Face Recognition System with various Expression and Occlusion based on a Novel Block Matching Algorithm and PCA,"International Journal of Computer Applications (0975 – 8887)
-Volume 38– No.11, January 2012
-Face Recognition System with various Expression
-nd Occlusion based on a Novel Block Matching
-Algorithm and PCA
-Shermina.J
-V.Vasudevan
-Department of Information Technology
-HoD, Department of Information Technology
-Kalasalingam University
-India"
 4c88e41424022c7c5f111d34d931fae15f52a551,"CUR Decompositions, Similarity Matrices, and Subspace Clustering","CUR Decompositions, Similarity Matrices, and
 Subspace Clustering
 Akram Aldroubi, Keaton Hamm, Ahmet Bugra Koku, and Ali Sekmen"
@@ -45986,17 +39139,6 @@ Adam Z. Stieg2,3*, James K. Gimzewski1,2,3
 Department of Chemistry and Biochemistry, University of California Los Angeles, Los Angeles, California, United States of America, 2 California NanoSystems Institute,
 University of California Los Angeles, Los Angeles, California, United States of America, 3 World Premier International Center for Materials Nanoarchitectonics, National
 Institute for Materials Science, Tsukuba, Ibaraki, Japan"
-4c41b774a6bdf43d980f640880cc49b82ae19b34,3D Facial Landmark Detection under Large Yaw and Expression Variations,"D Facial Landmark Detection under
-Large Yaw and Expression Variations
-Panagiotis Perakis, Member, IEEE Computer Society, Georgios Passalis,
-Theoharis Theoharis, and Ioannis A. Kakadiaris, Senior Member, IEEE"
-4cbf873d3d359200267a3bc33d45c442061f6989,Robust FFT-Based Scale-Invariant Image Registration with Image Gradients,"Short Papers___________________________________________________________________________________________________
-Robust FFT-Based Scale-Invariant Image
-Registration with Image Gradients
-Georgios Tzimiropoulos, Member, IEEE,
-Vasileios Argyriou, Member, IEEE,
-Stefanos Zafeiriou, Member, IEEE, and
-Tania Stathaki"
 4c55ea9c04d46d60ec5789f4e4c3224c41360768,Dimensionality Reduction Using Similarity-Induced Embeddings,"IEEE Copyright Notice
 Copyright c(cid:13)2017 IEEE
 Personal use of this material is permitted. Permission from
@@ -46050,37 +39192,6 @@ Jia Jie Zhu"
 8646f22a46b65c2018bc39ad3cbdb939e788a1fc,Learning a Confidence Measure for Optical Flow,"Learning a Conﬁdence Measure
 for Optical Flow
 Oisin Mac Aodha, Ahmad Humayun, Marc Pollefeys and Gabriel J. Brostow"
-861b12f405c464b3ffa2af7408bff0698c6c9bf0,An Effective Technique for Removal of Facial Dupilcation by SBFA Miss .,"International Journal on Recent and Innovation Trends in Computing and Communication                                                     ISSN: 2321-8169
-Volume: 3 Issue: 5
-3337 - 3342
-_______________________________________________________________________________________________
-An Effective Technique for Removal of Facial Dupilcation by SBFA
-Miss. Deepika B. Patil
-Computer Department,
-GHRCEM,
-Pune, India
-Dr. Ayesha Butalia
-Computer Department,
-GHRCEM,
-Pune, India"
-86be567bab1293ed847979d2c56a662fcbcbc1d5,Exploiting View-Specific Appearance Similarities Across Classes for Zero-Shot Pose Prediction: A Metric Learning Approach,"Exploiting View-Speciﬁc Appearance Similarities Across Classes for
-Zero-shot Pose Prediction: A Metric Learning Approach
-Alina Kuznetsova
-Leibniz University Hannover
-Appelstr 9A, 30169
-Hannover, Germany
-Sung Ju Hwang
-UNIST
-50 UNIST-gil, 689798
-Ulsan, Korea
-Bodo Rosenhahn
-Leibniz University Hannover
-Appelstr 9A, 30169
-Hannover, Germany
-Leonid Sigal
-Disney Research
-720 Forbes Avenue, 15213
-Pittsburgh, PA, US"
 8629c779581a0f46452bc4ca45b571bfbd3cd063,Defoiling Foiled Image Captions,"Defoiling Foiled Image Captions
 Pranava Madhyastha, Josiah Wang and Lucia Specia
 Department of Computer Science
@@ -46115,26 +39226,6 @@ Peer reviewed
 eScholarship.org
 Powered by the California Digital Library
 University of California"
-86cdc6ae46f53ac86b9e0ace2763c5fe15633055,Experimental Force-Torque Dataset for Robot Learning of Multi-Shape Insertion,"Experimental Force-Torque Dataset for Robot Learning of Multi-Shape Insertion
-Giovanni De Magistris1, Asim Munawar1, Tu-Hoa Pham1, Tadanobu Inoue1,
-Phongtharin Vinayavekhin1, Ryuki Tachibana1
-IBM Research - Tokyo, Japan
-The accurate modeling of real-world systems and
-physical interactions is a common challenge towards the
-resolution of robotics tasks. Machine learning approaches
-have demonstrated signiﬁcant results in the modeling of
-omplex systems (e.g., articulated robot structures, ca-
-le stretch, fluid dynamics), or to learn robotics tasks
-(e.g., grasping, reaching) from raw sensor measurements
-without explicit programming, using reinforcement learn-
-ing. However, a common bottleneck in machine learn-
-ing techniques resides in the availability of suitable data.
-While many vision-based datasets have been released in
-the recent years, ones involving physical interactions, of
-particular interest for the robotic community, have been
-scarcer. In this paper, we present a public dataset on peg-
-in-hole insertion tasks containing force-torque and pose
-information for multiple variations of convex-shaped pegs."
 867fd4914a265b5dd4494f14273b8d28257c7b5b,A Comparison of FPGA and GPGPU Designs for Bayesian Occupancy Filters,"Article
 A Comparison of FPGA and GPGPU Designs for
 Bayesian Occupancy Filters
@@ -46242,19 +39333,6 @@ Person Re-identiﬁcation
 Jiayun Wanga, Sanping Zhoua, Jinjun Wanga,∗, Qiqi Houa
 The institute of artiﬁcial intelligence and robotic, Xi’an Jiaotong University, Xianning West Road
 No.28, Shaanxi, 710049, P.R. China"
-86f72a4391c3b90a03f8fbbd28d4846947f028d6,Principal Manifolds and Probabilistic Subspaces for Visual Recognition,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 24, NO. 6,
-JUNE 2002
-Principal Manifolds and Probabilistic
-Subspaces for Visual Recognition
-Baback Moghaddam, Member, IEEE"
-867e709a298024a3c9777145e037e239385c0129,ANALYTICAL REPRESENTATION OF UNDERSAMPLED FACE RECOGNITION APPROACH BASED ON DICTIONARY LEARNING AND SPARSE REPRESENTATION,"INTERNATIONAL JOURNAL
-OF PROFESSIONAL ENGINEERING STUDIES                                                                                                            Volume VIII /Issue 2 / FEB 2017
-ANALYTICAL REPRESENTATION OF UNDERSAMPLED FACE
-RECOGNITION APPROACH BASED ON DICTIONARY LEARNING
-AND  SPARSE REPRESENTATION
-Murala Sandeep1 A.Mallikarjuna Reddy2 P.Rajashaker Reddy3 Dr. G. Vishnu murthy4
-(M.Tech)1, Assistant Professor2, Assistant Professor3, HOD of CSE Department4
-Anurag group of institutions Ghatkesar, Ranga Reddy, Hyderabad, India"
 86614c2d2f6ebcb9c600d4aef85fd6bf6eab6663,Benchmarks for Cloud Robotics,"Benchmarks for Cloud Robotics
 Arjun Singh
 Electrical Engineering and Computer Sciences
@@ -46262,34 +39340,6 @@ University of California at Berkeley
 Technical Report No. UCB/EECS-2016-142
 http://www.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-142.html
 August 12, 2016"
-86163c4270fa1173640e7b1f526ffdb482f45f17,ContextVP: Fully Context-Aware Video Prediction,"ContextVP: Fully Context-Aware Video
-Prediction
-Wonmin Byeon1,2,3,4, Qin Wang2,
-Rupesh Kumar Srivastava4, and Petros Koumoutsakos2
-NVIDIA, Santa Clara, CA, USA
-ETH Zurich, Zurich, Switzerland
-The Swiss AI Lab IDSIA, Manno, Switzerland
-NNAISENSE, Lugano, Switzerland"
-86e5f81bde496549e9df2b1abdef0879a3135adb,The Visual QA Devil in the Details: The Impact of Early Fusion and Batch Norm on CLEVR,"The Visual QA Devil in the Details: The Impact
-of Early Fusion and Batch Norm on CLEVR
-Mateusz Malinowski and Carl Doersch
-DeepMind, London, United Kingdom
-Introduction
-Visual QA is a pivotal challenge for higher-level reasoning [1,2,3,4], requiring
-understanding language, vision, and relationships between many objects in a
-scene. Although datasets like CLEVR [5] are designed to be unsolvable with-
-out such complex relational reasoning, some surprisingly simple feed-forward,
-“holistic” models have recently shown strong performance on this dataset [6,7].
-These models lack any kind of explicit iterative, symbolic reasoning procedure,
-which are hypothesized to be necessary for counting objects, narrowing down
-the set of relevant objects based on several attributes, etc. The reason for this
-strong performance is poorly understood. Hence, our work analyzes such mod-
-els, and ﬁnds that minor architectural elements are crucial to performance. In
-particular, we ﬁnd that early fusion of language and vision provides large per-
-formance improvements. This contrasts with the late fusion approaches popular
-t the dawn of Visual QA [5,8,9,10]. We propose a simple module we call Mul-
-timodal Core (MC), which we hypothesize performs the fundamental operations
-for multimodal tasks. We believe that understanding why these elements are so"
 861802ac19653a7831b314cd751fd8e89494ab12,"Time-of-Flight and Depth Imaging. Sensors, Algorithms, and Applications","Marcin Grzegorzek, Christian Theobalt, Reinhard Koch,
 Andreas Kolb
 Time-of-Flight and Depth Imaging. Sensors, Algorithms
@@ -46312,26 +39362,6 @@ last few years. The present
 techniques..."
 86c053c162c08bc3fe093cc10398b9e64367a100,Cascade of forests for face alignment,"Cascade of Forests for Face Alignment
 Heng Yang, Changqing Zou, Ioannis Patras"
-86b6de59f17187f6c238853810e01596d37f63cd,Competitive Representation Based Classification Using Facial Noise Detection,"(IJACSA) International Journal of Advanced Computer Science and Applications,
-Vol. 7, No. 3, 2016
-Competitive Representation Based Classification
-Using Facial Noise Detection
-Tao Liu
-Ying Liu
-Chongqing Key Laboratory of Computational Intelligence
-College of Computer Science and Technology, Chongqing
-Chongqing Key Laboratory of Computational Intelligence
-College of Computer Science and Technology, Chongqing
-University of Posts and Telecommunications
-University of Posts and Telecommunications
-Chongqing, China
-Chongqing, China
-Cong Li
-Chao Li
-Chongqing Key Laboratory of Computational Intelligence
-College of Computer Science and Technology, Chongqing
-Chongqing Key Laboratory of Computational Intelligence
-College of Computer Science and Technology, Chongqing"
 86b1751b265b289b09de79956e77a01d82e12086,Face recognition in multi-camera surveillance videos,"1st International Conference on Pattern Recognition (ICPR 2012)
 November 11-15, 2012. Tsukuba, Japan
 978-4-9906441-1-6 ©2012 IAPR"
@@ -46400,14 +39430,6 @@ destinée au dépôt et à la diffusion de documents
 scientifiques de niveau recherche, publiés ou non,
 émanant des établissements d’enseignement et de
 recherche français ou étrangers, des laboratoires"
-da4170c862d8ae39861aa193667bfdbdf0ecb363,Multi-Task CNN Model for Attribute Prediction,"Multi-task CNN Model for Attribute Prediction
-Abrar H. Abdulnabi, Student Member, IEEE, Gang Wang, Member, IEEE, , Jiwen Lu, Member, IEEE
-nd Kui Jia, Member, IEEE"
-da24f3e196c5345ce08dfcc835574035da197f48,A Global Alignment Kernel based Approach for Group-level Happiness Intensity Estimation,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2017
-A Global Alignment Kernel based Approach for
-Group-level Happiness Intensity Estimation
-Xiaohua Huang, Abhinav Dhall, Roland Goecke, Member, IEEE, Matti Pietik¨ainen, Fellow, IEEE, and
-Guoying Zhao, Senior Member, IEEE"
 daef6fa60c7d79930ad0a341aab69f1f4fa80442,Supplement for BIER,"Supplement for BIER
 . Introduction
 In this document we provide further insights into Boost-
@@ -46589,9 +39611,6 @@ University Malaysia Perlis (UniMAP)
 School of Mechatronics Engineering
 02600 Jejawi - Perlis
 MALAYSIA"
-bf9f26780d7207c8845d7787b6003a8df161afb8,Counting People With Low-Level Features and Bayesian Regression,"Counting People With Low-Level Features
-nd Bayesian Regression
-Antoni B. Chan, Member, IEEE, and Nuno Vasconcelos, Senior Member, IEEE"
 bff354d05823c83215183c8824faefbc093de011,A new efficient SVM and its application to real-time accurate eye localization,"Proceedings of International Joint Conference on Neural Networks, San Jose, California, USA, July 31 – August 5, 2011
 A New Efﬁcient SVM and Its Application to
 Real-time Accurate Eye Localization
@@ -46610,10 +39629,6 @@ Dissertation Committee:
 Professor Amit K. Roy-Chowdhury, Chairperson
 Professor Anastasios Mourikis
 Professor Walid Najjar"
-bfdcd4d5cc10c8c64743fc7be7e7ad6709d93b53,Evaluation of PCA and LDA techniques for Face recognition using ORL face database,"Evaluation of PCA and LDA techniques for Face
-recognition using ORL face database
-CSE Dept. Faculty of Engineering, Avinashilingam University, Coimbatore, India
-M.Saraswathi, Dr. S. Sivakumari"
 bf1e0279a13903e1d43f8562aaf41444afca4fdc,Different Viewpoints of Recognizing Fleeting Facial Expressions with DWT,"International Research Journal of Engineering and Technology (IRJET)       e-ISSN: 2395-0056
 Volume: 04 Issue: 10 | Oct -2017                     www.irjet.net                                                                 p-ISSN: 2395-0072
 Different Viewpoints of Recognizing Fleeting Facial Expressions with
@@ -46632,9 +39647,6 @@ bf9d47987943e8c763ea42fbfd4b71c08ffda266,LECTURE ATTENDANCE SYSTEM WITH FACE REC
 IJARSE, Vol. No.2, Issue No.3, March, 2013                                                       ISSN-2319-8354(E)
 LECTURE ATTENDANCE SYSTEM WITH FACE RECOGNITION
 AND IMAGE PROCESSING"
-bf5940d57f97ed20c50278a81e901ae4656f0f2c,Query-Free Clothing Retrieval via Implicit Relevance Feedback,"Query-free Clothing Retrieval via Implicit
-Relevance Feedback
-Zhuoxiang Chen, Zhe Xu, Ya Zhang, Member, IEEE, and Xiao Gu"
 bf4f76c3da8a46783dfd2b72651e2300901ced25,Robust aggregation of GWAP tracks for local image annotation,"Robust aggregation of GWAP tracks
 for local image annotation
 C. Bernaschina, P. Fraternali, L. Galli, D. Martinenghi, M. Tagliasacchi
@@ -46645,38 +39657,10 @@ Richard Chen1, Faisal Mahmood2, Alan Yuille1 and Nicholas J. Durr2
 Department of Computer Science 2Department of Biomedical Engineering
 Johns Hopkins University, Baltimore, MD
 {rchen40, faisalm, ayuille,"
-bfebba8356c5d20dc6a9b2f72ff66adaf63321b7,End-to-end pedestrian collision warning system based on a convolutional neural network with semantic segmentation,"End-to-End Pedestrian Collision Warning System
-ased on a Convolutional Neural Network
-with Semantic Segmentation
-Heechul Jung
-DGIST
-Daegu, Republic of Korea
-Min-Kook Choi
-DGIST
-Daegu, Republic of Korea
-Kwon Soon
-DGIST
-Daegu, Republic of Korea
-Woo Young Jung
-DGIST
-Daegu, Republic of Korea"
 bfa763e7cec812f855c712895fa48eae89a34a00,Face Retrieval using Frequency Decoded Local Descriptor,"PREPRINT: ACCEPTED IN MULTIMEDIA TOOLS AND APPLICATIONS, SPRINGER
 Face Retrieval using Frequency Decoded Local
 Descriptor
 Shiv Ram Dubey"
-bfd8bfce7c998a7bf209b7bf2e6c2e1f03c4334e,Discriminative Face Alignment,"Discriminative Face Alignment
-Xiaoming Liu, Member, IEEE"
-bff77a3b80f40cefe79550bf9e220fb82a74c084,Facial Expression Recognition Based on Local Binary Patterns and Local Fisher Discriminant Analysis,"Facial Expression Recognition Based on Local Binary Patterns and
-Local Fisher Discriminant Analysis
-SHIQING ZHANG 1, XIAOMING ZHAO 2, BICHENG LEI 1
-School of Physics and Electronic Engineering
-Taizhou University
-Taizhou 318000
-CHINA
-2Department of Computer Science
-Taizhou University
-Taizhou 318000
-CHINA"
 bf86c65a4a3d81ca422600fdbc5d31eb56e098b9,Fusion Algorithms for Face Localization,"Algorithms Fusion for Face
 Localization
 R. BELAROUSSI
@@ -46721,26 +39705,6 @@ Federica Battisti, Marco Carli, Giovanna Farinella, Alessandro Neri
 Applied Electronics Department
 Universit(cid:19)a degli Studi Roma TRE
 Rome, Italy"
-bfffcd2818a1679ac7494af63f864652d87ef8fa,Neural Importance Sampling,"Neural Importance Sampling
-THOMAS MÜLLER, Disney Research & ETH Zürich
-BRIAN MCWILLIAMS, Disney Research
-FABRICE ROUSSELLE, Disney Research
-MARKUS GROSS, Disney Research & ETH Zürich
-JAN NOVÁK, Disney Research
-We propose to use deep neural networks for generating samples in Monte
-Carlo integration. Our work is based on non-linear independent compo-
-nents estimation (NICE), which we extend in numerous ways to improve
-performance and enable its application to integration problems. First, we
-introduce piecewise-polynomial coupling transforms that greatly increase
-the modeling power of individual coupling layers. Second, we propose to
-preprocess the inputs of neural networks using one-blob encoding, which
-stimulates localization of computation and improves inference. Third, we de-
-rive a gradient-descent-based optimization for the KL and the χ 2 divergence
-for the specific application of Monte Carlo integration with unnormalized
-stochastic estimates of the target distribution. Our approach enables fast and
-ccurate inference and efficient sample generation independently of the di-
-mensionality of the integration domain. We show its benefits on generating
-natural images and in two applications to light-transport simulation: first,"
 bf8bcda2e4d04b6bd6f5e70622e972baf525a1c7,Three decades of Cognition & Emotion: A brief review of past highlights and future prospects.,"COGNITION AND EMOTION, 2018
 VOL. 32, NO. 1, 1–12
 https://doi.org/10.1080/02699931.2018.1418197
@@ -46751,9 +39715,6 @@ Amsterdam, the Netherlands"
 bfa6ad4d71008505729274d008a9b4a7d92b2985,Semantic Understanding of Scenes Through the ADE20K Dataset,"Semantic Understanding of Scenes through the ADE20K Dataset
 Bolei Zhou · Hang Zhao · Xavier Puig · Tete Xiao · Sanja Fidler · Adela
 Barriuso · Antonio Torralba"
-bff9d100e99dd6a99ec26ca867694075b1dcac92,Passive Multimodal 2-D+3-D Face Recognition Using Gabor Features and Landmark Distances,"Passive Multimodal 2-D+3-D Face Recognition
-Using Gabor Features and Landmark Distances
-Sina Jahanbin, Member, IEEE, Hyohoon Choi, Member, IEEE, and Alan C. Bovik, Fellow, IEEE"
 bf39babab5648ff64cc4b79bfec96e8c6c93b812,The Impact of Disappointment in Decision Making: Inter-Individual Differences and Electrical Neuroimaging,"(cid:65)(cid:114)(cid:116)(cid:105)(cid:99)(cid:108)(cid:101)
 (cid:84)(cid:104)(cid:101)(cid:32)(cid:73)(cid:109)(cid:112)(cid:97)(cid:99)(cid:116)(cid:32)(cid:111)(cid:102)(cid:32)(cid:68)(cid:105)(cid:115)(cid:97)(cid:112)(cid:112)(cid:111)(cid:105)(cid:110)(cid:116)(cid:109)(cid:101)(cid:110)(cid:116)(cid:32)(cid:105)(cid:110)(cid:32)(cid:68)(cid:101)(cid:99)(cid:105)(cid:115)(cid:105)(cid:111)(cid:110)(cid:32)(cid:77)(cid:97)(cid:107)(cid:105)(cid:110)(cid:103)(cid:58)(cid:32)(cid:73)(cid:110)(cid:116)(cid:101)(cid:114)(cid:45)(cid:73)(cid:110)(cid:100)(cid:105)(cid:118)(cid:105)(cid:100)(cid:117)(cid:97)(cid:108)
 (cid:68)(cid:105)(cid:102)(cid:102)(cid:101)(cid:114)(cid:101)(cid:110)(cid:99)(cid:101)(cid:115)(cid:32)(cid:97)(cid:110)(cid:100)(cid:32)(cid:69)(cid:108)(cid:101)(cid:99)(cid:116)(cid:114)(cid:105)(cid:99)(cid:97)(cid:108)(cid:32)(cid:78)(cid:101)(cid:117)(cid:114)(cid:111)(cid:105)(cid:109)(cid:97)(cid:103)(cid:105)(cid:110)(cid:103)
@@ -46761,24 +39722,6 @@ bf39babab5648ff64cc4b79bfec96e8c6c93b812,The Impact of Disappointment in Decisio
 bf05e710dae791f82cc639a09dbe5ec66fed2008,Generating Video Description using Sequence-to-sequence Model with Temporal Attention,"Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers,
 pages 44–52, Osaka, Japan, December 11-17 2016."
 bf4ec5068e6ff0b008a09f0c94bfaac290ae7d3b,Co-attention CNNs for Unsupervised Object Co-segmentation,Proceedings of the Twenty-Seventh International Joint Conference on Artiﬁcial Intelligence (IJCAI-18)
-bf735bb7557e73bc6f68853cba828b55bd163726,Fusion of Zernike Moments and SIFT Features for Improved Face Recognition,"International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT2012)
-Proceedings published in International Journal of Computer Applications® (IJCA)
-Fusion of Zernike Moments and SIFT Features for
-Improved Face Recognition
-Chandan Singh
-Professor
-Department of Computer
-Science, Punjabi University
-Patiala, India
-Ekta Walia
-Asst. Prof., Department of
-Computer Science, South
-Asian University, New Delhi,
-Neerja Mittal
-Asst. Prof., Department of
-CSE&IT, RBIEBT, Kharar,
-Distt. Mohali, India
-India"
 bf96a0f037e7472e4b6cb1dae192a5fedbbbd88a,Visual Listening In: Extracting Brand Image Portrayed on Social Media,"Visual Listening In: Extracting Brand Image
 Portrayed on Social Media
 Liu Liu
@@ -46891,26 +39834,6 @@ observation[2].
 The biometrics systems provide a more accurate and
 reliable user authentication method.
 Existing user authentication techniques include:"
-44442a26062c20dab7db4a9862349b598efca119,Modelling errors in a biometric re-identification system,"Modeling Errors in a Biometric Re-Identiﬁcation System
-B. DeCann and A. Ross
-We consider the problem of “re-identiﬁcation” where a biometric system answers the question “Has this person been encountered before?” without actually
-deducing the person’s identity. Such a system is vital in biometric surveillance applications and applicable to biometric de-duplication. In such a system, identiﬁers
-re created dynamically as and when the system encounters an input probe. Consequently, multiple probes of the same identity may be mistakenly assigned different
-identiﬁers, while probes from different identities may be mistakenly assigned the same identiﬁer. In this work, we describe a re-identiﬁcation system and develop
-terminology as well as mathematical expressions for prediction of matching errors. Further, we demonstrate that the sequential order in which the probes are
-encountered by the system has a great impact on its matching performance. Experimental analysis based on unimodal and multimodal face and ﬁngerprint scores
-onﬁrms the validity of the designed error prediction model, as well as demonstrates that traditional metrics for biometric recognition fail to accurately characterize
-the error dynamics of a re-identiﬁcation system.
-Introduction: In a classical biometric system [1], the input probe (query) biometric data is compared against the reference samples (templates) residing
-in the reference database (gallery). Each sample in the reference database is assigned a label, which acts as an identiﬁer (e.g., user-id, name, etc.) that
-relates the reference sample to a speciﬁc individual and therefore, the comparison process enables the system to either determine the individual associated
-with the input data (referred to as identiﬁcation or 1:N matching) or verify whether the input biometric data corresponds to a speciﬁc person (referred
-to as veriﬁcation or 1:1 matching). Labels are assigned to a reference sample during an enrollment phase, when the biometric data of an individual is
-cquired and stored in the reference database. The identiﬁer may be further associated with additional biographic data (e.g., legal name, ID number) to
-link the identiﬁer to an identity.1 Thus, the identiﬁcation and veriﬁcation problems address the question: “Who is this person?” or “Is this person who
-they claim to be?”, respectively.
-In this work, we examine a variant of the classical biometric identiﬁcation system, wherein probe data is input into the system from sensors at
-multiple locations. The objective of the system is to deduce: “Has this person been encountered before?”. A biometric system performing such duties"
 44e3d382ce8d765f705706d40716cb81575281e8,Automatic Parameter Adaptation for Multi-object Tracking,"Automatic Parameter Adaptation for
 Multi-Object Tracking
 Duc Phu CHAU, Monique THONNAT, and Fran¸cois BREMOND
@@ -46960,10 +39883,6 @@ Pedestrian Detectors
 Artur Jord˜ao, Jessica Sena de Souza, William Robson Schwartz
 Smart Surveillance Interest Group, Computer Science Department
 Universidade Federal de Minas Gerais, Minas Gerais, Brazil"
-44dd150b9020b2253107b4a4af3644f0a51718a3,An Analysis of the Sensitivity of Active Shape Models to Initialization When Applied to Automatic Facial Landmarking,"An Analysis of the Sensitivity of Active Shape
-Models to Initialization when Applied to Automatic
-Facial Landmarking
-Keshav Seshadri, Student Member, IEEE and Marios Savvides, Member, IEEE"
 44703dea094eb9558965db9439a07b9a74fd36b5,"Multiculturalism, Colorblindness, and Prejudice: Examining How Diversity Ideologies Impact Intergroup Attitudes","University of Arkansas, Fayetteville
 Theses and Dissertations
 8-2018
@@ -47023,11 +39942,6 @@ Received: 17 November 2008 / Revised: 20 February 2009 / Accepted: 7 July 2009
 © Springer-Verlag London Limited 2009"
 446dc1413e1cfaee0030dc74a3cee49a47386355,Recent Advances in Zero-shot Recognition,"Recent Advances in Zero-shot Recognition
 Yanwei Fu, Tao Xiang, Yu-Gang Jiang, Xiangyang Xue, Leonid Sigal, and Shaogang Gong"
-4421790b8f6b7d44915e030dfec6ececc0f03c2e,Pedestrian Detection in Infrared Video Images,"Pedestrian Detection in Infrared Video Images
-Di Wu 1,2, a *, Wei Liu1,b
-Xi’an Institute of Optics and Precision Mechanics of CAS,Xi ’an 710119,China
-The University of Chinese Academy of Sciences, Beijing 100049, China
-Keywords: pedestrian detection;infrared video images;background subtraction;simple features."
 4461a1b70e461ec298d7066ba103deda48d4ba22,Classification via Minimum Incremental Coding Length,"Vol. 2, No. 2, pp. 367–395
 (cid:2) 2009 Society for Industrial and Applied Mathematics
 Classiﬁcation via Minimum Incremental Coding Length
@@ -47141,11 +40055,6 @@ resale or redistribution to servers or lists, or to reuse any
 opyrighted component of this work in other works must be
 obtained from the IEEE."
 38d56ddcea01ce99902dd75ad162213cbe4eaab7,Sense Beauty by Label Distribution Learning,Proceedings of the Twenty-Sixth International Joint Conference on Artiﬁcial Intelligence (IJCAI-17)
-38b3cae6ba1b98d6bc6f88d903916dac888cb951,Improving Semantic Embedding Consistency by Metric Learning for Zero-Shot Classification,"Improving Semantic Embedding Consistency by
-Metric Learning for Zero-Shot Classiﬁcation
-Maxime Bucher1,2, St´ephane Herbin1, Fr´ed´eric Jurie2
-ONERA - The French Aerospace Lab, Palaiseau, France
-Normandie Univ, UNICAEN, ENSICAEN, CNRS"
 38a3611138388490c2cd60dfbf795932d5e55a79,2 D pose estimation in the Restaurant of the Future,"D pose estimation in the Restaurant
 of the Future
 Frederik (Frank) Evers
@@ -47170,32 +40079,6 @@ Supervisor: Mgr. Jan Šochman, Ph.D.
 Field of study: Open Informatics
 Subﬁeld: Computer Vision and Image Processing
 May 2017"
-3832a6d6b1f78cdadee6968d51c1c7c2922ab3cd,ISIA at the ImageCLEF 2017 Image Caption Task,"ISIA at the ImageCLEF 2017 Image Caption Task
-Sisi Liang, Xiangyang Li, Yongqing Zhu, Xue Li, and Shuqiang Jiang
-Key Laboratory of Intelligent Information Processing,
-Institute of Computing Technology Chinese Academy of Sciences,
-No.6 Kexueyuan South Road Zhongguancun, Haidian District, 100190 Beijing, China
-{sisi.liang, xiangyang.li, yongqing.zhu, xue.li,"
-3885cfd634c025c6e27c4db8211d72f54f864f90,Implications of holistic face processing in autism and schizophrenia,"Implications of holistic face processing in autism and
-schizophrenia
-Tamara L. Watson*
-School of Social Science and Psychology, University of Western Sydney, Sydney, NSW, Australia
-REVIEW ARTICLE
-published: 05 July 2013
-doi: 10.3389/fpsyg.2013.00414
-People with autism and schizophrenia have been shown to have a local bias in sensory
-processing and face recognition difﬁculties. A global or holistic processing strategy is
-known to be important when recognizing faces. Studies investigating face recognition in
-these populations are reviewed and show that holistic processing is employed despite
-lower overall performance in the tasks used. This implies that holistic processing is
-necessary but not sufﬁcient for optimal face recognition and new avenues for research
-into face recognition based on network models of autism and schizophrenia are proposed.
-Keywords: vision, face recognition, autism, schizophrenia, holistic coding, conﬁgurational coding
-Edited by:
-Rachel A. Robbins, Univeristy of
-Western Sydney, Australia
-Reviewed by:
-Olivia Carter, University of"
 382f1ebe6009e580949d5513bc298cb253a1eeda,Interpreting Complex Regression Models,"Interpreting Complex Regression Models
 Noa Avigdor-Elgrabli∗, Alex Libov†, Michael Viderman∗, Ran Wolff∗
 Yahoo Research, Haifa, Israel,
@@ -47215,22 +40098,6 @@ Chen Huang, Yining Li, Chen Change Loy, Senior Member, IEEE and Xiaoou Tang, Fel
 386a5c06d334d20227e8b2daf5433a2bef385648,Cross and Learn: Cross-Modal Self-Supervision,"Cross and Learn: Cross-Modal Self-Supervision
 Nawid Sayed1, Biagio Brattoli2, and Bj¨orn Ommer2
 Heidelberg University, HCI / IWR, Germany"
-38ddeb190590b5758eb03924917a5874dbbd3731,A New Multimodal Database for Performance Evaluation in System Level,"A New Multimodal Database for Performance Evaluation in
-System Level
-Mi-young Cho1∗, Young-Sook Jeong1, Hyun-suh Kim2, and Howard Kim2
-Electronics and Telecommunications Research Institute, Daejeon, Korea
-{mycho,
-Color Technology Laboratory, Suwon, Korea
-{hyun,"
-384908bfad5b9e81d605344abcb9e99d8b0f4027,Improving Deep Models of Person Re-identification for Cross-Dataset Usage,"Improving Deep Models of Person Re-identification for
-Cross-Dataset Usage
-Sergey Rodionov1,2, Alexey Potapov1,3, Hugo Latapie4, Enzo Fenoglio4,
-Maxim Peterson2,3
-SingularityNET LLC
-Novamente LLC, USA
-ITMO University, Kronverkskiy pr. 49, 197101 St. Petersburg, Russia
-Chief Technology & Architecture Office, Cisco
-{pas.aicv, astroseger, {hlatapie,"
 3805d47da61527137b6f44b92af3017a2dfe7bd5,Greedy column subset selection for large-scale data sets,"(will be inserted by the editor)
 Greedy Column Subset Selection for Large-scale
 Data Sets
@@ -47240,10 +40107,6 @@ Received: date / Accepted: date"
 380b8df0f340e5bbc3a953c62f9bc573ce073b92,Joint Image-Text News Topic Detection and Tracking by Multimodal Topic And-Or Graph,"Joint Image-Text News Topic Detection and
 Tracking by Multimodal Topic And-Or Graph
 Weixin Li, Jungseock Joo, Hang Qi, and Song-Chun Zhu"
-3859dd21b6373bb4b237ddcebf4dc8acacb587e0,Multimodal Face Recognition using Hybrid Correlation Filters,"Multimodal Face Recognition using Hybrid Correlation Filters
-Electrical Engineering Department, Indian Institute of Technology Roorkee, India
-Anamika Dubey, Abhishek Sharma
-{ana.iitr,"
 38a169b6e67ef7768f91fa208c9b5544f6f57f16,Object Bank: An Object-Level Image Representation for High-Level Visual Recognition,"Int J Comput Vis
 DOI 10.1007/s11263-013-0660-x
 Object Bank: An Object-Level Image Representation
@@ -47251,26 +40114,6 @@ for High-Level Visual Recognition
 Li-Jia Li · Hao Su · Yongwhan Lim · Li Fei-Fei
 Received: 2 January 2012 / Accepted: 11 September 2013
 © Springer Science+Business Media New York 2013"
-38f7f3c72e582e116f6f079ec9ae738894785b96,A New Technique for Face Matching after Plastic Surgery in Forensics,"IJARCCE
-ISSN (Online) 2278-1021
-ISSN (Print) 2319 5940
-International Journal of Advanced Research in Computer and Communication Engineering
-Vol. 4, Issue 11, November 2015
-A New Technique for Face Matching after
-Plastic Surgery in Forensics
-Anju Joseph1, Nilu Tressa Thomas2, Neethu C. Sekhar3
-Student, Dept. of CSE, Amal Jyothi College of Engineering, Kanjirappally, India 1,2
-Asst. Professor, Dept. of CSE, Amal Jyothi College of Engineering, Kanjirappally, India 3
-I.  INTRODUCTION
-Facial  recognition  is  one  of  the  most  important    task  that
-forensic  examiners  execute
-their
-investigation. This work focuses on analysing the effect of
-plastic  surgery  in  face  recognition  algorithms.  It  is
-imperative for the subsequent facial recognition systems to
-e  capable  of  addressing  this  significant  issue  and
-ccordingly  there  is  a  need  for  more  research  in  this
-important area."
 38b18585e4bdb78347d44caa561e69a0045ade8d,Differential Attention for Visual Question Answering,"Differential Attention for Visual Question Answering
 Badri Patro, Vinay P. Namboodiri
 IIT Kanpur
@@ -47335,15 +40178,6 @@ Department of Computer Science, University of California, Irvine"
 38f56240c642677f2245aebe94fb846988487570,Mining patterns of orientations and magnitudes for face recognition,"Mining patterns of orientations and magnitudes for face recognition
 Ngoc-Son Vu, Alice Caplier
 Gipsa-lab, Grenoble Institute of Technology"
-38682c7b19831e5d4f58e9bce9716f9c2c29c4e7,Movie Character Identification Using Graph Matching Algorithm,"International Journal of Computer Trends and Technology (IJCTT) – Volume 18 Number 5 – Dec 2014
-Movie Character Identification Using Graph Matching
-Algorithm
-Shaik. Kartheek.*1, A.Srinivasa Reddy*2
-M.Tech Scholar, Dept of CSE, QISCET, ONGOLE, Dist: Prakasam, AP, India.
-Associate Professor, Department of CSE, QISCET, ONGOLE, Dist: Prakasam, AP, India"
-383a58de852715c8544abe60fa64d29fb7ea5688,Inductive Hashing on Manifolds,"Inductive Hashing on Manifolds
-Fumin Shen‡(cid:5)∗ Chunhua Shen(cid:5)† Qinfeng Shi(cid:5) Anton van den Hengel(cid:5) Zhenmin Tang‡
-(cid:5) The University of Adelaide, Australia ‡ Nanjing University of Science and Technology, China"
 3810b6299140bf2c7d6d0cced765c0777d603923,Do deep features generalize from everyday objects to remote sensing and aerial scenes domains?,"Do Deep Features Generalize from Everyday Objects
 to Remote Sensing and Aerial Scenes Domains?
 Ot´avio A. B. Penatti
@@ -47419,18 +40253,6 @@ d0e20aa3d61b77d17f005a1d24d7cf47600836ef,Rethinking Atrous Convolution for Seman
 Liang-Chieh Chen George Papandreou Florian Schroff Hartwig Adam
 {lcchen, gpapan, fschroff,
 Google Inc."
-d04631e40b237ae29cb8d2bd187b04033580e63b,Multi-cue Based Multi-target Tracking with Boosted MHT,"Multi-cue Based Multi-target Tracking
-with Boosted MHT
-Long Ying1,2, Tianzhu Zhang1,2, Shengsheng Qian1,2, and Changsheng Xu1,2
-Institute of Automation, Chinese Academy of Science, Beijing, China
-China-Singapore Institute of Digital Media, Singapore"
-d014011b24c62d5b689c782c09b89c52970f46e7,"SRDA: Generating Instance Segmentation Annotation via Scanning, Reasoning and Domain Adaptation","SRDA: Generating Instance Segmentation
-Annotation Via Scanning, Reasoning And
-Domain Adaptation
-Wenqiang Xu(cid:63), Yonglu Li(cid:63), Cewu Lu
-Department of Computer Science and Engineering,
-Shanghai Jiaotong University
-{vinjohn,yonglu"
 d0a9bbd3bd9dcb62f9874fc1378a7f1a17f44563,Prototype Generation Using Self-Organizing Maps for Informativeness-Based Classifier,"Hindawi
 Computational Intelligence and Neuroscience
 Volume 2017, Article ID 4263064, 15 pages
@@ -47451,22 +40273,6 @@ original work is properly cited.
 The 𝑘 nearest neighbor is one of the most important and simple procedures for data classification task. The 𝑘NN, as it is called,
 requires only two parameters: the number of𝑘 and a similarity measure. However, the algorithm has some weaknesses that make it
 nalysis and all training dataset is necessary. Another weakness is the optimal choice of 𝑘 parameter when the object analyzed"
-d04d53038d4267cf25badc5d6acccd2fc910a8a7,Online Multi-Object Tracking with Structural Invariance Constraint,"ZHOU, JIANG, WEI, DONG, WANG: ONLINE MULTI-OBJECT TRACKING WITH SIC
-Online Multi-Object Tracking
-with Structural Invariance Constraint
-Xiao Zhou
-Peilin Jiang
-Zhao Wei
-Hang Dong
-Fei Wang
-National Engineering
-Laboratory for Visual Information
-Processing and Application,
-XJTU, 99 Yanxiang Road,
-Xi’an, Shaanxi 710054, China
-School of Software Engineering,
-XJTU, 28 West Xianning Road,
-Xi’an, Shaanxi 710049, China"
 d01e65591745fc46a3f69a6c9387be17caf55c16,State-Driven Particle Filter for Multi-person Tracking,"State-Driven Particle Filter
 for Multi-Person Tracking
 David Gerónimo1, Frédéric Lerasle2,3, and Antonio M. López1
@@ -47493,13 +40299,6 @@ http://dx.doi.org/10.14257/ijsh.2015.9.1.11
 D Reconstruction
 Xu Yongzhe1 and Byungsoo Lee1
 Department of Computer Engineering, University of Incheon, Korea"
-d0441970a9f19751e6c047b364f580c30bf9754a,Pose-Aware Person Recognition,"Pose-Aware Person Recognition
-Vijay Kumar (cid:63)
-Anoop Namboodiri (cid:63)
-(cid:63) CVIT, IIIT Hyderabad, India
-Manohar Paluri †
-Facebook AI Research
-C. V. Jawahar (cid:63)"
 d00787e215bd74d32d80a6c115c4789214da5edb,Faster and Lighter Online Sparse Dictionary Learning Project report,"Faster and Lighter Online
 Sparse Dictionary Learning
 Project report
@@ -47518,10 +40317,6 @@ Received: 5 January 2018; Accepted: 1 February 2018; Published: 3 February 2018"
 d0a21f94de312a0ff31657fd103d6b29db823caa,Facial Expression Analysis,"Facial Expression Analysis
 Fernando De la Torre and Jeffrey F. Cohn"
 d0de92865a53576af3dd118f4d1fa73be12aee9b,PCANet-II: When PCANet Meets the Second Order Pooling,"PCANet-II:WhenPCANetMeetstheSecondOrderPoolingLeiTian,XiaopengHong"
-d08cc366a4a0192a01e9a7495af1eb5d9f9e73ae,A 3-D Audio-Visual Corpus of Affective Communication,"A 3-D Audio-Visual Corpus
-of Affective Communication
-Gabriele Fanelli, Juergen Gall, Harald Romsdorfer, Member, IEEE, Thibaut Weise, and
-Luc Van Gool, Member, IEEE"
 d07e9b04c1480d65e37e44bec3be95fc3206c17b,Combining classifiers for face recognition,- 130-7803-7965-9/03/$17.00 ©2003 IEEEICME 2003(cid:224)
 d02f45670fa6eb1fbac7ed7ed3eaa442579c73b2,Covariance Pooling for Facial Expression Recognition,"Covariance Pooling for Facial Expression Recognition
 Computer Vision Lab, ETH Zurich, Switzerland
@@ -47541,14 +40336,6 @@ Damien Muselet1 & Alain Tr´emeau 1 & Christian Wolf2
 Univ Lyon, UJM, CNRS, Lab Hubert Curien UMR5516, F-42000
 Universite de Lyon, CNRS, France, INSA-Lyon, LIRIS, UMR5205, F-69621"
 d05825a394f11a391c8815f6b0d394cdb4cfaa95,I2T2I: Learning text to image synthesis with textual data augmentation,
-d0b083befa0034bcd4a1349336fb30158157e6d8,A Semantic Distance Based Nearest Neighbor Method for Image Annotation,"A Semantic Distance Based Nearest Neighbor
-Method for Image Annotation
-Wei Wu and Guanglai Gao
-Computer Science Department, Inner Mongolia University, Hohhot, China
-Email: {cswuwei,
-Jianyun Nie
-Department IRO, University of Montreal, Canada
-Email:"
 d02c54192dbd0798b43231efe1159d6b4375ad36,3 D Reconstruction and Face Recognition Using Kernel-Based ICA and Neural Networks,"D Reconstruction and Face Recognition Using Kernel-Based
 ICA and Neural Networks
 Cheng-Jian Lin                  Ya-Tzu Huang
@@ -47650,9 +40437,6 @@ A Novel Characterization of the Alternative Hypothesis
 Using Kernel Discriminant Analysis for
 LLR-Based Speaker Verification
 Yi-Hsiang Chao∗+ , Hsin-Min Wang∗ and Ruei-Chuan Chang∗+"
-5f19b98e5cd22198d25660d609cbd3f4a69c94e7,Combining Head Pose and Eye Location Information for Gaze Estimation,"Combining Head Pose and Eye Location Information
-for Gaze Estimation
-Roberto Valenti, Member, IEEE, Nicu Sebe, Member, IEEE, and Theo Gevers, Member, IEEE"
 5fac23560b5ba4d45045f1edd837ed4bb6c1f5ca,Optimization of a Face Verification System using Bayesian Screening Techniques.,"OPTIMIZATION OF A FACE VERIFICATION SYSTEM
 USING BAYESIAN SCREENING TECHNIQUES
 Raquel Montes Diez, Cristina Conde, Ángel Serrano, Licesio J. Rodríguez-Aragón, Enrique Cabello
@@ -47663,21 +40447,6 @@ C/ Tulipán, s/n. Móstoles E-29833, Madrid, Spain
 {r.montes, cristina.conde, aserranos, ljrodriguez,
 http://frav.escet.urjc.es/
 the  150  most"
-5f871838710a6b408cf647aacb3b198983719c31,Locally Linear Regression for Pose-Invariant Face Recognition,"Locally Linear Regression for Pose-Invariant
-Face Recognition
-Xiujuan Chai, Shiguang Shan, Member, IEEE, Xilin Chen, Member, IEEE, and Wen Gao, Senior Member, IEEE"
-5f92de3683b4fee28ad3f431c889e7c8bff604f8,"Performance study of Face Recognition systems using LBP and ICA descriptors with sparse representation-MRLSR and KNN Classifiers , respectively","International Journal of Computer Trends and Technology (IJCTT) – Volume 42 Number 1 – December 2016
-Performance study of Face Recognition
-systems using LBP and ICA descriptors
-with sparse representation - MRLSR and
-KNN Classifiers, respectively
-K Sarath1 and G. Sreenivasulu2
-PG scholar, Department of Electronics and Communication Engineering, SVU College of Engineering,
-Professor, Department of Electronics and Communication Engineering, SVU College of Engineering,
-Tirupathi, India
-Tirupathi, India
-sparse
-representation"
 5f3a513351a75f4eb86dd57e1651e33691c62417,Gender Recognition via Face Area Analysis,
 5f0f8c9acc3e8eb50ca6e7d9c33cf3d9a8a54985,Structured Inhomogeneous Density Map Learning for Crowd Counting,"Structured Inhomogeneous Density Map Learning
 for Crowd Counting
@@ -47693,12 +40462,6 @@ FASTTEXT.ZIP:
 COMPRESSING TEXT CLASSIFICATION MODELS
 Armand Joulin, Edouard Grave, Piotr Bojanowski, Matthijs Douze, Herv´e J´egou & Tomas Mikolov
 Facebook AI Research"
-5f32ba9d85234f20203c31d2dca0793908f825a9,NEURAL NETWORK BASED SUPERVISED SELF,"International Journal on Soft Computing (IJSC) Vol.3, No.3, August 2012
-NEURAL NETWORK BASED SUPERVISED SELF
-ORGANIZING MAPS FOR FACE RECOGNITION
-A.S.Raja1 and V. JosephRaj2
-Research Scholar, Sathyabama University, Jeppiar Nagar, Chennai,Tamil Nadu, India
-Professor, Kamaraj College, Thoothukudi, Tamil Nadu, India"
 5f5906168235613c81ad2129e2431a0e5ef2b6e4,A Unified Framework for Compositional Fitting of Active Appearance Models,"Noname manuscript No.
 (will be inserted by the editor)
 A Uniﬁed Framework for Compositional Fitting of
@@ -47748,31 +40511,6 @@ Issue
 Pages"
 5fc621cdef59c38ef898a2adc2b4472a8396119a,Elephant Panda Lion Dolphin Dog Monkey ... ... Classes Elephant Dolphin Lion Classifier Training Data Synthesizing,"Synthesizing Samples for Zero-shot Learning
 IJCAI Anonymous Submission 2625"
-5fc371760fd4c8abe94b91ae2ca03d428ac05faa,Fear-Speci fi c Amygdala Function in Children and Adolescents on the Fragile X Spectrum : A Dosage Response of the FMR 1 Gene,"Cerebral Cortex Advance Access published November 11, 2012
-Cerebral Cortex
-doi:10.1093/cercor/bhs341
-Fear-Speciﬁc Amygdala Function in Children and Adolescents on the Fragile X Spectrum:
-A Dosage Response of the FMR1 Gene
-So-Yeon Kim1, Jessica Burris1, Frederick Bassal1, Kami Koldewyn5, Sumantra Chattarji6, Flora Tassone2, David Hessl2,3 and
-Susan M. Rivera1,2,4
-Center for Mind and Brain, University of California, Davis, CA 95618, USA, 2MIND Institute, University of California, Davis, CA
-95817, USA, 3Department of Psychiatry and Behavioral Sciences, University of California, Davis, CA 95817, USA, 4Department of
-Psychology, University of California, Davis, CA 95616, USA, 5McGovern Institute for Brain Research, MIT, MA 02139, USA and
-6National Center for Biological Sciences, Bangalore 560065, India
-Address correspondence to Susan M. Rivera, Center for Mind and Brain, University of California, Davis, 267 Cousteau Place, Davis, CA 95618,
-USA. Email:
-Mutations of the fragile X mental retardation 1 (FMR1) gene are the
-genetic cause of fragile X syndrome (FXS). The presence of signiﬁ-
-ant socioemotional problems has been well documented in FXS
-lthough the brain basis of those deﬁcits remains unspeciﬁed. Here,
-we investigated amygdala dysfunction and its relation to socioemo-
-tional deﬁcits and FMR1 gene expression in children and adoles-
-ents on the FX spectrum (i.e., individuals whose trinucleotide CGG"
-5f7a5ba79ad2c4aa7762470a3c7b59001e2f0de0,Part-Level Convolutional Neural Networks for Pedestrian Detection Using Saliency and Boundary Box Alignment,"Part-Level Convolutional Neural Networks for
-Pedestrian Detection Using Saliency and Boundary
-Box Alignment
-Inyong Yun, Cheolkon Jung, Member, IEEE, Xinran Wang, Alfred O Hero, Fellow, IEEE, and Joongkyu
-Kim, Member, IEEE"
 5f96af88dfef2bff4ed8a49ceca909efb701d1d5,Addressing the Dark Side of Vision Research: Storage,"Addressing the Dark Side of Vision Research: Storage
 Vishakha Gupta-Cledat
 Intel Labs
@@ -47780,16 +40518,6 @@ Luis Remis
 Intel Labs
 Christina R. Strong
 Intel Labs"
-5fb5d9389e2a2a4302c81bcfc068a4c8d4efe70c,Multiple Facial Attributes Estimation Based on Weighted Heterogeneous Learning,"Multiple Facial Attributes Estimation based on
-Weighted Heterogeneous Learning
-H.Fukui* T.Yamashita* Y.Kato* R.Matsui*
-T. Ogata** Y.Yamauchi* H.Fujiyoshi*
-*Chubu University
-**Abeja Inc.
-200, Matuoto-cho, Kasugai,
--1-20, Toranomon, Minato-ku,
-Aichi, Japan
-Tokyo, Japan"
 5fc664202208aaf01c9b62da5dfdcd71fdadab29,Automatic Face Recognition from Video,rXiv:1504.05308v1  [cs.CV]  21 Apr 2015
 5f58bf2c25826cb6ee927a1461aa72bd623157ff,Tasting Families of Features for Image Classification,"ICCV 2011 Submission #549. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE.
 Tasting Families of Features for Image Classiﬁcation
@@ -47817,9 +40545,6 @@ UESTC
 Jian Cheng
 UESTC
 haijun"
-5f107c92dd1c3f294b53627a5de1c7c46d996994,Complex Eye Movement Pattern Biometrics: The Effects of Environment and Stimulus,"Complex Eye Movement Pattern Biometrics:
-The Effects of Environment and Stimulus
-Corey D. Holland, Student Member, IEEE and Oleg V. Komogortsev, Member, IEEE"
 5fa1724a79a9f7090c54925f6ac52f1697d6b570,The Development of Multimodal Lexical Resources,"Proceedings of the Workshop on Grammar and Lexicon: Interactions and Interfaces,
 pages 41–47, Osaka, Japan, December 11 2016."
 5fa587381a9e4308163b3a5395985f0375c3cf7d,Deep Extreme Cut: From Extreme Points to Object Segmentation,"Deep Extreme Cut: From Extreme Points to Object Segmentation
@@ -47830,61 +40555,14 @@ L. Van Gool
 Figure 1. Example results of DEXTR: The user provides the extreme clicks for an object, and the CNN produces the segmented masks."
 5f534bacc658f620a15b5647adecb0ea813286c8,Reliable object detection and segmentation using inpainting,"Reliable Object Detection and Segmentation using Inpainting
 Ji Hoon Joung, M. S. Ryoo, Sunglok Choi, and Sung-Rak Kim"
-5f0b7245bedfc984b327b8e144c3cba9d9b2a807,Morphological Primitive Patterns with Grain Components on LDP for Child and Adult Age Classification,"International Journal of Computer Applications (0975 – 8887)
-Volume 21– No.3, May 2011
-Morphological Primitive Patterns with Grain Components
-on LDP for Child and Adult Age Classification
-B.Sujatha
-Dr.V.Vijaya Kumar
-Associate Professor
-G.I.E.T, Rajahmundry
-Dean, Dept. of Comp. Sciences
-Head, SRRF-G.I.E.T
-JNTUK,Kakinada
-Andhra Pradesh, India
-Rajahmundry
-Andhra Pradesh, India
-M.Rama Bai
-Associate Professor
-M.G.I.T, JNTUH
-Hyderabad
-Andhra Pradesh, India"
-5fc15baee1383d502775fab8ee91d56f4875429c,Factorial Discriminant Analysis for 3 D Face Recognition System using SVM Classifier,"International Journal of Computer Applications (0975 – 8887)
-International Conference on Information and Communication Technologies (ICICT-2014)
-Factorial Discriminant Analysis for
-D Face Recognition System using SVM Classifier
-P. S. Hiremath
-Department of P. G. Studies and Research in
-Computer Science,
-Gulbarga University, Gulbarga-585106
-Karnataka, India
-turned"
 5fcde9236d654a0f92a76c1a3f07c0cad954985c,Personality-Dependent Referring Expression Generation,"Personality-dependent Referring Expression Generation
 Ivandr´e Paraboni, Danielle Sampaio Monteiro, and Alex Gwo Jen Lan
 University of S˜ao Paulo, School of Arts, Sciences and Humanities, S˜ao Paulo, Brazil"
-5ff64afd70434b12e043ff39a91271eab6391124,Building Extraction in Very High Resolution Remote Sensing Imagery Using Deep Learning and Guided Filters,"Article
-Building Extraction in Very High Resolution
-nd Guided Filters
-Yongyang Xu 1 ID , Liang Wu 1,2, Zhong Xie 1,2,* and Zhanlong Chen 1
-Department of Information Engineering, China University of Geosciences, Wuhan 430074, China;
-(Y.X.); (L.W.); (Z.C.)
-National Engineering Research Center of Geographic Information System, Wuhan 430074, China
-* Correspondence:
-Received: 19 December 2017; Accepted: 16 January 2018; Published: 19 January 2018"
 5f5164cf998a10d2bef37741adb562ab07fac413,A Comprehensive Study on Cross-View Gait Based Human Identification with Deep CNNs,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TPAMI.2016.2545669, IEEE
 Transactions on Pattern Analysis and Machine Intelligence
 A Comprehensive Study on Cross-View Gait Based
 Human Identiﬁcation with Deep CNNs
 Zifeng Wu, Yongzhen Huang, Liang Wang, Xiaogang Wang, and Tieniu Tan"
-5f7ae1e13c00bb58856374b9888f1ddf73c6865e,Gender classification using face image and voice,"IOSR Journal of Computer Engineering (IOSR-JCE)
-e-ISSN: 2278-0661,p-ISSN: 2278-8727, Volume 17, Issue 5, Ver. V (Sep. – Oct. 2015), PP 20-25
-www.iosrjournals.org
-Gender classification using face image and voice
-Dharamraj yadav1 Shashwat Shukla2 & Bramah Hazela2
-Dept.of Computer Science & Engineering  Amity School of Engineering & Technology Amity University,
-Lucknow campus, India
-Dept.of Computer Science & Engineering  Amity School of Engineering & Technology Amity University,
-Lucknow campus, India"
 d904f945c1506e7b51b19c99c632ef13f340ef4c,0 ° 15 ° 30 ° 45 ° 60 ° 75 ° 90 °,"A scalable 3D HOG model for fast object detection and viewpoint estimation
 Marco Pedersoli
 Tinne Tuytelaars
@@ -48010,16 +40688,6 @@ Department of Electronics & Communication Engineering, MNNIT, Allahabad"
 d929534024614e3153c986e55d758ea7471d3fff,How Not to Evaluate a Developmental System,"How Not to Evaluate a Developmental System
 Frederick Shic and Brian Scassellati"
 d9bc16dcbc13502389704e4a0bdd8ee7af618069,Learning pullback HMM distances for action recognition,Learning pullback HMM distances for action recognition
-d950af49c44bc5d9f4a5cc1634e606004790b1e5,Divide and Fuse: A Re-ranking Approach for Person Re-identification,"YU ET AL.: DIVIDE AND FUSE: A RE-RANKING APPROACH FOR PERSON RE-ID
-Divide and Fuse: A Re-ranking Approach for
-Person Re-identiﬁcation
-Huazhong University of Science and
-Technology
-Wuhan, China
-Rui Yu
-Zhichao Zhou
-Song Bai
-Xiang Bai ∗"
 d94b37958657aa703d8a3d02a66ee251b4c3f597,Learning deep features from body and parts for person re-identification in camera networks,"Zhang and Si EURASIP Journal on Wireless Communications and
 Networking  (2018) 2018:52
 https://doi.org/10.1186/s13638-018-1060-2
@@ -48071,17 +40739,6 @@ Carlos Herranz-Perdiguero1 and Roberto J. L´opez-Sastre1"
 d97e7799142e2c66b63fe63bc52632fdf305f313,Lanczos Vectors versus Singular Vectors for Effective Dimension Reduction,"Lanczos Vectors versus Singular Vectors for
 Effective Dimension Reduction
 Jie Chen and Yousef Saad"
-d9327b9621a97244d351b5b93e057f159f24a21e,Laplacian smoothing transform for face recognition,"SCIENCE CHINA
-Information Sciences
-. RESEARCH PAPERS .
-December 2010 Vol. 53 No. 12: 2415–2428
-doi: 10.1007/s11432-010-4099-1
-Laplacian smoothing transform for face recognition
-GU SuiCheng, TAN Ying
-& HE XinGui
-Key Laboratory of Machine Perception (MOE); Department of Machine Intelligence,
-School of Electronics Engineering and Computer Science; Peking University, Beijing 100871, China
-Received March 16, 2009; accepted April 1, 2010"
 d914c53cdf26acc64259d381fbd45c4e150633ee,Pedestrian Tracking in the Compressed Domain Using Thermal Images,"Pedestrian Tracking in the Compressed Domain
 Using Thermal Images
 Ichraf Lahouli1,2,3, Robby Haelterman1, Zied Chtourou2, Geert De Cubber1,
@@ -48117,34 +40774,6 @@ Kariapatti.
 Kariapatti.
 Mr.D.Prince Winston
 Aruppukottai."
-d9bfc8095bfa604d90e1cb8c878ab844c2f89464,Kinship through Imaging,"International Journal of Application or Innovation in Engineering & Management (IJAIEM)
-Web Site: www.ijaiem.org Email:
-ISSN 2319 - 4847
-Volume 03, Issue 09, September 2014
-Kinship through Imaging
-Chaitali Deshmukh1, Prof. S.D.Jondhale2
-¹Department of Computer Engineering, PG Student, SVIT, Chincholi, Nashik, University of Pune, India
-²Department of Computer Engineering, Professor, SVIT, Chincholi, Nashik , University of Pune, India"
-d9df2ed64494f54c0e2529f2c05a16423a57235c,A Novel Approach for Facial Expression Analysis in real time applications using SIFT flow and SVM 1,"Australian Journal of Basic and Applied Sciences, 9(21) Special 2015, Pages: 1-6
-ISSN:1991-8178
-Australian Journal of Basic and Applied Sciences
-Journal home page: www.ajbasweb.com
-A Novel Approach for Facial Expression Analysis in real time applications using SIFT
-flow and SVM
-K. Suganya Devi and 2P. Srinivasan
-Department of Computer Science and Engineering, University college of Engg Panruti, Panruti 607106, Tamilnadu, India
-Department of Physics, University college of Engg Panruti, Panruti 607106, Tamilnadu, India
-A R T I C L E   I N F O
-Article history:
-Article Received : 12 January 2015
-Revised: 1 May 2015
-Accepted:  8 May 2015
-Keywords:
-Expression  recognition,  Facial  region
-selection,  Facial  expression,  Sparse
-learning  technique,  Scale  Invariant
-Feature Transform flow, SVM
-A B S T R A C T"
 d930ec59b87004fd172721f6684963e00137745f,Face Pose Estimation using a Tree of Boosted Classifiers,"Face Pose Estimation using a
 Tree of Boosted Classifiers
 Javier Cruz Mota
@@ -48160,17 +40789,6 @@ Fraunhofer IOSB, Karlsruhe, Germany
 Karlsruhe Institute of Technology KIT, Vision and Fusion Lab, Karlsruhe, Germany
 Keywords:
 Instance Segmentation, Multi-Scale Analysis, Foveated Imaging, Cityscapes."
-d9318c7259e394b3060b424eb6feca0f71219179,Face Matching and Retrieval Using Soft Biometrics,"Face Matching and Retrieval Using Soft Biometrics
-Unsang Park, Member, IEEE, and Anil K. Jain, Fellow, IEEE"
-d9ef1a80738bbdd35655c320761f95ee609b8f49,A Research-Face Recognition by Using Near Set Theory,"Volume 5, Issue 4, 2015                                     ISSN: 2277 128X
-International Journal of Advanced Research in
-Computer Science and Software Engineering
-Research Paper
-Available online at: www.ijarcsse.com
-A Research - Face Recognition by Using Near Set Theory
-Manisha V. Borkar, Bhakti Kurhade
-Department of Computer Science and  Engineering
-Abha Gaikwad -Patil College of  Engineering, Nagpur, Maharashtra, India"
 9679d15c6699b521740408b2e899c03af89390ac,ARTICULATED BODY TRACKING AND HUMAN ACTION ANALYSIS,"DIMENSIONALITY REDUCTION FOR 3D
 ARTICULATED BODY TRACKING AND HUMAN
 ACTION ANALYSIS
@@ -48191,10 +40809,6 @@ eISSN 2092-805X
 Region-Based Facial Expression Recognition in
 Still Images
 Gawed M. Nagi*, Rahmita Rahmat*, Fatimah Khalid* and Muhamad Taufik*"
-96fc93175169b788acd98f0a676dffab00651cbc,On Matching Faces with Alterations due to Plastic Surgery and Disguise,"On Matching Faces with Alterations due to Plastic Surgery and Disguise
-Saksham Suri1, Anush Sankaran2, Mayank Vatsa1, Richa Singh1
-IIIT - Delhi, India 2IBM Research, Bengaluru, India
-{saksham15082, mayank,"
 96dfa2a7630fc6800ba8a546df526b8174f54b5c,Appearance-Based Facial Recognition Using Visible and Thermal Imagery : A Comparative Study ∗,"Appearance-Based Facial Recognition Using Visible and Thermal
 Imagery: A Comparative Study ∗
 Andrea Selinger†
@@ -48219,15 +40833,6 @@ Received: 11 November 2011 / Accepted: 11 May 2013 / Published online: 19 June 2
 Nisarg Raval, Ashwin Machanavajjhala, and Jerry Pan
 Olympus: Sensor Privacy through Utility Aware
 Obfuscation"
-9686dcf40e6fdc4152f38bd12b929bcd4f3bbbcc,Emotion Based Music Player,"International Journal of Engineering Research and General Science Volume 3, Issue 1,  January-February, 2015
-ISSN 2091-2730
-Emotion Based Music Player
-Hafeez Kabani1, Sharik Khan2, Omar Khan3, Shabana Tadvi4
-Department of Computer Science and Engineering
-Department of Computer Science and Engineering
-Department of Computer Science and Engineering
-Asst. Professor, Department of Computer Science and Engineering
-M.H Saboo Siddik College of Engineering, University of Mumbai, India"
 964e43f4983a42ef3790c265bdce42c1fce56d79,A virtual environment tool for benchmarking face analysis systems,"A Virtual Environment Tool for Benchmarking Face
 Analysis Systems
 Mauricio Correa+,*, Javier Ruiz-del-Solar+,*, Rodrigo Verschae*
@@ -48291,23 +40896,6 @@ CCS Concepts: •Computing methodologies →Scene understanding; Natural languag
 Additional Key Words and Phrases: saliency, visual saliency prediction, image captioning, deep learning."
 96f0da034d090a3ecadd0fb92333bb681f23ab14,Temporal-Spatial Mapping for Action Recognition,"Temporal-Spatial Mapping for Action Recognition
 Xiaolin Song, Cuiling Lan, Wenjun Zeng, Junliang Xing, Jingyu Yang, and Xiaoyan Sun"
-9630109529870d142fde01341da05967484e906c,Techniques of Facial Synthesis : A Comprehensive Literature Review,"International Journal of Computer Applications (0975 – 8887)
-Volume 61– No.10, January 2013
-Techniques of Facial Synthesis: A
-Comprehensive Literature Review
-Deepti Chandra
-Shri Shankaracharya College
-of Engg. & Technology,  Bhilai,
-Chhattisgarh, India
-Sanjeev  Karmakar
-Bhilai Institute of Technology (BIT)
-Chhattisgarh, Durg 491001, India
-Rajendra  Hegadi
-Pragati College of Engg. &
-Management
-Raipur,Chhattisgarh, India
-realism
--the  synthesized"
 96788880589a514c3ae9de29695c0127d6e76b8f,Attention-Based Multimodal Fusion for Video Description,"Attention-Based Multimodal Fusion for Video Description
 Chiori Hori
 Takaaki Hori
@@ -48337,29 +40925,6 @@ detection algorithm identifies potential scenes containing
 visitors. Using a neural-network-based face detector,1
 Argus extracts faces from these images. A memory-based
 face recognition system2 examines these faces and at-"
-96723b42451c42ec396381596490143aac8f85cd,A Computer Vision Approach for the Eye Accessing Cue Model Used in Neuro-linguistic Programming,"U.P.B. Sci. Bull., Series C, Vol. 75, Iss. 4, 2013                                                   ISSN 2286 – 3540
-A COMPUTER VISION APPROACH FOR THE EYE
-ACCESSING CUE MODEL USED IN NEURO-LINGUISTIC
-PROGRAMMING
-Ruxandra VRÂNCEANU1, Laura FLOREA2, Corneliu FLOREA3
-This paper investigates the Eye Accessing Cue (EAC) model used in Neuro-
-Linguistic Programming (NLP) and shows how image processing techniques can be
-used to improve the interpretation of this model. An experiment was carried out to
-validate the model by inducing certain eye cues using a set of questions. A simple
-nd  efficient  method  is  proposed  for  automatically  locating  the  eyes  and  the
-orrespondent  EAC.  The  relative  position  between  the  iris  and  the  sclera  is
-determined  using  a  fast  mechanism,  based  on  the  analysis  of  integral  projections
-inside the bounding box of the eye.
-Keywords: Neuro-Linguistic Programming, Eye Detection, Eye Gaze
-. Introduction
-The progress made in image processing and the increase of computational
-apabilities  of  machines  over  the  past  decades  has  led  to  new  opportunities  for
-human-computer  interactions  and  to  the  development  of  systems  capable  of
-utomatically  interpreting  the  facial  attributes  of  a  person.  Such  algorithms  are
-used  in  the  field  of  people  identification  and  description,  in  applications  that"
-96d6e0bf752c42ede0170e9b332ca390ac75cd1f,Temporal Hierarchical Dictionary with HMM for Fast Gesture Recognition,"018 24th International Conference on Pattern Recognition (ICPR)
-Beijing, China, August 20-24, 2018
-978-1-5386-3787-6/18/$31.00 ©2018 European Union"
 9606b1c88b891d433927b1f841dce44b8d3af066,Principal Component Analysis with Tensor Train Subspace,"Principal Component Analysis with Tensor Train
 Subspace
 Wenqi Wang, Vaneet Aggarwal, and Shuchin Aeron"
@@ -48389,10 +40954,6 @@ Misalignment
 Liansheng Zhuang · Tsung-Han Chan ·
 Allen Y. Yang · S. Shankar Sastry · Yi Ma
 Received: date / Accepted: date"
-9603b3a4649fd217752972909d627bde8e0a5023,Spectral Hashing With Semantically Consistent Graph for Image Indexing,"Spectral Hashing With Semantically
-Consistent Graph for Image Indexing
-Peng Li, Meng Wang, Member, IEEE, Jian Cheng, Member, IEEE, Changsheng Xu, Senior Member, IEEE, and
-Hanqing Lu, Senior Member, IEEE"
 a726858df7c9503116504206577a938df1a67815,Unsupervised Vehicle Re-Identification using Triplet Networks,"Unsupervised Vehicle Re-Identiﬁcation using Triplet Networks
 Pedro Antonio Mar´ın-Reyes
 Andrea Palazzi
@@ -48408,33 +40969,6 @@ University of Las Palmas de Gran Canaria
 University of Modena and Reggio Emilia"
 a7eee3222623778294461102d0dc770d4e09a7c5,A novel fusion-based method for expression-invariant gender classification,"978-1-4244-2354-5/09/$25.00 ©2009 IEEE
 ICASSP 2009"
-a758b744a6d6962f1ddce6f0d04292a0b5cf8e07,"Study on Human Face Recognition under Invariant Pose , Illumination and Expression using LBP , LoG and SVM","ISSN XXXX XXXX © 2017 IJESC
-Research Article                                                                                                                              Volume 7 Issue No.4
-Study on Human Face Recognition under Invariant Pose, Illumination
-nd Expression using LBP, LoG and SVM
-Amrutha
-Depart ment of Co mputer Science & Engineering
-Mangalore Institute of Technology & Engineering , Moodabidri, Mangalore, India
-INTRODUCTION
-RELATED WORK
-Abstrac t:
-Face  recognition  system  uses  human  face  for  the  identification  of  the   user.  Face  recognition  is  a  difficu lt  task  there  is  no  unique
-method  that  provide  accurate  an  accurate  and  effic ient  solution  in  all  the  situations  like  the  face  image  with  differen t  pose ,
-illu mination  and  exp ression.  Local  Binary  Pattern  (LBP)  and  Laplac ian  of  Gaussian  (Lo G)  operators.  Support  Vector  Machine
-lassifier  is  used  to  recognize  the  human  face.  The  Lo G  algorith m  is  used  to preprocess the  image  to  detect  the  edges of  the  face
-image to get the image information. The  LBP operator divides the face  image into several blocks to generate the features informat ion
-on  pixe l  level  by  creating  LBP  labels  for  all  the  blocks  of  image  is  obtained  by  concatenating  all  the  individual  local  histo grams.
-Support Vector Machine classifier  (SVM )  is used to classify t he image. The a lgorith m performances is verified under the constraints
-like illu mination, e xp ression and pose variation
-Ke ywor ds:  Face  Recognition,  Local  Binary  Pattern,  Laplac ian  of  Gaussian,  histogram,  illu mination,  pose  angle,  exp ression
-variations, SVM ."
-a7790555c65be0fc5b5de9bcb1dc550f4919ce3f,Literature Survey for Face Detection under Illumination Variation,"International Journal of Scientific Research Engineering & Technology (IJSRET)
-Volume 2 Issue 10   pp 659-664 January 2014
-www.ijsret.org            ISSN 2278 – 0882
-Literature Survey for Face Detection under Illumination Variation
-J.SHYNU, P.KANNAN
-PG Scholar Department of ECE, PET Engineering College, India
-Professor Department of ECE, PET Engineering College, India"
 a71106ef95103276fac010c10291f6dd6fd9d9f5,Social status level and dimension interactively influence person evaluations indexed by P300s.,"ISSN: 1747-0919 (Print) 1747-0927 (Online) Journal homepage: http://www.tandfonline.com/loi/psns20
 Social status level and dimension interactively
 influence person evaluations indexed by P300s
@@ -48471,15 +41005,6 @@ Sandra Ebert
 Dipl.-Inform.
 orn in Leipzig, Germany
 Saarbrücken, 2012"
-a775da3e6e6ea64bffab7f9baf665528644c7ed3,Human Face Pose Estimation based on Feature Extraction Points,"International Journal of Computer Applications (0975 – 8887)
-Volume 142 – No.9, May 2016
-Human Face Pose Estimation based on Feature
-Extraction Points
-Guneet Bhullar
-Research scholar,
-Department of ECE
-SBSSTC, Moga Road,
-Ferozepur, Punjab, India"
 a7e8ce268c16ea8c10e4c5ccd8d6e53702423faa,The Ciona17 Dataset for Semantic Segmentation of Invasive Species in a Marine Aquaculture Environment,"The Ciona17 Dataset for Semantic Segmentation
 of Invasive Species in a Marine Aquaculture Environment
 Angus Galloway∗, Graham W. Taylor∗, Aaron Ramsay†, Medhat Moussa∗
@@ -48493,15 +41018,6 @@ Montague, PEI, Canada"
 a7066c13ba21817abcf8ff955740493adf95b02c,Points2Pix: 3D Point-Cloud to Image Translation using conditional Generative Adversarial Networks,"Points2Pix: 3D Point-Cloud to Image Translation
 using conditional Generative Adversarial Networks
 Stefan Milz 1 * Martin Simon 1 * Kai Fischer 1 * Maximillian Poepperl 1"
-a703d51c200724517f099ee10885286ddbd8b587,Fuzzy neural networks(FNN)-based approach for personalized facial expression recognition with novel feature selection method,"Fuzzy Neural Networks(FNN)-based Approach for
-Personalized Facial Expression Recognition with
-Novel Feature Selection Method
-Dae-Jin Kim and Zeungnam Bien
-Div. of EE, Dept. of EECS, KAIST
-73-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Korea
-Kwang-Hyun Park
-Human-friendly Welfare Robotic System Engineering Research Center, KAIST
-73-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Korea"
 a7e78f80e0e37d0c17bc09058c27996e32e4454e,UNAM at SemEval-2018 Task 10: Unsupervised Semantic Discriminative Attribute Identification in Neural Word Embedding Cones,"Proceedings of the 12th International Workshop on Semantic Evaluation (SemEval-2018), pages 977–984
 New Orleans, Louisiana, June 5–6, 2018. ©2018 Association for Computational Linguistics"
 a76d471a409904c084746a56334453450f1c6c1a,Study of the Changing Trends in Facial Expression Recognition,"Study of the Changing Trends in Facial Expression Recognition
@@ -48514,12 +41030,6 @@ Authors:
 Dr. S. Ravi
 Mahima S
 10.5120/2509-3397"
-a77e9f0bd205a7733431a6d1028f09f57f9f73b0,Multimodal feature fusion for CNN-based gait recognition: an empirical comparison,"Multimodal feature fusion for CNN-based gait recognition: an
-empirical comparison
-F.M. Castroa,, M.J. Mar´ın-Jim´enezb, N. Guila, N. P´erez de la Blancac
-Department of Computer Architecture, University of Malaga, Spain, 29071
-Department of Computing and Numerical Analysis, University of Cordoba, Spain, 14071
-Department of Computer Science and Artiﬁcial Intelligence, University of Granada, Spain, 18071"
 a73a16203b644353a287a4759bc951450e67d700,BodyNet: Volumetric Inference of 3D Human Body Shapes,"BodyNet: Volumetric Inference of
 D Human Body Shapes
 G¨ul Varol1,*
@@ -48557,9 +41067,6 @@ ontribution has been peer-reviewed. The double-blind peer-review was conducted o
 a7bfb6426359140a0bc0c84741ad9a3ac83eff04,Object-Level Context Modeling For Scene Classification with Context-CNN,"Object-Level Context Modeling For Scene Classiﬁcation with Context-CNN
 Syed Ashar Javed1 and Anil Kumar Nelakanti2
 IIIT Hyderabad, 2Amazon"
-a7fe834a0af614ce6b50dc093132b031dd9a856b,Orientation Driven Bag of Appearances for Person Re-identification,"Orientation Driven Bag of Appearances for Person
-Re-identiﬁcation
-Liqian Ma, Hong Liu†, Member, IEEE, Liang Hu, Can Wang, Qianru Sun"
 a75db530b5a905c87aba6b65676809b35f9614f5,Dynamic Eye Gaze Tracking for Foveated Rendering and Retinal Blur,"Dynamic Eye Gaze Tracking for Foveated Rendering and Retinal Blur
 Kushagr Gupta, Suleman Kazi, Terry Kong"
 a73bc57fb0aa429ba5f7f12b6d02e2c6274cabdd,A Superior Tracking Approach: Building a Strong Tracker through Fusion,"A Superior Tracking Approach:
@@ -48583,10 +41090,6 @@ PortSaid University
 Mansoura University
 Zagazig University"
 a7664247a37a89c74d0e1a1606a99119cffc41d4,Modal Consistency based Pre-Trained Multi-Model Reuse,Proceedings of the Twenty-Sixth International Joint Conference on Artiﬁcial Intelligence (IJCAI-17)
-a77e0db38ed7ad95a3bca95fea72048985c54508,DART: Distribution Aware Retinal Transform for Event-based Cameras,"SUBMITTED TO IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
-DART: Distribution Aware Retinal Transform for
-Event-based Cameras
-Bharath Ramesh*, Hong Yang, Garrick Orchard, Ngoc Anh Le Thi, and Cheng Xiang, Member, IEEE"
 a70fa8af52e4cc32dae09e6e753f1dd3ec198327,Neural Task Representations as Weak Supervision for Model Agnostic Cross-Lingual Transfer,"Neural Task Representations as Weak Supervision for Model Agnostic
 Cross-Lingual Transfer
 Sujay Kumar Jauhar
@@ -48809,13 +41312,6 @@ output after calibration using our network. As shown, using the mis-calibrated p
 of the world results in an incoherent reconstruction. Notice how the 3D structures highlighted in (c) using red rectangles
 fail to project to their 2D counterparts. However, using the extrinsic calibration parameters predicted by CalibNet produces
 more consistent and accurate reconstructions (d), even for large initial mis-calibrations."
-5af5802cc6128bafbde1ae12e0ab41612aee9e3b,An object tracking method using extreme learning machine with online learning,"An Object Tracking Method Using Extreme
-Learning Machine with Online Learning
-Yuanlong Yu, Liyan Xie, and Zhiyong Huang
-College of Mathematics and Computer Science
-Fuzhou University
-Fuzhou, Fujian, 350116, China
-Emails: hzy"
 5a93f9084e59cb9730a498ff602a8c8703e5d8a5,Face Recognition using Local Quantized Patterns,"HUSSAIN ET. AL: FACE RECOGNITION USING LOCAL QUANTIZED PATTERNS
 Face Recognition using Local Quantized
 Patterns
@@ -48885,10 +41381,6 @@ Wenguan Wang, and Jianbing Shen, Senior Member, IEEE, and Ling Shao, Senior Memb
 5acfacbe8bf93ab1ee17bd6f65667abe0d6e1b5e,Where Should We Place LiDARs on the Autonomous Vehicle? - An Optimal Design Approach,"Where Should We Place LiDARs on the Autonomous Vehicle?
 - An Optimal Design Approach
 Zuxin Liu1 , Mansur Arief2 and Ding Zhao2,∗"
-5a7520380d9960ff3b4f5f0fe526a00f63791e99,The Indian Spontaneous Expression Database for Emotion Recognition,"The Indian Spontaneous Expression
-Database for Emotion Recognition
-S L Happy, Student Member, IEEE, Priyadarshi Patnaik, Aurobinda Routray, Member, IEEE,
-nd Rajlakshmi Guha"
 5ab9f00a707a55f4955b378981ad425aa1cb8ea3,Forecasting People Trajectories and Head Poses by Jointly Reasoning on Tracklets and Vislets,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. XX, NO. YY, NOVEMBER 2018
 Forecasting People Trajectories and Head Poses
 y Jointly Reasoning on Tracklets and Vislets
@@ -48923,9 +41415,6 @@ Parisutham Institute of Technology & Science
 Thanjavur.
 Affiliated to Anna university, Chennai
 recognition  can  be  used"
-5a34a9bb264a2594c02b5f46b038aa1ec3389072,Label-Embedding for Image Classification,"Label-Embedding for Image Classiﬁcation
-Zeynep Akata, Member, IEEE, Florent Perronnin, Member, IEEE, Zaid Harchaoui, Member, IEEE,
-nd Cordelia Schmid, Fellow, IEEE"
 185360fe1d024a3313042805ee201a75eac50131,Person De-Identification in Videos,"Person De-Identiﬁcation in Videos
 Prachi Agrawal and P. J. Narayanan"
 182df40034d937c74df0edb0acb295088e63f1ed,University of Michigan North Campus long-term vision and lidar dataset,"University of Michigan North Campus
@@ -49042,9 +41531,6 @@ left or right, i.e., I(cid:48)
 l and
 r are multiples of I(cid:48)
 I(cid:48)"
-1886b6d9c303135c5fbdc33e5f401e7fc4da6da4,Knowledge Guided Disambiguation for Large-Scale Scene Classification With Multi-Resolution CNNs,"Knowledge Guided Disambiguation for Large-Scale
-Scene Classiﬁcation with Multi-Resolution CNNs
-Limin Wang, Sheng Guo, Weilin Huang, Member, IEEE, Yuanjun Xiong, and Yu Qiao, Senior Member, IEEE"
 1819d9a9099dafc987dd236c2174945e7922be13,Eigenfeature Regularization and Extraction in Face Recognition,"Eigenfeature Regularization and Extraction
 in Face Recognition
 Xudong Jiang, Senior Member, IEEE, Bappaditya Mandal, and Alex Kot, Fellow, IEEE"
@@ -49097,10 +41583,6 @@ MIT Media Lab 75 Amherst St. Cambridge, MA 02139
 Timnit Gebru
 Microsoft Research 641 Avenue of the Americas, New York, NY 10011
 Editors: Sorelle A. Friedler and Christo Wilson"
-18c4a0e82fdddda2530b7281ad567abc0373a89f,Principal Coefficients Embedding: Theory and Algorithm,"IEEE TRANSACTIONS ON CYBERNETICS
-Automatic Subspace Learning via Principal
-Coefﬁcients Embedding
-Xi Peng, Jiwen Lu, Senior Member, IEEE, Zhang Yi, Fellow, IEEE and Rui Yan, Member, IEEE,"
 18d7684c6b96caf51adb519738720eceb1b13050,Hidden Relationships: Bayesian Estimation With Partial Knowledge,"Hidden Relationships:
 Bayesian Estimation with Partial Knowledge
 Tomer Michaeli and Yonina C. Eldar, Senior Member, IEEE
@@ -49132,9 +41614,6 @@ Dept. of Computer Science
 Autonomous University of Barcelona
 08193 Bellaterra, Barcelona, Spain
 {dvazquez, jiaolong, sramosp, antonio,"
-18727c3f4ada0cec9e5914340cc672d0554d7784,"3-D Face Detection, Landmark Localization, and Registration Using a Point Distribution Model","D face detection, landmark localization and
-registration using a Point Distribution Model
-Prathap Nair*, Student Member, IEEE, and Andrea Cavallaro, Member, IEEE"
 1806665f9571bbdcf654f3bdf5e009bcb8eac799,Markov random field terrain classification for autonomous robots in unstructured terrain,"Fachbereich 4: Informatik
 Arbeitsgruppe
 Aktives Sehen
@@ -49185,12 +41664,6 @@ Croatian Telecom, Savska 32, Zagreb, Croatia, e-mail:
 University of Zagreb, FER, Unska 3/XII, Zagreb, Croatia
 implementations
 in  all  possible  algorithm"
-18233c55982050292ba7f6a5462c0e7576c3398d,Face Recognition using Eye Distance and PCA Approaches,"Face Recognition using Eye Distance and PCA
-Approaches
-Ripal Patel , Nidhi Rathod , Ami Shah , Mayur Sevak
-Electronics & Telecommunication Department,
-BVM Engineering College.
-Vallabh Vidyanagar-388120, Gujarat, India"
 1885acea0d24e7b953485f78ec57b2f04e946eaf,Combining Local and Global Features for 3D Face Tracking,"Combining Local and Global Features for 3D Face Tracking
 Pengfei Xiong, Guoqing Li, Yuhang Sun
 Megvii (face++) Research
@@ -49207,19 +41680,6 @@ ISPGroup, ELEN Department, ICTEAM Institute
 Universit´e catholique de Louvain
 Louvain-la-Neuve, B-1348, Belgium
 {amit.kc,"
-18a4399b8afb460cbd4de2225f39ed23a95336d6,HMS-Net: Hierarchical Multi-scale Sparsity-invariant Network for Sparse Depth Completion,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015
-HMS-Net: Hierarchical Multi-scale
-Sparsity-invariant Network for Sparse Depth
-Completion
-Zixuan Huang, Junming Fan, Shuai Yi, Xiaogang Wang, Senior Member, IEEE,
-Hongsheng Li, Member, IEEE"
-18cd79f3c93b74d856bff6da92bfc87be1109f80,An Application to Human Face Photo-sketch Synthesis and Recognition,"International Journal of Advances in Engineering & Technology, May 2012.
-©IJAET                                                                                                          ISSN: 2231-1963
-AN APPLICATION TO HUMAN FACE PHOTO-SKETCH
-SYNTHESIS AND RECOGNITION
-Amit R. Sharma and 2Prakash. R. Devale
-Student and 2Professor & Head,
-Department of Information Tech., Bharti Vidyapeeth Deemed University, Pune, India"
 189fa973bc09cf3f3416e875fc853c3c489edeb0,Multimodal Trajectory Predictions for Autonomous Driving using Deep Convolutional Networks,"Multimodal Trajectory Predictions for Autonomous
 Driving using Deep Convolutional Networks
 Henggang Cui, Vladan Radosavljevic, Fang-Chieh Chou, Tsung-Han Lin,
@@ -49240,21 +41700,6 @@ Eva Cerezo • Isabelle Hupont • Sandra Baldassarri •
 Sergio Ballano
 Received: 3 February 2011 / Accepted: 24 September 2011 / Published online: 30 October 2011
 Ó Springer-Verlag 2011"
-18c72175ddbb7d5956d180b65a96005c100f6014,From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 23, NO. 6,
-JUNE 2001
-From Few to Many: Illumination Cone
-Models for Face Recognition under
-Variable Lighting and Pose
-Athinodoros S. Georghiades, Student Member, IEEE, Peter N. Belhumeur, Member, IEEE, and
-David J. Kriegman, Senior Member, IEEE"
-18aae0f20fdc6aab093c72c81005247d2cbc8512,Bayesian CP Factorization of Incomplete Tensors with Automatic Rank Determination,"Bayesian CP Factorization of Incomplete
-Tensors with Automatic Rank Determination
-Qibin Zhao, Member, IEEE, Liqing Zhang, Member, IEEE, and Andrzej Cichocki Fellow, IEEE"
-18001ed8ce46cf9df5574b1e360550ed9401cd76,Sentic blending: Scalable multimodal fusion for the continuous interpretation of semantics and sentics,"Sentic Blending:
-Scalable Multimodal Fusion for the Continuous
-Interpretation of Semantics and Sentics
-Erik Cambria, Member, IEEE, Newton Howard, Member, IEEE,
-Jane Hsu, Member, IEEE, and Amir Hussain, Senior Member, IEEE"
 18a849b1f336e3c3b7c0ee311c9ccde582d7214f,"Efficiently Scaling Up Crowdsourced Video Annotation A Set of Best Practices for High Quality , Economical Video Labeling","Int J Comput Vis
 DOI 10.1007/s11263-012-0564-1
 Efﬁciently Scaling up Crowdsourced Video Annotation
@@ -49268,20 +41713,6 @@ Edouard Oyallon,1,4,5 Eugene Belilovsky,2 Sergey Zagoruyko,3 Michal Valko4
 CentraleSupelec, Universit´e Paris-Saclay
 MILA, University of Montreal
 WILLOW – Inria Paris, 4SequeL – Inria Lille, 5GALEN – Inria Saclay"
-189355bff03076cc5bddaa11239626051931144d,Learning Representations for Automatic Colorization,"Learning Representations for Automatic Colorization
-Gustav Larsson1, Michael Maire2, and Gregory Shakhnarovich2
-University of Chicago
-Toyota Technological Institute at Chicago"
-18d4210a5bb56e92045ef0637208685abaaca6a5,GIANT: geo-informative attributes for location recognition and exploration,"GIANT: Geo-Informative Attributes for
-locatioN recogniTion and exploration
-National Lab of Pattern Recognition, Institute of Automation, CAS, Beijing 100190, China
-China-Singapore Institute of Digital Media, Singapore, 139951, Singapore
-Quan Fang1,2, Jitao Sang1,2, Changsheng Xu1,2
-{qfang, jtsang,"
-183ad3409a53914247affc599b33af38d94937be,A Latent-Variable Lattice Model,"An Inertial Latent-Variable Sequence Model
-Rajasekaran Masatran
-Indian Institute of Technology Madras, Chennai, TN, India
-MASATRAN AT FREESHELL.ORG"
 85188c77f3b2de3a45f7d4f709b6ea79e36bd0d9,"Combined model for detecting , localizing , interpreting and recognizing faces","Author manuscript, published in ""Workshop on Faces in 'Real-Life' Images: Detection, Alignment, and Recognition, Marseille :
 France (2008)"""
 85387549277d6131dc8596ffacc7a21aeee0c6d1,Attribute Enhanced Face Aging with Wavelet-based Generative Adversarial Networks,"Attribute Enhanced Face Aging with Wavelet-based Generative Adversarial
@@ -49330,14 +41761,6 @@ Robots
 F. Gaisser
 BioMechanical Enginering"
 856b8576999517c0cb7d95aef0159432604a8447,The 19 th Meeting on Image Recognition and Understanding Weighted Heterogeneous Learning for Deep Convolutional Neural Network Based Facial Image Analysis,The 19th Meeting on Image Recognition and Understanding
-8599560c50a55e75928dba6bbcbb98ef180a0798,Vocabulary Length Experiments for Binary Image Classification Using BOV Approach,"Signal & Image Processing : An International Journal (SIPIJ) Vol.4, No.6, December 2013
-VOCABULARY LENGTH EXPERIMENTS FOR BINARY
-IMAGE CLASSIFICATION USING BOV APPROACH
-S.P.Vimal1, Eshaan Puri2 and P.K.Thiruvikiraman3
-,2Department of Computer Science and Information Systems
-Birla Institute of Technology and Science, Pilani, Rajasthan, India
-Department of Physics,  Birla Institute of Technology and Science,
-Hyderabad Campus, Andra Pradesh, India"
 8558ea46c8f7e56c57073b27408c6638e81293f0,Morphable crowds,
 85955fe6cdf4f9f35fc9eab6cc4fccbb819e68a1,3D Face Reconstruction by Learning from Synthetic Data,"D Face Reconstruction by Learning from Synthetic Data
 Elad Richardson*
@@ -49348,14 +41771,6 @@ Department of Computer Science, Technion - Israel Institute of Technology"
 Autonomous Vehicles that Interact with Pedestrians:
 A Survey of Theory and Practice
 Amir Rasouli and John K. Tsotsos"
-8582d5307793643e5b6a5e4354ee1ba32eff3809,Techniques for Face Detection & Recognition Systema Comprehensive Review,"IOSR Journal of Computer Engineering (IOSR-JCE)
-e-ISSN: 2278-0661, p- ISSN: 2278-8727Volume 15, Issue 5 (Nov. - Dec. 2013), PP 01-12
-www.iosrjournals.org
-Techniques for Face Detection & Recognition System-
-Comprehensive Review
-Vandana S.Bhat1, Dr. J. D. Pujari2
-Department of Information Science & Engineering, SDMCET, Dharwad, INDIA
-Department of Information Science & Engineering, SDMCET, Dharwad, INDIA"
 85fd2bda5eb3afe68a5a78c30297064aec1361f6,"Are You Smiling, or Have I Seen You Before? Familiarity Makes Faces Look Happier.","702003 PSSXXX10.1177/0956797617702003Carr et al.Are You Smiling, or Have I Seen You Before?
 research-article2017
 Research Article
@@ -49386,30 +41801,9 @@ CNRS, UMR5516, Laboratoire Hubert
 Curien, F-42000, Saint-Etienne, France,
 Université de Saint-Etienne, Jean Mon-
 net, F-42000, Saint-Etienne, France."
-851f3dcfde59313dc2c8b87314f5a191d82194f4,Multiview Graphical Models for Tracking Occluded Objects,"Volume 3, Issue 10, October 2013                                    ISSN: 2277 128X
-International Journal of Advanced Research in
-Computer Science and Software Engineering
-Research Paper
-Available online at: www.ijarcsse.com
-Multiview Graphical Models for Tracking Occluded Objects
-Bharath
-Student,
-Dept.of CSE,
-Jntuk, Kakinada, India
-Smt. D.Neelima
-Asst.Professor,
-Dept.of CSE,
-Jntuk, Kakinada, India"
 858901405086056361f8f1839c2f3d65fc86a748,ON TENSOR TUCKER DECOMPOSITION : THE CASE FOR AN ADJUSTABLE CORE SIZE,"ON TENSOR TUCKER DECOMPOSITION: THE CASE FOR AN
 ADJUSTABLE CORE SIZE
 BILIAN CHEN ∗, ZHENING LI † , AND SHUZHONG ZHANG ‡"
-85d9cc478a6ef976ae83c8817d7d35e94b4dcf9d,Big Data Processing With Application to Image Super-Resolution,"Big Data Processing With Application to Image Super-Resolution
-Xiangjun Meng & Baiqing Diao
-State Grid Shandong Electric Power Company, Jinan, China
-Lipeng Zhu
-China Electric Power Research Institute, Nanjing, China
-Guangwei Gao & Song Deng
-Institute of Advanced Technology, Nanjing University of Posts and Telecommunications, Nanjing, China"
 858ddff549ae0a3094c747fb1f26aa72821374ec,"Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-Related Applications","Survey on RGB, 3D, Thermal, and Multimodal
 Approaches for Facial Expression Recognition:
 History, Trends, and Affect-related Applications
@@ -49445,12 +41839,6 @@ Kamel Saidi
 Will Shackleford
 This publication is available free of charge from:
 http://dx.doi.org/10.6028/NIST.IR.8045"
-8569fc88a3d1ac8b873872becb2ee8bc01dc73bc,Deep-Person: Learning Discriminative Deep Features for Person Re-Identification,"Deep-Person: Learning Discriminative Deep Features
-for Person Re-Identiﬁcation
-Xiang Bai, Mingkun Yang, Tengteng Huang,
-Zhiyong Dou, Rui Yu, Yongchao Xu∗
-School of Electronic Information and Communications, Huazhong University of Science and
-Technology (HUST), Wuhan, 430074, China"
 8566231abd7e5bc71ee0bc0da84b8d76ce07a501,On The Stability of Video Detection and Tracking,"On The Stability of Video Detection and Tracking
 Hong Zhang
 Chinese University of Hong Kong
@@ -49460,26 +41848,6 @@ TuSimple LLC"
 George D. C. Cavalcanti1s2 and Edson C. B. Cawalho Filho’
 ’ UFPE-Universidade  Federal de Pemambuco, 50732-970, Recife, PE, Brad
 FIR-Faculdade  Integrada do Recife 50720-635 Recife, PE, Brad"
-858555b6f4663fe083d6c81a2671c9cd8130bbf3,Object Discovery via Cohesion Measurement,"Object Discovery via Cohesion Measurement
-Guanjun Guo, Hanzi Wang*, Senior Member, IEEE, Wan-Lei Zhao,
-Yan Yan, Member, IEEE, Xuelong Li, Fellow, IEEE"
-853d6cfe9c08c971979d1dd138bb21c25ff750bf,Comparison of MultiView Face Recognition using DCT and Hybrid DWT of Score Fusion under Uncontrolled Illumination Variation,"International Journal of Computer Applications (0975 – 8887)
-Volume 96– No.4, June 20143
-Comparison of Multi-View Face Recognition using DCT
-nd Hybrid DWT of Score Fusion under Uncontrolled
-Illumination Variation
-Manisha J Kasar
-M.Tech Student (CE)
-Computer Department, MPSTME
-NMIMS, Shirpur, Dist :Dhule, Maharashtra,
-India
-Nitin S.Choubey
-P.hd (Computer)
-Computer Department, MPSTME
-NMIMS, Shirpur, Dist :Dhule, Maharashtra,
-India
-is  one  of
-for  matching.  First,"
 8575adafc04a7915bd71c3733e379577da0c4406,Sistema tutor afectivo para la enseñanza de lógica algorítmica y programación,"Sistema tutor afectivo para la enseñanza de lógica
 lgorítmica y programación
 Ramón Zatarain-Cabada1, María Lucia Barrón-Estrada1,
@@ -49505,10 +41873,6 @@ PA-GAN: IMPROVING GAN TRAINING BY
 PROGRESSIVE AUGMENTATION
 Anonymous authors
 Paper under double-blind review"
-854dbb4a0048007a49df84e3f56124d387588d99,Spatial-Temporal Recurrent Neural Network for Emotion Recognition,"JOURNAL OF LATEX CLASS FILES, VOL. 13, NO. 9, SEPTEMBER 2014
-Spatial-Temporal Recurrent Neural Network for
-Emotion Recognition
-Tong Zhang, Wenming Zheng*, Member, IEEE, Zhen Cui*, Yuan Zong and Yang Li"
 85401b669a989da15bb3d2b37d4598c21d9d061b,"The effect of intranasal oxytocin versus placebo treatment on the autonomic responses to human sounds in autism: a single-blind, randomized, placebo-controlled, crossover design study","Lin et al. Molecular Autism 2014, 5:20
 http://www.molecularautism.com/content/5/1/20
 Open Access
@@ -49642,21 +42006,12 @@ Google Brain Toronto"
 35308a3fd49d4f33bdbd35fefee39e39fe6b30b7,Efficient and effective human action recognition in video through motion boundary description with a compact set of trajectories,"biblio.ugent.be   The UGent Institutional Repository is the electronic archiving and dissemination platform for allUGent research publications. Ghent University has implemented a mandate stipulating that allacademic publications of UGent researchers should be deposited and archived in this repository.Except for items where current copyright restrictions apply, these papers are available in OpenAccess.   This item is the archived peer-reviewed author-version of:   Efficient and effective human action recognition in video through motion boundary description witha compact set of trajectories   Jeong-Jik Seo, Jisoo Son, Hyung-Il Kim, Wesley De Neve, and Yong Man Ro   In: 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition,1, 1-6, 2015.     To refer to or to cite this work, please use the citation to the published version:   Seo, J., Son, J., Kim, H., De Neve, W., and Ro, Y. M. (2015). Efficient and effective human actionrecognition in video through motion boundary description with a compact set of trajectories. 11thIEEE International Conference and Workshops on Automatic Face and Gesture Recognition 1 1-6.http://dx.doi.org/10.1109/FG.2015.7163123"
 35800a537017803dd08274710388734db66b54f0,Sliced Wasserstein Generative Models,"Sliced Wasserstein Generative Models
 Jiqing Wu * 1 Zhiwu Huang * 1 Wen Li 1 Janine Thoma 1 Luc Van Gool 1 2"
-3514140d9c2e692abed0aebe0531f78c250f5806,Discriminative Transformation Learning for Fuzzy Sparse Subspace Clustering,"Discriminative Transformation Learning for Fuzzy
-Sparse Subspace Clustering
-Zaidao Wen, Biao Hou, Member, IEEE, Qian Wu and Licheng Jiao, Senior Member, IEEE"
 3596c23a0f13c36d2c71c4cba4351363954dd02a,PathFinder : An autonomous mobile robot guided by Computer Vision,"PathFinder: An autonomous mobile robot guided by Computer
 Vision
 Andre R. de Geus1,2, Marcelo H. Stoppa1, Sergio F. da Silva1,2
 Modeling and Optimization Program, Federal University of Goias, Catalao, Goias, Brazil
 Biotechnology Institute, Federal University of Goias, Catalao, Goias, Brazil
 Email:"
-3575d74eb548c3187ec5b0d27383ac966b9d7110,Feature Extraction and Face Recognition through Neural Network,"International Journal of Advanced Computer Technology (IJACT)
-ISSN:2319-7900
-Feature Extraction and Face Recognition through Neural
-Network
-Sanjay Kumar Dekate,Research scholar, Dr. C. V. Raman University, Bilaspur, India
-Dr. Anupam Shukla,Professor, ABV-IIITM, Gwalior, India"
 357df3ee0f0c30d5c8abc5a1bdf70122322d6fbd,O BJECT DETECTORS EMERGE IN D EEP S CENE CNN S,"Under review as a conference paper at ICLR 2015
 OBJECT DETECTORS EMERGE IN DEEP SCENE CNNS
 Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, Antonio Torralba
@@ -49691,10 +42046,6 @@ Zoe Bichler3
 Bioinformatics Institute, A*STAR, Singapore
 Institute of Molecular and Cell Biology, A*STAR, Singapore
 National Neuroscience Institute, Singapore"
-35c0220ab8a8281129a00ac32ef2f488fb562eb7,Part Annotations via Pairwise Correspondence,"Part Annotations via Pairwise Correspondence
-Subhransu Maji Gregory Shakhnarovich
-{smaji,
-Toyota Technological Institute at Chicago, Chicago, IL"
 35035f79256a3f19a111fff34df6d14876d83fab,Satyam: Democratizing Groundtruth for Machine Vision,"SATYAM: DEMOCRATIZING GROUNDTRUTH FOR MACHINE VISION
 Hang Qiu?, Krishna Chintalapudi†, Ramesh Govindan?"
 35794480e556b946c82d498ce868fa62235befa7,Real-Time Detection and Tracking of Multiple Humans from High Bird's-Eye Views in the Visual and Infrared Spectrum,"Real-Time Detection and Tracking of Multiple
@@ -49703,11 +42054,6 @@ Visual and Infrared Spectrum
 Julius K¨ummerle, Timo Hinzmann,
 Anurag Sai Vempati and Roland Siegwart
 Autonomous Systems Lab, ETH Zurich"
-35e0256b33212ddad2db548484c595334f15b4da,Attentive Fashion Grammar Network for Fashion Landmark Detection and Clothing Category Classification,"Attentive Fashion Grammar Network for
-Fashion Landmark Detection and Clothing Category Classiﬁcation
-Wenguan Wang∗1,2, Yuanlu Xu∗2, Jianbing Shen†1, and Song-Chun Zhu2
-Beijing Lab of Intelligent Information Technology, School of Computer Science, Beijing Institute of Technology, China
-Department of Computer Science and Statistics, University of California, Los Angeles, USA"
 35fd6c9f2e651259ee565475f88faeb523511d4e,On the Performance of Kernel Methods for Skin Color Segmentation,"Hindawi Publishing Corporation
 EURASIP Journal on Advances in Signal Processing
 Volume 2009, Article ID 856039, 13 pages
@@ -49728,9 +42074,6 @@ Speciﬁcally, binary Support Vector Classiﬁer (two-class SVM) and one-class N
 in some example images or in limited databases. We hypothesize that comparative performance evaluation on a representative
 pplication-oriented database will allow us to determine whether proposed kernel methods exhibit signiﬁcant better performance
 than conventional skin segmentation methods. Two image databases were acquired for a webcam-based face recognition"
-35184b2891ca17a8b1e5fe45b319336d00a2a4c9,Video Person Re-Identification by Temporal Residual Learning,"Video Person Re-identiﬁcation by Temporal
-Residual Learning
-Ju Dai∗, Pingping Zhang∗, Huchuan Lu, Senior Member, IEEE, and Hongyu Wang, Member, IEEE"
 35e855b0c1af4cc7bf62a8eb459c949776fbe7ee,Local Features and Kernels for Classification of Texture and Object Categories : An In-Depth Study,"INSTITUT NATIONAL DE RECHERCHE EN INFORMATIQUE ET EN AUTOMATIQUE
 Local Features and Kernels for Classi(cid:2)cation of
 Texture and Object Categories: An In-Depth Study
@@ -49749,10 +42092,6 @@ Singh, Matteo Cella, Michel Valstar, Hongying Meng, Andrew Kemp, Moshen Shafizad
 C. Elkins, Natalie Kanakam, Amschel de Rothschild, Nick Tyler, Paul J. Watson, Amanda C. de C.
 Williams, Maja Pantic, and Nadia Bianchi-Berthouze*
 face  videos,  head  mounted  and  room  audio  signals,"
-354ddc8976a762ee03fb78b73adc3b5312e5f2a5,Accurate Eye Center Location through Invariant Isocentric Patterns,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication.
-Accurate Eye Center Location through Invariant
-Isocentric Patterns
-Roberto Valenti, Student Member, IEEE, and Theo Gevers, Member, IEEE,"
 35197862aed9a73415bdaea2fb8ad29d66675604,Mixture of SVMs for Face Class Modeling,"Mixture of SVMs for Face Class Modeling
 Julien Meynet1, Vlad Popovici, and Jean-Philippe Thiran
 Signal Processing Institute, Swiss Federal Institute of Technology Lausanne,
@@ -49803,40 +42142,10 @@ Georgia Inst. Of Technology
 Atlanta, CA"
 351de1f7862bd13a82fcfcaa698b4efd53bc2c35,Automatic 3D face verification from range data,- 1930-7803-7663-3/03/$17.00 ©2003 IEEEICASSP 2003(cid:224)
 35fe83665c61adb513781c7208b92706ae2a1578,Answering Visual What-If Questions: From Actions to Predicted Scene Descriptions,
-357e97b04375f09e9f4cfd45c69ecd9d7f0a15e1,ISAAC: A Convolutional Neural Network Accelerator with In-Situ Analog Arithmetic in Crossbars,"October 5th 2016: This version corrects some of the results for the ISAAC-PE and ISAAC-SE configurations.
-ISAAC: A Convolutional Neural Network
-Accelerator with In-Situ Analog Arithmetic in
-Crossbars
-Ali Shaﬁee∗, Anirban Nag∗, Naveen Muralimanohar†, Rajeev Balasubramonian∗,
-John Paul Strachan†, Miao Hu†, R. Stanley Williams†, Vivek Srikumar∗
-School of Computing, University of Utah, Salt Lake City, Utah, USA
-Email: {shaﬁee, anirban, rajeev,
-Hewlett Packard Labs, Palo Alto, California, USA
-Email: {naveen.muralimanohar, john-paul.strachan, miao.hu,"
 3506ef7168e07840187ec978b47f3a05a753101d,Robust 3D Face Landmark Localization Based on Local Coordinate Coding,"Robust 3D Face Landmark Localization based on
 Local Coordinate Coding
 Mingli Song, Senior Member, IEEE, Dacheng Tao, Senior Member, IEEE, Shengpeng Sun, Chun Chen, and
 Stephen J. Maybank Fellow, IEEE,"
-3535ba0cba9bf03443d52cbfc9a87090ca2e5d49,Supplementary Material : Synthesized Classifiers for Zero-Shot Learning,"Supplementary Material:
-Synthesized Classiﬁers for Zero-Shot Learning
-Soravit Changpinyo∗, Wei-Lun Chao∗
-U. of Southern California
-Los Angeles, CA
-Boqing Gong
-U. of Central Florida
-Orlando, FL
-schangpi,
-Fei Sha
-U. of California
-Los Angeles, CA
-In this Supplementary Material, we provide details
-omitted in the main text.
-• Section 1: cross-validation strategies (Section 3.2
-of the main paper).
-• Section 2: learning metrics for semantic similarity
-(Section 3.1 of the main paper).
-• Section 3: details on experimental setup (Sec-
-tion 4.1 of the main paper)."
 35e87e06cf19908855a16ede8c79a0d3d7687b5c,Strategies for MultiView Face Recognition for Identification of Human Faces : A Review,"Strategies for Multi-View Face Recognition for
 Identification of Human Faces: A Review
 Pritesh G. Shah
@@ -49903,10 +42212,6 @@ Full Terms & Conditions of access and use can be found at
 http://www.tandfonline.com/action/journalInformation?journalCode=pqje20
 Download by: [Rachel Bennetts]
 Date: 22 March 2016, At: 07:06"
-351c02d4775ae95e04ab1e5dd0c758d2d80c3ddd,ActionSnapping: Motion-Based Video Synchronization,"ActionSnapping: Motion-based Video
-Synchronization
-Jean-Charles Bazin and Alexander Sorkine-Hornung
-Disney Research"
 353480b21d5745590db5f70b016a27e25f5b9aec,Cross-Modal and Hierarchical Modeling of Video and Text,"Cross-Modal and Hierarchical Modeling of Video
 nd Text
 Bowen Zhang(cid:63)1, Hexiang Hu(cid:63)1, and Fei Sha2
@@ -49919,9 +42224,6 @@ Mouna Kacimi
 Gerhard Weikum
 MPI–I–2011–5–002
 May 2011"
-35058a8166a8fa4479167ba33b3010cc8c839f44,A Study on Gait-Based Gender Classification,"A Study on Gait-Based Gender Classiﬁcation
-Shiqi Yu, Member, IEEE, Tieniu Tan, Fellow, IEEE,
-Kaiqi Huang, Member, IEEE, Kui Jia, and Xinyu Wu"
 3504907a2e3c81d78e9dfe71c93ac145b1318f9c,An End-to-End System for Unconstrained Face Verification with Deep Convolutional Neural Networks,"Noname manuscript No.
 (will be inserted by the editor)
 Unconstrained Still/Video-Based Face Veriﬁcation with Deep
@@ -49951,10 +42253,6 @@ Plzeˇn, Czech Republic
 Faculty of Applied Sciences
 University of West Bohemia
 Plzeˇn, Czech Republic"
-35af45f799c65d21bbb3cd24f666de861bad33b0,Multi-Target Tracking by Discrete-Continuous Energy Minimization,"Multi-Target Tracking by
-Discrete-Continuous Energy Minimization
-Anton Milan, Member, IEEE, Konrad Schindler, Senior Member, IEEE and
-Stefan Roth, Member, IEEE,"
 53078a5692d493685fd2d63abf297a39b2edb36d,Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking,"Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking
 Filip Radenovi´c1 Ahmet Iscen1 Giorgos Tolias1 Yannis Avrithis2 Ondˇrej Chum1
 VRG, FEE, CTU in Prague
@@ -49988,11 +42286,6 @@ Kumar Krishna Agrawal∗
 Pabitra Mitra
 {arnavkj95, abhinavagarawalla, kumarkrishna,
 Indian Institute of Technology Kharagpur"
-533bfb82c54f261e6a2b7ed7d31a2fd679c56d18,Unconstrained Face Recognition: Identifying a Person of Interest From a Media Collection,"Technical Report MSU-CSE-14-1
-Unconstrained Face Recognition: Identifying a
-Person of Interest from a Media Collection
-Lacey Best-Rowden, Hu Han, Member, IEEE, Charles Otto, Brendan Klare, Member, IEEE, and
-Anil K. Jain, Fellow, IEEE"
 53bed2d3d75c4320ad5af4a85e31bf92e3c704ef,Reinforced Video Captioning with Entailment Rewards,"Reinforced Video Captioning with Entailment Rewards
 Ramakanth Pasunuru and Mohit Bansal
 UNC Chapel Hill
@@ -50032,18 +42325,6 @@ Ramin Irani, Kamal Nasrollahi, and Thomas B. Moeslund
 Visual Analysis of People (VAP) Laboratory
 Rendsburggade 14, 9000 Aalborg, Denmark
 {ri, kn,"
-538a9230ddc14b8a5d3f5f195aac4ec43e37d16f,Joint Holistic and Partial CNN for Pedestrian Detection,"YUN ZHAO et al.: JOINT HOLISTIC AND PARTIAL CNN FOR PEDESTRIAN DETECTION 1
-Joint Holistic and Partial CNN for Pedestrian
-Detection
-Yun Zhao1
-Zejian Yuan*1
-Hui Zhang2
-Institute of Artiﬁcial Intelligence and
-Robotics
-Xi’an Jiaotong University
-Xi’an, China
-Shenzhen Forward Innovation
-Digital Technology Co. Ltd. China"
 5345822a30293c9989fd1ec19b5a2da96956347b,Acoustic-labial Speaker Verication 1,"Acoustic(cid:0)Labial Speaker Veri(cid:1)cation 
 P(cid:0) Jourlin a
 (cid:0)
@@ -50064,9 +42345,6 @@ School of Engineering
 Department of Applied Signal Processing
 Supervisor:  Mr. Tommaso Gritti, PHILIPS RESEARCH, Eindhoven, Netherlands
 Examiner:    Mr. Mikael Nilsson"
-532c80d296a5852703a33c03824f4199e44f96a7,Fast Rigid 3D Registration Solution: A Simple Method Free of SVD and Eigen-Decomposition,"Fast Rigid 3D Registration Solution: A Simple
-Method Free of SVD and Eigen-Decomposition
-Jin Wu, Member, IEEE, Ming Liu, Member, IEEE, Zebo Zhou and Rui Li, Member, IEEE"
 5367610430dc0380dfbe8344e08537267875968c,Tracking 3 D Surfaces Using Multiple Cameras : A Probabilistic Approach,"Tracking 3D Surfaces Using
 Multiple Cameras: A
 Probabilistic Approach
@@ -50125,9 +42403,6 @@ Aditya Khosla
 Akhil S. Raju
 Antonio Torralba
 Aude Oliva"
-53facd4da5f1d1f98f876211421957f5fbe8a29a,The Mesh-LBP: A Framework for Extracting Local Binary Patterns From Discrete Manifolds,"The Mesh-LBP: A Framework for Extracting Local
-Binary Patterns From Discrete Manifolds
-Naoufel Werghi, Member, IEEE, Stefano Berretti, Member, IEEE, and Alberto del Bimbo, Member, IEEE"
 535919a5ffa0f214df2ad39e80015ecba174a10d,k-fold Subsampling based Sequential Backward Feature Elimination,
 5366573e96a1dadfcd4fd592f83017e378a0e185,"Server, server in the cloud. Who is the fairest in the crowd?","Böhlen, Chandola and Salunkhe
 Server, server in the cloud.
@@ -50152,26 +42427,6 @@ Zagreb, HR-10000, Croatia
 Email:
 Email:
 Email:"
-53b35519e09772fb7ec470fdec51c6edb43c4f13,Word Channel Based Multiscale Pedestrian Detection without Image Resizing and Using Only One Classifier,"Word Channel Based Multiscale Pedestrian Detection
-Without Image Resizing and Using Only One Classifier
-Arthur Daniel Costea       and       Sergiu Nedevschi
-Image Processing and Pattern Recognition Group  (http://cv.utcluj.ro)
-Computer Science Department, Technical University of Cluj-Napoca, Romania
-{arthur.costea,
-pedestrian or non-pedestrian based on image features. The
-image features should capture the required information for
-lassification, while allowing fast computation.
-Previous  object  detection  approaches  use  a  fixed  size
-sliding window and resize the image [8] or use a fixed size
-image  and  resize  the  sliding  window  [29].  When  using
-multiple  sliding  window  scales,  individual  classifiers  are
-trained  for  different  scales.  In  this  paper  we  propose  a
-solution to pedestrian detection that does not require image
-resizing and uses only one classifier for all sliding window
-scales. The proposed approach introduces the use of word
-hannels,  inspired  from  codebook  based  semantic  image
-nnotation techniques for extracting classification features.
-. Related work"
 539b66c91f41719ef94f50e6d42ab470f2a2702c,Agreeing to cross: How drivers and pedestrians communicate,"Agreeing To Cross: How Drivers and Pedestrians Communicate*
 Amir Rasouli, Iuliia Kotseruba and John K. Tsotsos1"
 53822d61e829ef02a95a6c89fea082114fd3e16b,A General Framework for Tracking Multiple People from a Moving Camera,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication.
@@ -50179,13 +42434,6 @@ IEEE TRANSACTION ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
 A General Framework for Tracking Multiple
 People from a Moving Camera
 Wongun Choi, Caroline Pantofaru, Silvio Savarese"
-536d1f74c6543afcf2bc711befd82ac7886d1c33,Fusing Shearlets and LBP Feature Sets for Face Recognition,"ISSN 1746-7659, England, UK
-Journal of Information and Computing Science
-Vol. 10, No. 1, 2015, pp. 029-039
-Fusing Shearlets and LBP Feature Sets for Face Recognition
-Zhiyong Zeng 1
-Faculty of Software, Fujian Normal University, Fuzhou, 350108, China
-(Received October  07, 2014, accepted December 24, 2014)"
 53819049f41998a5a1587dfccccc2db8612b45af,Deep Semantic Lane Segmentation for Mapless Driving,"018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
 Madrid, Spain, October 1-5, 2018
 978-1-5386-8093-3/18/$31.00 ©2018 IEEE"
@@ -50213,11 +42461,6 @@ Published online: 8 October 2015
 53f981cb6f1cf19b08255c571d62cc1073fd792b,Deconvolutional networks for point-cloud vehicle detection and tracking in driving scenarios,"Deconvolutional Networks for Point-Cloud Vehicle Detection
 nd Tracking in Driving Scenarios
 V´ıctor Vaquero∗, Ivan del Pino∗, Francesc Moreno-Noguer, Joan Sol`a, Alberto Sanfeliu and Juan Andrade-Cetto"
-896e2776174dcb86d311789ab83a266151d0595b,A Novel Performance Evaluation Methodology for Single-Target Trackers,"A Novel Performance Evaluation Methodology
-for Single-Target Trackers
-Matej Kristan, Member, IEEE, Jiri Matas, Aleˇs Leonardis, Member, IEEE, Tom´aˇs Voj´ıˇr,
-Roman Pflugfelder, Gustavo Fern´andez, Georg Nebehay, Fatih Porikli and
-Luka ˇCehovin Member, IEEE,"
 89742f28108330f97df94df98f73b459b02ca33d,Query Specific Semantic Signature for Improved Web Image Re-Ranking Joshith,"International Journal of Engineering and Technical Research (IJETR)
 ISSN: 2321-0869, Volume-3, Issue-3, March 2015
 Query Specific Semantic Signature for Improved
@@ -50311,26 +42554,6 @@ No Author Given
 No Institute Given"
 8961677300a9ee30ca51e1a3cf9815b4a162265b,Deep Representation Learning with Part Loss for Person Re-Identification,"Deep Representation Learning with Part Loss for Person Re-Identiﬁcation
 Hantao Yao, Shiliang Zhang, Yongdong Zhang, Jintao Li, Qi Tian"
-89fe52d1be59c7cbc8c0c2d41a0247060390ca74,Robust Multimodal Biometrics Recognition : A Review,"Volume 5, Issue 10, October-2015                                       ISSN: 2277 128X
-International Journal of Advanced Research in
-Computer Science and Software Engineering
-Research Paper
-Available online at: www.ijarcsse.com
-Robust Multimodal Biometrics Recognition: A Review
-Sangramsing Kayte
-Jaypalsing N. Kayte
-Dr. Charansing Kayte
-Suvarnsing G. Bhable
-Department of Computer
-Science & IT
-Science & IT
-Computer Science & IT
-Department of Computer
-Department of
-Assistant Professor
-Department of Digital
-nd Cyber Forensic,
-Aurangabad,"
 890103cb8d3d869298421da817d0a181487ec79a,Learning the Hierarchical Parts of Objects by Deep Non-Smooth Nonnegative Matrix Factorization,"Learning the Hierarchical Parts of Objects by Deep
 Non-Smooth Nonnegative Matrix Factorization
 Jinshi Yu, Guoxu Zhou, Andrzej Cichocki
@@ -50365,10 +42588,6 @@ Powered by the California Digital Library
 University of California"
 894f1e924dfb8dfb843c42835fa79e386ac07383,Dimensional emotion recognition using visual and textual cues,"Dimensional emotion recognition using visual and textual cues
 Pedro M. Ferreira1, Diogo Pernes2, Kelwin Fernandes1, Ana Rebelo3 and Jaime S. Cardoso1"
-89475b4d09e541e09becb9aa134c8de117725205,Automatic Analysis of Facial Expressions Based on Deep Covariance Trajectories,"Automatic Analysis of Facial Expressions Based on
-Deep Covariance Trajectories
-Naima Otberdout, Member, IEEE, Anis Kacem, Member, IEEE, Mohamed Daoudi, Senior, IEEE,
-Lahoucine Ballihi, Member, IEEE, and Stefano Berretti, Senior, IEEE"
 89ef75b43bc329f21fd3e81d36235d4824478831,A real-time Deep Learning pedestrian detector for robot navigation,"A Real-Time Deep Learning Pedestrian Detector for Robot Navigation
 David Ribeiro, Andr´e Mateus, Pedro Miraldo, and Jacinto C. Nascimento
 Instituto de Sistemas e Rob´otica, Instituto Superior T´ecnico, Universidade de Lisboa, Lisboa, Portugal"
@@ -50385,26 +42604,6 @@ A. Elhayek C. Stoll K. I. Kim and C. Theobalt
 Max-Planck-Institute for Informatics, Saarbrücken, Germany
 Figure 1: Examples of multi-person tracking with moving cameras. (Left two images) two actors, and two moving and 3 static
 ameras (Soccer1). (Right two images) One actor, and three moving and two static cameras (Walk2)."
-894fa98257c0b9a1cb0388ecf56f3bcaa85dd3ff,Cognitive Effects of Mindfulness Training: Results of a Pilot Study Based on a Theory Driven Approach,"ORIGINAL RESEARCH
-published: 12 July 2016
-doi: 10.3389/fpsyg.2016.01037
-Cognitive Effects of Mindfulness
-Training: Results of a Pilot Study
-Based on a Theory Driven Approach
-Lena Wimmer *, Silja Bellingrath and Lisa von Stockhausen
-Department of Psychology, University of Duisburg-Essen, Essen, Germany
-The present paper reports a pilot study which tested cognitive effects of mindfulness
-practice in a theory-driven approach. Thirty-four ﬁfth graders received either a
-mindfulness training which was based on the mindfulness-based stress reduction
-pproach (experimental group), a concentration training (active control group), or no
-treatment (passive control group). Based on the operational deﬁnition of mindfulness by
-Bishop et al. (2004), effects on sustained attention, cognitive flexibility, cognitive inhibition,
-nd data-driven as opposed to schema-based information processing were predicted.
-These abilities were assessed in a pre-post design by means of a vigilance test, a
-reversible ﬁgures test, the Wisconsin Card Sorting Test, a Stroop test, a visual search
-task, and a recognition task of prototypical faces. Results suggest that the mindfulness
-training speciﬁcally improved cognitive inhibition and data-driven information processing.
-Keywords: mindfulness, attention, cognition, meditation, cognitive flexibility, cognitive inhibition, children, school"
 89ed007d1dc8cd26033e71dfad7698c835b7336f,"Statistical modeling, level-set and ensemble learning for automatic segmentation of 3D high-frequency ultrasound data : towards expedited quantitative ultrasound in lymph nodes from cancer patients. (Modélisation statistique, méthodes d'ensemble de niveaux et apprentissage automatique pour la segmen","Statistical modeling, level-set and ensemble learning for
 utomatic segmentation of 3D high-frequency
 ultrasound data : towards expedited quantitative
@@ -50506,14 +42705,6 @@ social network, account, Sensor Pattern Noise, identity, linking, digital image
 89e324b9c64a800e57ad82eddecc03f2cc0b7cc5,Long-Term Identity-Aware Multi-Person Tracking for Surveillance Video Summarization.,"Long-Term Identity-Aware Multi-Person Tracking
 for Surveillance Video Summarization
 Shoou-I Yu, Yi Yang, Xuanchong Li, and Alexander G. Hauptmann"
-d22785eae6b7503cb16402514fd5bd9571511654,Evaluating Facial Expressions with Different Occlusion around Image Sequence,"Evaluating Facial Expressions with Different
-Occlusion around Image Sequence
-Ankita Vyas, Ramchand Hablani
-Department of Computer Science
-Sanghvi Institute of Management & Science
-Indore (MP), India
-local
-INTRODUCTION"
 d2b86b6dc93631990e21a12278e77f002fb4b116,Aalborg Universitet Attention in Multimodal Neural Networks for Person Re-identification,"Aalborg Universitet
 Attention in Multimodal Neural Networks for Person Re-identification
 Lejbølle, Aske Rasch; Krogh, Benjamin; Nasrollahi, Kamal; Moeslund, Thomas B.
@@ -50585,13 +42776,6 @@ Keywords:
 Convolution Neural Network
 Ear Recognition
 Uniform Illumination Invariant"
-d2a5b9b8f02f39f7d9ef48d234ec61f4ddc6c291,Facial surface reconstruction in 3 D format,"Journal of Theoretical and Applied Computer Science
-ISSN 2299-2634
-Vol. 6, No. 4, 2012, pp. 37-50
-http://www.jtacs.org
-Facial surface reconstruction in 3D format
-Nadezhda Shchegoleva
-Department of Mathematical Computer Software, Saint Petersburg Electrotechnical University (LETI), Russia"
 d2518b01092160cecec2e986935b0129b0bbff45,Looking around the Backyard Helps to Recognize Handwritten Digits Anonymous CVPR submission Paper ID 2611,"#2611
 CVPR 2008 Submission #2611. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE.
 #2611
@@ -50641,26 +42825,6 @@ d24a7a7ceb2ddce42ac64d1d07ccebc2a55ed053,A Bayesian Architecture for Combining S
 Dashan Gao and Nuno Vasconcelos
 SVCL-TR 2005/01
 June 2005"
-d278e020be85a1ccd90aa366b70c43884dd3f798,Learning From Less Data: Diversified Subset Selection and Active Learning in Image Classification Tasks,"Learning From Less Data: Diversiﬁed Subset Selection and
-Active Learning in Image Classiﬁcation Tasks
-Vishal Kaushal
-IIT Bombay
-Mumbai, Maharashtra, India
-Khoshrav Doctor
-AITOE Labs
-Mumbai, Maharashtra, India
-Suyash Shetty
-AITOE Labs
-Mumbai, Maharashtra, India
-Rishabh Iyer
-AITOE Labs
-Seattle, Washington, USA
-Anurag Sahoo
-AITOE Labs
-Seattle, Washington, USA
-Narsimha Raju
-IIT Bombay
-Mumbai, Maharashtra, India"
 d24a30ed78b749f3730e25dcef89472dd5fb439c,Improving Face Recognition Performance Using a Hierarchical Bayesian Model,"Improving Face Recognition
 Performance Using a Hierarchical
 Bayesian Model
@@ -50688,12 +42852,6 @@ d2f254780699bafff02eafc92e00822ee597c864,A comparative evaluation of global repr
 for Face Verification
 S. Cruz-Llanas, J. Fierrez-Aguilar, J. Ortega-Garcia, J. Gonzalez-Rodriguez
 Biometrics Research Lab. – Universidad Politecnica de Madrid"
-d252e10024a22c8274ae67dbf37aa854d75a85f2,Joint Gender Classification and Age Estimation by Nearly Orthogonalizing Their Semantic Spaces,"Joint Gender Classiﬁcation and Age Estimation
-y Nearly Orthogonalizing Their Semantic
-Spaces
-Qing Tiana, Songcan Chena,∗
-College of Computer Science and Technology, Nanjing University of Aeronautics and
-Astronautics, Nanjing 210016, China"
 d28c12e270a06e977b59194cc6564787c87caa7e,HUMAN ACTION POSELETS ESTIMATION VIA COLOR G-SURF IN STILL IMAGES,"HUMAN ACTION POSELETS ESTIMATION VIA COLOR G-SURF IN STILL IMAGES
 M. Favorskaya *, D. Novikov, Y. Savitskaya
 Institute of Informatics and Telecommunications, Siberian State Aerospace University, 31 Krasnoyarsky Rabochy av., Krasnoyarsk,
@@ -50710,16 +42868,6 @@ Objekterkennung
 Erik Rodner
 Lehrstuhl Digitale Bildverarbeitung
 Friedrich-Schiller Universit¨at Jena"
-d2b0e08637266f49e9764b65e5154363b063a00d,Employing Fuzzy-Histogram Equalization to Combat Illumination Invariance in Face Recognition Systems,"I.J. Intelligent Systems and Applications, 2012, 9, 54-60
-Published Online  August 2012 in MECS  (http://www.mecs -press.org/)
-DOI:  10.5815/ijisa.2012.09.07
-Employing  Fuzzy-Histogram  Equalization to
-Combat Illumination  Invariance  in Face
-Recognition  Systems
-Adebayo  Kolawole  John
-Department Of  Computer Science,  Oduduwa University, Ipetumodu, Ile-Ife,  Nigeria
-Onifade  Onifade  Williams
-Department Of  Computer Science,  University Of  Ibadan, Ibadan, Nigeria"
 d2ada7d9424c056cc555f331dbb23ddab84eeee7,Background Subtraction with Dirichlet Processes,"Background Subtraction with Dirichlet
 Processes
 Tom S. F. Haines and Tao Xiang
@@ -50739,12 +42887,6 @@ Doctoral Student, Jain University, Bangalore
 GM Institute of Technology, Davanagere
 D Face Detection and Recognition under Occlusion
 is  very  vital.  Three-dimensional"
-d2f1fa5f3cc425f7d5b9f6fe6123da8bdb0724b7,A New Image Retrieval System Based on CBIR,"International Journal of Emerging Technology and Advanced Engineering
-Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 5, Issue 2, February 2015)
-A New Image Retrieval System Based on CBIR
-Richa Jain1, Sitesh Kumar Sinha2, Mukesh Kumar3
-,2,3CSE Department, AISECT University, India
-image  retrieval"
 d2cda0dbb8b2e83ce3e70d818f78d2add803c661,Automatic Video Captioning via Multi-channel Sequential Encoding,"Automatic Video Captioning via Multi-channel
 Sequential Encoding
 Chenyang Zhang and Yingli Tian
@@ -50796,23 +42938,6 @@ Copyright © Institute of Research Engineers and Doctors, USA .All rights reserv
 ISBN: 978-1-63248-060-6 doi: 10.15224/ 978-1-63248-060-6-07
 Bio-Inspired Pedestrian Detection and Tracking
 Miguel Farrajota, João M.F. Rodrigues and J.M.H. du Buf"
-cdd5062627c7b331d64a1dec25989815cd9a4913,GCSTLPP : Face Recognition using Gabor Center-Symmetric Tensor Locality Preservative Projection Approach in Video,"I.J. Modern Education and Computer Science, 2016, 4, 18-24
-Published Online April 2016 in MECS (http://www.mecs-press.org/)
-DOI: 10.5815/ijmecs.2016.04.03
-GCSTLPP: Face Recognition using Gabor
-Center-Symmetric Tensor Locality Preservative
-Projection Approach in Video
-DayanandaSagar College of Engineering, Information Science and Engineering Department, Bangalore, India
-Rajeshwari.J
-Email:
-K. Karibasappa
-Oxford College of Engineering, Bangalore, India
-Email:
-Gopalkrishna M.T
-K.S. School of Engineering and Management, Computer Science and Engineering Department, Bangalore, India
-Email:
-three
-ombining"
 cd827a9dbf82240cb711f049989decada01c8ac7,"Object Localization , Segmentation , and Classification in 3 D Images by","City University of New York (CUNY)
 CUNY Academic Works
 Dissertations, Theses, and Capstone Projects
@@ -50858,13 +42983,6 @@ ARTIFICIAL REFERENCE PICTURES
 Felix Haub, Thorsten Laude and J¨orn Ostermann
 Leibniz University Hannover, Institut f¨ur Informationsverarbeitung,
 Appelstr. 9a, 30167 Hannover, Germany"
-cd490432e35ed5c5b7d80e1525e2780d7467ffb6,ESTIMATION OF LOST VALUES USING KINECT ’ S SENSOR IN AN INPAINTING TECHNIQUE,"International Journal of Scientific Research Engineering & Technology (IJSRET), ISSN 2278 – 0882
-Vo lu me 3, Issue 8, Nove mber 2014
-BACKGROUND ESTIMATION OF LOST VALUES USING
-KINECT’S SENSOR IN AN INPAINTING TECHNIQUE
-* PG Schola r, Dept of EEE [Embedded systems technologies], #Assistant Professsor,
-Dept of EEE, Kongunadu College Of Engineering & Technology,Trichy, Ta mil Nadu, India
-*S.Kavitha, #Ms.S.Hemalatha"
 cd0a04c0af9b6c523884415ba54bff370fd02fab,Generalized Sparselet Models for Real-Time Multiclass Object Recognition,"Generalized Sparselet Models for Real-Time
 Multiclass Object Recognition
 Hyun Oh Song, Ross Girshick, Stefan Zickler, Christopher Geyer, Pedro Felzenszwalb, and Trevor Darrell"
@@ -50965,32 +43083,6 @@ Charlie Frowd*, Anna Petkovic, Kamran Nawaz and Yasmeen Bashir
 School of Psychology, University of Central Lancashire, Preston, UK
 *Corresponding author: Dr Charlie Frowd, School of Psychology, University of Central Lancashire,
 Preston PR1 2HE. Email: Phone: (01772) 893439."
-b2b535118c5c4dfcc96f547274cdc05dde629976,Automatic Recognition of Facial Displays of Unfelt Emotions,"JOURNAL OF IEEE TRANSACTIONS ON AFFECTIVE COMPUTING, VOL. XX, NO. X, XXX 2017
-Automatic Recognition of Facial Displays of
-Unfelt Emotions
-Kaustubh Kulkarni*, Ciprian Adrian Corneanu*, Ikechukwu Ofodile*, Student Member, IEEE, Sergio
-Escalera, Xavier Bar´o, Sylwia Hyniewska, Member, IEEE, J¨uri Allik,
-nd Gholamreza Anbarjafari, Senior Member, IEEE"
-b216040f110d2549f61e3f5a7261cab128cab361,Weighted Voting of Discriminative Regions for Face Recognition,"IEICE TRANS. INF. & SYST., VOL.E100–D, NO.11 NOVEMBER 2017
-LETTER
-Weighted Voting of Discriminative Regions for Face Recognition∗
-Wenming YANG†, Member, Riqiang GAO†a), and Qingmin LIAO†, Nonmembers
-SUMMARY
-This paper presents a strategy, Weighted Voting of Dis-
-riminative Regions (WVDR), to improve the face recognition perfor-
-mance, especially in Small Sample Size (SSS) and occlusion situations.
-In WVDR, we extract the discriminative regions according to facial key
-points and abandon the rest parts. Considering different regions of face
-make different contributions to recognition, we assign weights to regions
-for weighted voting. We construct a decision dictionary according to the
-recognition results of selected regions in the training phase, and this dic-
-tionary is used in a self-deﬁned loss function to obtain weights. The ﬁnal
-identity of test sample is the weighted voting of selected regions. In this
-paper, we combine the WVDR strategy with CRC and SRC separately, and
-extensive experiments show that our method outperforms the baseline and
-some representative algorithms.
-key words: discriminative regions, small sample size, occlusion, weighted
-strategy, face recognition"
 b2624c3cb508bf053e620a090332abce904099a1,Dynamic Memory Networks for Visual and Textual Question Answering,"Dynamic Memory Networks for Visual and Textual Question Answering
 Caiming Xiong*, Stephen Merity*, Richard Socher
 MetaMind, Palo Alto, CA USA
@@ -51003,11 +43095,6 @@ MTech Student 1 , Assistant Professor 2  , Department of Computer Science and En
 Management and Technology, Raipur Chhattisgarh, India1, 2
 Vinita Phatnani1, Akash Wanjari2,
 its  significant  contribution"
-b29e60ddcabff5002c3ddec135ec94dd991d8d5a,Compressing deep convolutional neural networks in visual emotion recognition,"Compressing deep convolutional neural networks in visual emotion
-recognition
-A.G. Rassadin1, A.V. Savchenko1
-National Research University Higher School of Economics, Laboratory of Algorithms and Technologies for Network Analysis, 25/12 Bolshaya Pecherskaya
-Street, 603155, Nizhny Novgorod, Russia"
 b277bde51641d6b08693c171aea761beb14af800,FACE KERNEL EXTRACTION FROM LOCAL FEATURES,"FACE KERNEL EXTRACTION FROM
 LOCAL FEATURES
 A thesis submitted to the University of Manchester
@@ -51091,13 +43178,6 @@ France"
 b266be4d9fab8bf307ee2e6fdd6180ac7f6ef893,Look into Person: Joint Body Parsing & Pose Estimation Network and A New Benchmark,"Look into Person: Joint Body Parsing & Pose
 Estimation Network and A New Benchmark
 Xiaodan Liang, Ke Gong, Xiaohui Shen, and Liang Lin"
-b2046c78d4e2f00a72ee9a76875746d2d3f47e1c,Variational Infinite Hidden Conditional Random Fields,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
-IEEE TRANSACTION ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
-Variational Inﬁnite
-Hidden Conditional Random Fields
-Konstantinos Bousmalis, Student Member, IEEE, Stefanos Zafeiriou, Member, IEEE,
-Louis-Philippe Morency, Member, IEEE, Maja Pantic, Fellow, IEEE,
-nd Zoubin Ghahramani, Member, IEEE"
 b2891e43c7b5dcd889f1a270721209a9cb9cfb49,Human Emotion Detection and Recognition from Still Images,"Human Emotion Detection and Recognition from Still Images
 Zareena
 Student, VTU RC, Mysore
@@ -51154,16 +43234,6 @@ In Proceedings of the 12th International Joint Conference on Computer Vision, Im
 89-397
 ISBN: 978-989-758-225-7
 Copyright c(cid:13) 2017 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved"
-0e815b773e480ef20a680dd35cd72ab26a141d2f,Person re-identification via efficient inference in fully connected CRF,"Person re-identification via efficient inference in fully
-onnected CRF
-Wan Jiuqing
-Department of Automation
-Xing Menglin
-Department of Automation
-Beijing University of Aeronautics and Astronautics
-Beijing University of Aeronautics and Astronautics
-Beijing, China
-Beijing, China"
 0e78af9bd0f9a0ce4ceb5f09f24bc4e4823bd698,Spontaneous Subtle Expression Recognition: Imbalanced Databases and Solutions,"Spontaneous Subtle Expression Recognition:
 Imbalanced Databases & Solutions (cid:63)
 Anh Cat Le Ngo1, Raphael Chung-Wei Phan1, John See2
@@ -51190,9 +43260,6 @@ July 2003"
 0efdd82a4753a8309ff0a3c22106c570d8a84c20,LDA WITH SUBGROUP PCA METHOD FOR FACIAL IMAGE RETRIEVAL,"LDA WITH SUBGROUP PCA METHOD FOR FACIAL IMAGE RETRIEVAL
 Wonjun Hwang, Tae-Kyun Kim, Seokcheol Kee
 Human Computer Interaction Lab., Samsung Advanced Institute of Technology, Korea."
-0e36bf238d2db6c970ade0b5f68811ed6debc4e8,Recognizing Partial Biometric Patterns,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 4, AUGUST 2018
-Recognizing Partial Biometric Patterns
-Lingxiao He, Student Member, IEEE, Zhenan Sun, Member, IEEE, Yuhao Zhu and Yunbo Wang"
 0ef99317c2ab67923c1657c05f2eba5a280a54eb,Incremental adaptation of fuzzy ARTMAP neural networks for video-based face classification,"Proceedings of the 2009 IEEE Symposium on Computational Intelligence
 in Security and Defense Applications (CISDA 2009)
 Incremental Adaptation of Fuzzy ARTMAP Neural Networks for
@@ -51210,30 +43277,6 @@ for Face Alignment under Signiﬁcant Head Rotation
 Brandon M. Smith
 Charles R. Dyer
 University of Wisconsin–Madison"
-0ebd83e838dcd5827329c65d1ccc260e7aa7b5fe,Sufficient Dimensionality Reduction with Irrelevant Statistics,"UAI2003
-GLOBERSON ET AL.
-Sufficient Dimensionality
-Reduction  with
-Irrelevance
-Statistics
-Amir Globerson* Gal Chechik •  Naftali Tishby
-of Computer
-School
-Interdisciplinary
-The Hebrew University,
-Science
-Center for Neural Computation
-Jerusalem
-91904,
-Israel
-nd Engineering
-Unfortunately
-, natural
-datasets"
-0ee737085af468f264f57f052ea9b9b1f58d7222,SiGAN: Siamese Generative Adversarial Network for Identity-Preserving Face Hallucination,"SiGAN: Siamese Generative Adversarial Network
-for Identity-Preserving Face Hallucination
-Chih-Chung Hsu, Member, IEEE, Chia-Wen Lin, Fellow, IEEE, Weng-Tai Su, Student Member, IEEE,
-nd Gene Cheung, Senior Member, IEEE,"
 0e13f7fc698cbe78ddbf3412b13ca27a4d878fa8,Greater need to belong predicts a stronger preference for extraverted faces ☆,"See	discussions,	stats,	and	author	profiles	for	this	publication	at:	https://www.researchgate.net/publication/306357929
 Greater	need	to	belong	predicts	a	stronger
 preference	for	extraverted	faces	☆
@@ -51312,28 +43355,9 @@ Unsupervised Detection of Outlier Images Using Multi-Order
 Image Transforms
 Lior Shamira,∗
 Lawrence Technological University, 21000 W Ten Mile Rd., Southﬁeld, MI 48075, United States."
-0e7fdc0b03a1481b2fa1b5d592125f41b6cb7ad7,Dual CNN Models for Unsupervised Monocular Depth Estimation,"Dual CNN Models for Unsupervised Monocular Depth Estimation
-Computer Vision Group,
-Indian Institute of Information Technology, Sri City,
-Vamshi Krishna Repala
-Shiv Ram Dubey
-Andhra Pradesh-517646, India
-vamshi.r14,"
-0ed78b9562661c550e382ed30de252d877a04cdc,An Evaluation of Video-to-Video Face Verification,"An Evaluation of Video-to-Video Face Veriﬁcation
-Norman Poh, Member, IEEE, Chi Ho Chan, Josef Kittler, Sébastien Marcel, Christopher Mc Cool,
-Enrique Argones Rúa, José Luis Alba Castro, Mauricio Villegas, Student Member, IEEE, Roberto Paredes,
-Vitomir ˇStruc, Member, IEEE, Nikola Paveˇsic´, Albert Ali Salah, Hui Fang, and Nicholas Costen
-features,"
 0e767d8a88cdeea1a4338817c0e6ea3640ba4232,Deep Learning Architectures for Face Recognition in Video Surveillance,"Deep Learning Architectures for Face
 Recognition in Video Surveillance
 Saman Bashbaghi, Eric Granger, Robert Sabourin and Mostafa Parchami"
-0ea0f6842b759c7a51c462a7c6d3f2505ba6ea3b,Fuzzy Pattern-Based with Laplacianfaces Biometric Pattern Matching Algorithm for Face Recognition,"ISSN : 0976-8491 (Online)  |  ISSN : 2229-4333 (Print)
-IJCST  Vol. 6, ISSue 1, Jan - MarCh 2015
-Fuzzy Pattern-Based with Laplacianfaces Biometric Pattern
-Matching Algorithm for Face Recognition
-Dept. of Software Engineering, RKDF Institute of Science Technology, Bhopal, India
-Dept. of Computer Science, RKDF Institute of Science Technology, Bhopal, India
-Ajit Kumar Tiwari, 2Shrikant Lade"
 0ecaabbf846bbc78c91bf7ff71b998b61c0082d8,Automated Visual Fin Identification of Individual Great White Sharks,"Noname manuscript No.
 (will be inserted by the editor)
 Automated Visual Fin Identiﬁcation
@@ -51343,13 +43367,6 @@ Received: date / Accepted: date"
 0eff410cd6a93d0e37048e236f62e209bc4383d1,Learning discriminative MspLBP features based on Ada-LDA for multi-class pattern classification,"Anchorage Convention District
 May 3-8, 2010, Anchorage, Alaska, USA
 978-1-4244-5040-4/10/$26.00 ©2010 IEEE"
-0e23229289b1fbea14bc425718bc0a227d100b8e,Survey of Recent Advances in Visual Question Answering,"Survey of Recent Advances in Visual Question Answering
-Supriya Pandhre∗
-Indian Institute of Technology Hyderabad
-Hyderabad, India
-Shagun Sodhani
-Adobe Systems
-Noida, India"
 0e7862580028aa80c409b52ef1fa683444afcbcd,Reducing the Dimensionality of Face Space in a Sparse Distributed Local-Features Representation,"(cid:3)
 Reducing the Dimensionality of Face Space in a Sparse Distributed
 Local-Features Representation
@@ -51357,8 +43374,6 @@ Laboratory of Computational Neuroscience
 230 York Avenue, New York, NY 10021
 The Rockefeller University
 Penio S. Penev"
-0ec0b35b95f1770887844687f0718924066b1f85,Adaptive Image Denoising by Targeted Databases,"Adaptive Image Denoising by Targeted Databases
-Enming Luo, Student Member, IEEE, Stanley H. Chan, Member, IEEE, and Truong Q. Nguyen, Fellow, IEEE"
 0e9f7d8554e065a586163845dd2bfba26e55cefb,Registration of 3 D Face Scans with Average Face Models ∗,"Registration of 3D Face Scans with Average Face Models
 Albert Ali Salah1,2, Ne¸se Aly¨uz1, Lale Akarun1
 {salah, nese.alyuz,
@@ -51386,24 +43401,6 @@ Electronics Engineering Department
 SVNIT, Surat"
 0e031312cb6e1634e3115e428505e2be9ef46b75,Explicit Knowledge-based Reasoning for Visual Question Answering,"Proceedings of the Twenty-Sixth International Joint Conference on Artiﬁcial Intelligence (IJCAI-17)
 giraffe people people Attributes: glass house room standing walking wall zoo  Scenes: museum indoor  Visual Question: How many giraffes are there in the image? Answer: Two.  Common-Sense Question: Is this image related to zoology? Answer: Yes. Reason: Object/Giraffe  -->  Herbivorous animals    --> Animal --> Zoology; Attribute/Zoo --> Zoology. KB-Knowledge Question: What are the common properties between the animal in this image and zebra? Answer: Herbivorous animals; Animals; Megafauna of Africa. Figure1:ArealexampleoftheproposedKB-VQAdatasetandtheresultsgivenbyAhab,theproposedVQAapproach.Ourapproachanswersquestionsbyextractingseveraltypesofvisualconceptsfromanimageandaligningthemtolarge-scalestructuredknowl-edgebases.Apartfromanswers,ourapproachcanalsoproviderea-sonsandexplanationsforcertaintypesofquestions.itisansweringthequestionbasedonimageinformation,orjusttheprevalenceofaparticularanswerinthetrainingset.Thesecondproblemisthatbecausethemodelistrainedonindividualquestion/answerpairs,therangeofquestionsthatcanbeaccuratelyansweredislimited.Answeringgeneralquestionsposedbyhumansaboutimagesinevitablyrequiresreferencetoadiversevarietyofinformationnotcontainedintheimageitself.CapturingsuchlargeamountofinformationwouldrequireanimplausiblylargeLSTM,andacompletelyimpracticalamountoftrainingdata.Thethird,andmajor,problemwiththeLSTMapproachisthatitisincapableofex-plicitreasoningexceptinverylimitedsituations[Rockt¨ascheletal.,2016].OurmaincontributionisamethodwecallAhab1foran-sweringawidevarietyofquestionsaboutimagesthatrequire1Ahab,thecaptaininthenovelMobyDick,iseitherabrilliantvisionary,oradeludedfanatic,dependingonyourperspective."
-0e95f68171b27621a39e393afb7c74ef1506fe85,CONTENT BASED IMAGE RETRIEVAL USING ENHANCED LOCAL TETRA PATTERNS,"CONTENT BASED IMAGE RETRIEVAL USING
-ENHANCED LOCAL TETRA PATTERNS
-Divya Gupta1, Anjali Jindal2
-Assistant Professor, Computer Science Department
-SRM University, Delhi NCR Campus, India
-M.Tech Student (Computer Science and Engineering)
-SRM University, Delhi NCR Campus, India"
-0ee661a1b6bbfadb5a482ec643573de53a9adf5e,On the Use of Discriminative Cohort Score Normalization for Unconstrained Face Recognition,"JOURNAL OF LATEX CLASS FILES, VOL. X, NO. X, MONTH YEAR
-On the Use of Discriminative Cohort Score
-Normalization for Unconstrained Face Recognition
-Massimo Tistarelli, Senior Member, IEEE, Yunlian Sun, and Norman Poh, Member, IEEE"
-e9ed17fd8bf1f3d343198e206a4a7e0561ad7e66,Cognitive Learning for Social Robot through Facial Expression from Video Input,"International Journal of Enhanced Research in Science Technology & Engineering, ISSN: 2319-7463
-Vol. 3 Issue 1, January-2014, pp: (362-365), Impact Factor: 1.252, Available online at: www.erpublications.com
-Cognitive Learning for Social Robot through
-Facial Expression from Video Input
-Neeraj Rai1, Deepak Rai2
-Department of Automation & Robotics, 2Department of Computer Science & Engg.
-,2Ajay Kumar Garg Engineering College, Ghaziabad, UP, India"
 e9c8594ce3b8c555df59ff32b1a71eb62722b38c,On the Importance of Stereo for Accurate Depth Estimation: An Efficient Semi-Supervised Deep Neural Network Approach,"On the Importance of Stereo for Accurate Depth Estimation:
 An Efﬁcient Semi-Supervised Deep Neural Network Approach
 Nikolai Smolyanskiy
@@ -51411,27 +43408,10 @@ Nikolai Smolyanskiy
 Alexey Kamenev
 NVIDIA
 Stan Birchﬁeld"
-e9ae8bbfec913300eedede3ec48acb56c15ebdea,DisguiseNet : A Contrastive Approach for Disguised Face Verification in the Wild,"DisguiseNet : A Contrastive Approach for Disguised Face Veriﬁcation in the Wild
-Skand Vishwanath Peri
-Abhinav Dhall
-Learning Affect and Semantic Image AnalysIs (LASII) Group,
-Indian Institute of Technology Ropar, India"
 e9af96d478b487fec9a06dde9e43b2ed3355ea7b,Automatic thresholding of SIFT descriptors,"AUTOMATIC THRESHOLDING OF SIFT DESCRIPTORS
 Matthew R. Kirchner
 Image and Signal Processing Branch, Research Ofﬁce, Code 4F0000D
 Naval Air Warfare Center Weapons Division, China Lake, CA 93555 USA"
-e96a3d4df7f6956ba185107747c3d7c16d1ed845,Unite the People: Closing the Loop Between 3D and 2D Human Representations,"Unite the People: Closing the Loop Between 3D and 2D Human Representations
-Christoph Lassner1,2
-Javier Romero3,*
-Martin Kiefel2
-Federica Bogo4,*
-Michael J. Black2
-Peter V. Gehler5,*
-Bernstein Center for Computational Neuroscience, T¨ubingen, Germany
-MPI for Intelligent Systems, T¨ubingen, Germany
-Body Labs Inc., New York, United States
-Microsoft, Cambridge, UK
-5University of W¨urzburg, Germany"
 e941ee2d584938e6509c0676466023f8b43b9486,Appearance based tracking with background subtraction,"The 8th International
 Computer Science
 April 26-28,  2013. Colombo,
@@ -51452,12 +43432,6 @@ Engineering
 Telecommunication
 Telecommunication
 Electronic"
-e94804b7f2515740671a678239eccdb79a050272,Generating a Fusion Image: One's Identity and Another's Shape,"Generating a Fusion Image: One’s Identity and Another’s Shape
-Donggyu Joo∗
-School of Electrical Engineering, KAIST, South Korea
-Doyeon Kim∗
-{jdg105, doyeon kim,
-Junmo Kim"
 e917bb1f7efdfc448b8b63c52e8f643e68630a11,3 D information is valuable for the detection of humans in video streams,"D information is valuable for the detection of humans
 in video streams
 Sébastien Piérard
@@ -51521,13 +43495,6 @@ Xi Yin and Xiaoming Liu Member, IEEE,"
 e9ac109c395ededb23dfc78fe85d76eeb772ee7e,A Multilevel Mixture-of-Experts Framework for Pedestrian Classification,"A Multilevel Mixture-of-Experts Framework for
 Pedestrian Classiﬁcation
 Markus Enzweiler and Dariu M. Gavrila"
-e9dc096762f503cfe0d56066c02d27082665b3cf,Face Sketch to Photo Matching Using LFDA,"International Journal of Science and Research (IJSR)
-ISSN (Online): 2319-7064
-Face Sketch to Photo Matching Using LFDA
-Pushpa Gopal Ambhore1, Lokesh Bijole2
-Research Scholor of Amravati University,
-Computer Engineering Department Padm. Dr. V. B. Kolte Coe Malkapur Maharashtra, India
-Assistant Professor, Computer Engineering Department Padm. Dr.V.B. Kolte coe Malkapur Maharashtra, India"
 e991ff3b28c46279a3bee2446d989326a682bd33,Robust non-negative matrix factorization,"Front. Electr. Electron. Eng. China 2011, 6(2): 192–200
 DOI 10.1007/s11460-011-0128-0
 Lijun ZHANG, Zhengguang CHEN, Miao ZHENG, Xiaofei HE
@@ -51660,15 +43627,6 @@ nd Media Informatics, Budapest University of Technology and Economics, Budapest,
 A special area of human-machine interaction,
 the expression of emotions gains
 importance with the continuous development of artiﬁcial agents such as social robots or"
-54801c260df5221a9de533d371d3edcc358b4050,On Combining Classifiers,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,  VOL.  20,  NO.  3,  MARCH  1998
-On Combining Classifiers
-Josef Kittler, Member, IEEE Computer Society, Mohamad Hatef, Robert P.W. Duin, and Jiri Matas"
-54dae5187de3898d8034719bcaa3e0100ae72d76,Probabilistic Attributed Hashing,"Probabilistic Attributed Hashing
-Mingdong Ou1, Peng Cui1, Jun Wang2, Fei Wang3, Wenwu Zhu1
-Tsinghua National Laboratory for Information Science and Technology
-Department of Computer Science and Technology, Tsinghua University. Beijing, China
-Department of Computer Science and Engineering, University of Connecticut. Storrs, CT. USA.
-Data Science, Alibaba Group, Seattle, WA, USA."
 5458ccf22bdea7197e28b433ef06d5225fb030a7,Video Description using Bidirectional Recurrent Neural Networks,"Video Description using Bidirectional Recurrent
 Neural Networks
 ´Alvaro Peris1, Marc Bola˜nos2,3, Petia Radeva2,3, and Francisco Casacuberta1
@@ -51725,11 +43683,6 @@ Paola CAMPADELLI, Raffaella LANZAROTTI, Giuseppe LIPORI 1
 Dipartimento di Scienze dell’Informazione.
 Università degli Studi di Milano.
 Via Comelico, 39/41 - 20135 Milano (Italy)"
-54aacc196ffe49b3450059fccdf7cd3bb6f6f3c3,A joint learning framework for attribute models and object descriptions,"A Joint Learning Framework for Attribute Models and Object Descriptions
-Dhruv Mahajan
-Yahoo! Labs, Bangalore, India
-Sundararajan Sellamanickam
-Vinod Nair"
 5479da1038a530beb760a38dbb5b08947dfaefbd,Fusing continuous spectral images for face recognition under indoor and outdoor illuminants,"DOI 10.1007/s00138-008-0151-1
 ORIGINAL PAPER
 Fusing continuous spectral images for face recognition
@@ -51835,72 +43788,11 @@ results of PK were compared to results of control subjects. Patient PK showed at
 typical patterns of brain activations in the FG and OFA. However, a significant difference between PK and control subjects was found in
 the left anterior superior temporal sulcus/middle temporal gyrus (aSTS/MTG). In PK the left aSTS/MTG was hypo‑activated in comparison"
 541bccf19086755f8b5f57fd15177dc49e77d675,A few days of a robot's life in the human's world: toward incremental individual recognition,"Computer Science and ArtificialIntelligence LaboratoryTechnical Reportmassachusetts institute of technology, cambridge, ma 02139 usa — www.csail.mit.eduMIT-CSAIL-TR-2007-022April 3, 2007A Few Days of A Robot’s Life in the Human’s World: Toward Incremental Individual RecognitionLijin Aryananda"
-8bdbb685174d6023e63c55fdf9ad9b2ac78e79bd,Learning Human Poses from Actions-Supplementary Material,"ADITYA, JAWAHAR, PAWAN: LEARNING HUMAN POSES FROM ACTIONS
-Learning Human Poses from Actions -
-Supplementary Material
-Aditya Arun1
-C.V. Jawahar1
-M. Pawan Kumar2
-IIIT Hyderabad
-University of Oxford &
-The Alan Turing Institute
-In this supplementary material, we provide additional details on optimization of our
-learning objective, implementation details, and visualization of the learning process. We
-lso provide additional results of training a different architecture for human pose estimation
-on two data sets.
-Optimization
-In this section, we provide details of optimization presented in section 3.5 of the paper.
-.1 Learning Objective
-We represent the prediction distribution using a DISCO Net, which we denote by Prw, w
-eing the parameter of the network. Similarly, we represent the conditional distribution using
-set of DISCO Nets, which we denote by Prθθθ . The set of parameters for the conditional
-networks is denoted by θθθ. We compute samples from the prediction network as {hw"
-8bf57dc0dd45ed969ad9690033d44af24fd18e05,Subject-Independent Emotion Recognition from Facial Expressions using a Gabor Feature RBF Neural Classifier Trained with Virtual Samples Generated by Concurrent Self-Organizing Maps,"Subject-Independent Emotion Recognition from Facial Expressions
-using a Gabor Feature RBF Neural Classifier Trained with Virtual
-Samples Generated by Concurrent Self-Organizing Maps
-VICTOR-EMIL NEAGOE, ADRIAN-DUMITRU CIOTEC
-Depart. Electronics, Telecommunications & Information Technology
-Polytechnic University of Bucharest
-Splaiul Independentei No. 313, Sector 6, Bucharest,
-ROMANIA"
 8b21c89b436e0aa540f7b9648e4344eb30a6e372,Robust coding schemes for indexing and retrieval from large face databases,"IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 9, NO. 1, JANUARY 2000
 Correspondence________________________________________________________________________
 Robust Coding Schemes for Indexing and Retrieval from
 Large Face Databases
 Chengjun Liu and Harry Wechsler"
-8b8b3375bc51ae357528a1f015c4d094418c9f71,"An Efficient Feature Extraction Method , Global Between Maximum and Local Within Minimum , and Its Applications","Hindawi Publishing Corporation
-Mathematical Problems in Engineering
-Volume 2011, Article ID 176058, 15 pages
-doi:10.1155/2011/176058
-Research Article
-An Efﬁcient Feature Extraction Method,
-Global Between Maximum and Local Within
-Minimum, and Its Applications
-Lei Wang,1, 2 Jiangshe Zhang,1, 2 and Fei Zang1, 2
-School of Science, Xi’an Jiaotong University, Xi’an 710049, China
-State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University,
-Xi’an 710049, China
-Correspondence should be addressed to Lei Wang,
-Received 28 March 2011; Revised 16 April 2011; Accepted 18 April 2011
-Academic Editor: Jyh Horng Chou
-Copyright q 2011 Lei Wang et al. This is an open access article distributed under the Creative
-Commons Attribution License, which permits unrestricted use, distribution, and reproduction in
-ny medium, provided the original work is properly cited.
-Feature extraction plays an important role in preprocessing procedure in dealing with small
-sample size problems. Considering the fact that LDA, LPP, and many other existing methods are"
-8b26744e11e5f226f187bf903b88933c5b0fcdc0,Cost-Effective Class-Imbalance Aware CNN for Vehicle Localization and Categorization in High Resolution Aerial Images,"Article
-Cost-Effective Class-Imbalance Aware CNN for
-Vehicle Localization and Categorization in High
-Resolution Aerial Images
-Feimo Li 1,2,*, Shuxiao Li 1,2,*, Chengfei Zhu 1,2, Xiaosong Lan 1,2 and Hongxing Chang 1,2
-Institute of Automation Chinese Academy of Sciences, Beijing 100190, China;
-(C.Z.); (X.L.); (H.C.)
-University of Chinese Academy of Science, Beijing 100049, China
-* Correspondence: (F.L.); (S.L.);
-Tel.: +86-188-0012-4228 (F.L.); +86-138-1077-1030 (S.L.)
-Academic Editors: Qi Wang, Nicolas H. Younan, Carlos López-Martínez, Gonzalo Pajares Martinsanz,
-Xiaofeng Li and Prasad S. Thenkabail
-Received: 26 February 2017; Accepted: 15 May 2017; Published: 18 May 2017"
 8bb4d90d5b97e8d08d2aaa99e9c075a506b3108a,Generating Diverse Clusterings,"Generating Diverse Clusterings
 Anonymous Author(s)"
 8b36c4675732249963b3e9294a0f52f26c6dd931,A Survey on Local Invariant Features,"FnT Computer Graphics and Vision 2:4
@@ -51976,13 +43868,6 @@ Informatics,
 in partial
 Dipl.-Inform. Stefan Heinrich
 Hamburg, 2016"
-8bda09b2fb85c317c6361aee1935bcbcf87c1c70,Score Normalization in Multimodal Systems using Generalized Extreme Value Distribution,"Score Normalization in Multimodal
-Systems using Generalized Extreme Value
-Distribution
-Renu Sharma1, 2                  1Centre for Development of Advanced Computing,
-Mumbai, India
-Sukhendu Das2                   2Indian Institute of Technology, Madras, India
-Padmaja Joshi1"
 8b632db02220806cd62e35fdebb3ede58243dee0,Recognizing Partially Occluded Faces from a Single Sample Per Class Using String-Based Matching,"Recognizing Partially Occluded Faces from a
 Single Sample Per Class Using String-Based
 Matching
@@ -52102,15 +43987,6 @@ vorgelegt von
 Tom´as Lay Herrera
 Havanna
 Bonn, November 2012"
-8bf647fed40bdc9e35560021636dfb892a46720e,Learning to hash-tag videos with Tag2Vec,"Learning to Hash-tag Videos with Tag2Vec
-Aditya Singh
-Saurabh Saini
-Rajvi Shah
-CVIT, KCIS, IIIT Hyderabad, India
-P J Narayanan
-http://cvit.iiit.ac.in/research/projects/tag2vec
-Figure 1. Learning a direct mapping from videos to hash-tags : sample frames from short video clips with user-given hash-tags
-(left); a sample frame from a query video and hash-tags suggested by our system for this query (right)."
 8b607928c7af70259a9f8af9e08e28e6037411c8,Bayesian teaching of image categories,"Bayesian teaching of image categories
 Wai Keen Vong∗
 Ravi B. Sojitra*
@@ -52167,16 +44043,6 @@ Daniel Rosser
 Yusuf Pisan
 Games Studio, Faculty of Engineering and IT, University of Technology, Sydney"
 8b9c53e7d65ba7a7be3d588d00481f2ff49b5ef4,Orienting in response to gaze and the social use of gaze among children with autism spectrum disorder.,23Journal of Autism andDevelopmental Disorders ISSN 0162-3257Volume 43Number 7 J Autism Dev Disord (2013)43:1584-1596DOI 10.1007/s10803-012-1704-8Orienting in Response to Gaze and theSocial Use of Gaze among Children withAutism Spectrum DisorderAdrienne Rombough & Grace Iarocci
-b7207c142b0b9f4def3ae7cd07ce50ca31d930e8,Human Age Group Prediction from Unknown Facial Image 1,"Volume 7, Issue 5, May 2017                                  ISSN: 2277 128X
-International Journal of Advanced Research in
-Computer Science and Software Engineering
-Research Paper
-Available online at: www.ijarcsse.com
-Arumugam P, 2Muthukumar S, 3Selva Kumar S, 4Gayathri
-Department of Statistics,   2, 4 Department of CSE, 3Research Scholar
-, 3 Manonmaniam Sundaranar University, Tirunelveli, Tamilnadu, India
-, 4 Varuvan Vadivelan Institute of Technology, Dharmapuri, Tamilnadu, India
-DOI: 10.23956/ijarcsse/SV7I5/0103"
 b774d7c951b9c444572085e15f6a81a063abf123,Diversity Regularized Spatiotemporal Attention for Video-based Person Re-identification,"FeaturesSpatial  AttentionTemporal  Attention1                      2                      3                              N‘face’‘torso’‘bag’Figure1.SpatiotemporalAttention.Inchallengingvideore-identiﬁcationscenarios,apersonisrarelyfullyvisibleinallframes.However,framesinwhichonlypartofthepersonisvis-ibleoftencontainusefulinformation.Forexample,thefaceisclearlyvisibleintheframes1and2,thetorsoinframe2,andthehandbaginframes2,3andN.Insteadofaveragingfullframefeaturesacrosstime,weproposeanewspatiotemporalapproachwhichlearnstodetectasetofKdiversesalientimageregionswithineachframe(superimposedheatmaps).Anaggregaterep-resentationofeachbodypartisthenproducedbycombiningtheextractedper-frameregionsacrosstime(weightsshownaswhitetext).Ourspatiotemporalapproachcreatesacompactencodingofthevideothatexploitsusefulpartialinformationineachframebyleveragingmultiplespatialattentionmodels,andcombiningtheiroutputsusingmultipletemporalattentionmodels.personre-identiﬁcation,whichisageneralizationofthestandardimage-basedre-identiﬁcationtask.InsteadofarXiv:1803.09882v1  [cs.CV]  27 Mar 2018"
 b704f8360c369e65f0826ca23dac2d4e221d8997,A Knowledge Base for Automatic Feature Recognition from Point Clouds in an Urban Scene,"Article
 A Knowledge Base for Automatic Feature Recognition
@@ -52280,14 +44146,6 @@ Department of Applied Mathematics and Informatics,
 Ryukoku University, Ootsu, Shiga 520–2194, JAPAN
 National Institute of Advanced Industrial Science and Technology(AIST),
 Tsukuba, Ibaraki 305–8568, JAPAN"
-b7894c1f805ffd90ab4ab06002c70de68d6982ab,A comprehensive age estimation on face images using hybrid filter based feature extraction,"Biomedical Research 2017; Special Issue: S610-S618
-ISSN 0970-938X
-www.biomedres.info
-A comprehensive age estimation on face images using hybrid filter based
-feature extraction.
-Karthikeyan D1*, Balakrishnan G2
-Department of ECE, Srinivasan Engineering College, Perambalur, India
-Department of Computer Science and Engineering, Indra Ganesan College of Engineering, Trichy, India"
 b7a0e7dab11781c252e1145f3526aee388b4136d,Facing humanness: Facial width-to-height ratio predicts ascriptions of humanity.,"Journal of Personality and Social
 Psychology
 Facing Humanness: Facial Width-to-Height Ratio
@@ -52373,10 +44231,6 @@ Centre for Research in Computer Vision, University of Central Florida (UCF)2"
 b79f3d9f8de4d1cc6679676146a40d2a8596f32d,Composing Simple Image Descriptions using Web-scale N-grams,"Proceedings of the Fifteenth Conference on Computational Natural Language Learning, pages 220–228,
 Portland, Oregon, USA, 23–24 June 2011. c(cid:13)2011 Association for Computational Linguistics"
 b73fdae232270404f96754329a1a18768974d3f6,International Journal of Advanced Robotic Systems Local Relation Map : A Novel Illumination Invariant Face Recognition Approach Regular Paper,
-b730908bc1f80b711c031f3ea459e4de09a3d324,Active Orientation Models for Face Alignment In-the-Wild,"Active Orientation Models for Face
-Alignment In-the-Wild
-Georgios Tzimiropoulos, Joan Alabort-i-Medina, Student Member, IEEE,
-Stefanos P. Zafeiriou, Member, IEEE, and Maja Pantic, Fellow, IEEE"
 b74c410ea8db3babb9a307d1fb8f08b90ce8b490,Automatic Visual Speech Recognition,"6 Automatic Visual Speech Recognition Alin Chiţu¹ and Léon J.M. Rothkrantz¹,² ¹Delft University of Technology ²Netherlands Defence Academy The Netherlands 1. Introduction Lip reading was thought for many years to be specific to hearing impaired persons. Therefore, it was considered that lip reading is one possible solution to an abnormal situation. Even the name of the domain suggests that lip reading was considered to be a rather artificial way of communication because it associates lip reading with the written language which is a relatively new cultural phenomenon and is not an evolutionary inherent ability. Extensive lip reading research was primarily done in order to improve the teaching methodology for hearing impaired persons to increase their chances for integration in the society. Later on, the research done in human perception and more exactly in speech perception proved that lip reading is actively employed in different degrees by all humans irrespective to their hearing capacity. The most well know study in this respect was performed by Harry McGurk and John MacDonald in 1976. In their experiment the two researchers were trying to understand the perception of speech by children. Their finding, now called the McGurk effect, published in Nature (Mcgurk & Macdonald, 1976), was that if a person is presented a video sequence with a certain utterance (i.e. in their experiments utterance 'ga'), but in the same time the acoustics present a different utterance (i.e. in their experiments the sound 'ba'), in a large majority of cases the person will perceive a third utterance (i.e. in this case 'da'). Subsequent experiments showed that this is true as well for longer utterances and that is not a particularity of the visual and aural senses but also true for other perception functions. Therefore, lip reading is part of our multi-sensory speech perception process and could be better named visual speech recognition. Being an evolutionary acquired capacity, same as speech perception, some scientists consider the lip reading's neural mechanism the one that enables humans to achieve high literacy skills with relative easiness (van Atteveldt, 2006). Another source of confusion is the “lip” word, because it implies that the lips are the only part of the speaker face that transmit information about what is being said. The teeth, the tongue and the cavity were shown to be of great importance for lip reading by humans (Williams et al., 1998). Also other face elements were shown to be important during face to face communication; however, their exact influence is not completely elucidated. During experiments in which a gaze tracker was used to track the speaker's areas of attention during communication it was found that the human lip readers focus on four major areas: the mouth, the eyes and the centre of the face depending on the task and the noise level (Buchan et al., 2007). In normal situations the listener scans the mouth and the other areas www.intechopen.com"
 b768cb6fc2616f3dbe9ef4e25dedd7d95781ba66,Distribution Matching in Variational Inference,"Distribution Matching in Variational Inference
 Mihaela Rosca Balaji Lakshminarayanan
@@ -52405,19 +44259,7 @@ of the scene in addition to its color video. Nevertheless,
 effective people counting in real-world conditions using depth
 information still remains a largely unsolved problem due to
 noise and occlusion [6]."
-b7d540cd0de72e984cdec44afa4a4d039cfd5eea,Object Tracking Benchmark,"Object Tracking Benchmark
-Yi Wu, Member, IEEE, Jongwoo Lim, Member, IEEE, and Ming-Hsuan Yang, Senior Member, IEEE"
 b732393cd3877f7e6d3cf3ca033a42415bd6db56,Statistical and Geometric Modeling of Spatio-Temporal Patterns for Video Understanding,
-2fe0555f2b92a81992247519cb8fdc047069e2b0,A Semantic World Model for Urban Search and Rescue Based on Heterogeneous Sensors,"This is a preprint of a paper which appeared in the Proceedings of
-RoboCup 2010: Robot Soccer World Cup XIV
-A Semantic World Model for Urban Search and
-Rescue Based on Heterogeneous Sensors
-Johannes Meyer2, Paul Schnitzspan1, Stefan Kohlbrecher1, Karen Petersen1,
-Mykhaylo Andriluka1, Oliver Schwahn1, Uwe Klingauf2, Stefan Roth1,
-Bernt Schiele1,3, and Oskar von Stryk1
-Department of Computer Science, TU Darmstadt, Germany
-Department of Mechanical Engineering, TU Darmstadt, Germany
-MPI Informatics, Saarbr¨ucken, Germany"
 2f23f7d08c7b8670289cfedd1e571f44a3bace8b,Contextual Information and Covariance Descriptors for People Surveillance: An Application for Safety of Construction Workers,"Hindawi Publishing Corporation
 EURASIP Journal on Image and Video Processing
 Volume 2011, Article ID 684819, 16 pages
@@ -52581,19 +44423,6 @@ AudioPairBank: Towards A Large-Scale
 Tag-Pair-Based Audio Content Analysis
 Sebastian S¨ager, and Benjamin Elizalde, and Damian Borth IEEE Member, and Christian Schulze,
 nd Bhiksha Raj IEEE Fellow, and Ian Lane IEEE Member"
-2f349ec19443523bc6c1e4b15fb677b1c188e253,Finding Time Series Motifs in Disk-Resident Data,"Finding Time Series Motifs in Disk-Resident Data
-Abdullah Mueen, Eamonn Keogh
-Nima Bigdely-Shamlo
-Department of Computer Science and Engineering
-University of California, Riverside, USA
-{mueen,"
-2ffcd35d9b8867a42be23978079f5f24be8d3e35,Satellite based Image Processing using Data mining,"ISSN XXXX XXXX © 2018 IJESC
-Research Article                                                                                                                            Volume 8 Issue No.6
-Satellite based Image Processing using Data mining
-E.Malleshwari1, S.Nirmal Kumar2, J.Dhinesh3
-Professor1, Assistant Professor2, PG Scholar3
-Department of Information Technology1, 2, Master of Computer Applications3
-Vel Tech High Tech Dr Rangarajan Dr Sakunthala Engineering College, Avadi, Chennai, India"
 2f7e9b45255c9029d2ae97bbb004d6072e70fa79,cvpaper.challenge in 2015 - A review of CVPR2015 and DeepSurvey,"Noname manuscript No.
 (will be inserted by the editor)
 vpaper.challenge in 2015
@@ -52685,26 +44514,6 @@ Fernando Azpiroz3, Petia Radeva1,2 and Jordi Vitri`a1,2
 Computer Vision Center (CVC), Universitat Aut`onoma de Barcelona, Barcelona, Spain
 Dept. Matem`atica Aplicada i An`alisis, Universitat de Barcelona, Barcelona, Spain
 Digestive System Research Unit, Hospital Vall dHebron, Barcelona, Spain"
-2f3f4e0c8a9c63e714a10a6711c67f5e84e4c7c1,IoT Based Embedded Smart Lock Control System,"ISSN XXXX XXXX © 2016 IJESC
-Research Article                                                                                                             Volume 6 Issue No. 11
-IoT Based Embedded Smart Lock Control System
-Rohith R1, J. Nageswara Reddy2, K. Ravi Kiran3
-M.Tech, Embedded Systems, CM RCET, Hyderabad, India 1
-Assistant Professor, Depart ment of ECE, CM RCET, Hyderabad, India2
-Assistant Professor, Depart ment, of ECE, CM RCET, Hyderabad, India3
-INTRODUCTION
-Abstrac t:
-Smart ho me security and re mote monitoring have become vita l and indispensable in recent times, and with the advent of new con cepts
-like  Internet of Things and development of advanced authentication and security technologies, the need for smarter security s ystems
-has  only  been  growing.  The  design  and  development  of  an  intelligent  web -based  door  lock  control  system  using  face  recognition
-technology, for authentication, re mote  monitoring of visitors and re mote control of s mart door loc k has been reported in th is paper.
-This system uses Haar-like  features for face detection and Local Binary Pattern Histogram (LBPH) fo r face recognition. The  system
-lso includes a web-based remote monitoring, an authentication module, and a bare-bones embedded IoT server, which transmits the
-live pictures of the visitors via email a long with an SMS notification,  and the owner can then remotely control the lock by responding
-to  the  email  with  predefined  security  codes  to  unlock  the door.  This  system  finds  a wide application  in  sma rt  homes  where  the
-physical presence of the owner at all times is not possible, and where a remote authentication and control  is desired. The system has
-een  imple mented  and  tested  using  the  Raspberry  Pi  2  board,  Python  along  with  OpenCV  are   used  to  program  the  various  face
-recognition and control modules."
 2f59f28a1ca3130d413e8e8b59fb30d50ac020e2,Children Gender Recognition Under Unconstrained Conditions Based on Contextual Information,"Children Gender Recognition Under Unconstrained
 Conditions Based on Contextual Information
 Riccardo Satta, Javier Galbally and Laurent Beslay
@@ -52728,24 +44537,6 @@ Coupled Generative Adversarial Nets
 Liu, M.-Y.; Tuzel, O.
 TR2016-070
 June 2016"
-2f17f6c460e02bd105dcbf14c9b73f34c5fb59bd,Robust Face Recognition Using the Deep C2D-CNN Model Based on Decision-Level Fusion,"Article
-Robust Face Recognition Using the Deep C2D-CNN
-Model Based on Decision-Level Fusion
-Jing Li 1,2,†, Tao Qiu 3,†, Chang Wen 3,*, Kai Xie 1,2 and Fang-Qing Wen 1,2
-School of Electronic and Information, Yangtze University, Jingzhou 434023, China;
-(J.L.); (K.X.); (F-Q.W.)
-National Demonstration Center for Experimental Electrical and Electronic Education, Yangtze University,
-Jingzhou 434023, China
-School of Computer Science, Yangtze University, Jingzhou 434023, China;
-* Correspondence: Tel.: +86-136-9731-5482
-These authors contributed equally to this work.
-Received: 20 May 2018; Accepted: 25 June 2018; Published: 28 June 2018"
-2fa16dc0ee50550c1bf58c410912d48cddbc3554,Search Tracker: Human-Derived Object Tracking in the Wild Through Large-Scale Search and Retrieval,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCSVT.2016.2555718, IEEE
-Transactions on Circuits and Systems for Video Technology
-Search Tracker: Human-derived object tracking
-in-the-wild through large-scale search and retrieval
-Archith John Bency, Student Member, IEEE S. Karthikeyan,, Carter De Leo, Santhoshkumar Sunderrajan,
-Member, IEEE and B. S. Manjunath, Fellow, IEEE"
 2fa1629d75a03b950c56bf9b3430b2983abd7881,Learning geometrical transforms between multi camera views using Canonical Correlation Analysis,"CONRAD, MESTER: LEARNING GEOMETRICAL TRANSFORMS USING CCA
 Learning geometrical transforms between
 multi camera views using Canonical
@@ -52907,30 +44698,9 @@ September 2010
 Department of Computer Science"
 aa23d33983b1abd2d8a677040eb875e93c478a7f,Measuring the Objectness of Image Windows,"Measuring the objectness of image windows
 Bogdan Alexe, Thomas Deselaers, and Vittorio Ferrari"
-aaa6fe8045e1a071e1762cffe4f59e0bd508daf9,Single-Pedestrian Detection Aided by Two-Pedestrian Detection,"IEEE TRANSACTIONS PATTERN ANALYSIS AND MACHINE INTELLIGENCE
-Single-Pedestrian Detection Aided by
--Pedestrian Detection
-Wanli Ouyang, Member, IEEE, Xingyu Zeng and Xiaogang Wang, Member, IEEE,"
-aa07203067566f251041f73ee087aa7dfb847509,Biometric System Using Cryptography : A Survey,"Anupam Baruah et al, International Journal of Computer Science and Mobile Computing, Vol.4 Issue.9, September- 2015, pg. 101-104
-Available Online at www.ijcsmc.com
-International Journal of Computer Science and Mobile Computing
-A Monthly Journal of Computer Science and Information Technology
-ISSN 2320–088X
-IJCSMC, Vol. 4, Issue. 9, September 2015, pg.101 – 104
-SURVEY ARTICLE
-Biometric System Using
-Cryptography: A Survey
-Anupam Baruah1, Prof. (Dr.) Lakshmi Prasad Saikia2
-¹Research Scholar, Dept. Of Computer Sc. & Engg, Assam downtown University, India
-²Professor, Dept. Of Computer Sc. & Engg, Assam downtown University, India"
 aad7f9eeb10d4f655c3e3d18d3542603ad3071b4,Deep Unsupervised Learning of Visual Similarities,"Deep Unsupervised Learning of Visual Similarities
 Artsiom Sanakoyeu∗, Miguel A. Bautista, Björn Ommer
 Heidelberg Collaboratory for Image Processing and Interdisciplinary Center for Scientiﬁc Computing, Heidelberg University, Germany"
-aae742779e8b754da7973949992d258d6ca26216,Robust facial expression classification using shape and appearance features,"Robust Facial Expression Classification Using Shape
-nd Appearance Features
-S L Happy and Aurobinda Routray
-Department of Electrical Engineering,
-Indian Institute of Technology Kharagpur, India"
 aad03480c30c0a3d917d171d8d6b914026fe5105,Affordances Provide a Fundamental Categorization Principle for Visual Scenes,"Affordances
 Provide
 Fundamental
@@ -52958,59 +44728,16 @@ Rhonda P. Patrick1 and Bruce N. Ames1
 Nutrition and Metabolism Center, Children’s Hospital Oakland Research Institute, Oakland,
 California, USA
 Serotonin and vitamin D have been pro-"
-aa11aa50c5a3cee44d7fb39b1e2732c5699f565f,A Bayesian Approach to Image Recognition Based on Separable Lattice Hidden Markov Models,"IEICE TRANS. INF. & SYST., VOL.E99–D, NO.12 DECEMBER 2016
-PAPER
-A Bayesian Approach to Image Recognition Based on Separable
-Lattice Hidden Markov Models
-Kei SAWADA†a), Student Member, Akira TAMAMORI†b), Member, Kei HASHIMOTO†c), Nonmember,
-Yoshihiko NANKAKU†d), and Keiichi TOKUDA†e), Members
-SUMMARY
-This paper proposes a Bayesian approach to image recog-
-nition based on separable lattice hidden Markov models (SL-HMMs). The
-geometric variations of the object to be recognized, e.g., size, location,
-nd rotation, are an essential problem in image recognition. SL-HMMs,
-which have been proposed to reduce the effect of geometric variations, can
-perform elastic matching both horizontally and vertically. This makes it
-possible to model not only invariances to the size and location of the object
-ut also nonlinear warping in both dimensions. The maximum likelihood
-(ML) method has been used in training SL-HMMs. However, in some im-
-ge recognition tasks, it is dif‌f‌icult to acquire suf‌f‌icient training data, and
-the ML method suffers from the over-ﬁtting problem when there is insuf‌f‌i-
-ient training data. This study aims to accurately estimate SL-HMMs using
-the maximum a posteriori (MAP) and variational Bayesian (VB) methods."
 aa9b924c88b75909871585cbadbed2d76df7dbdf,The effects of item familiarity on the neural correlates of successful associative memory encoding.,"Cogn Affect Behav Neurosci
 DOI 10.3758/s13415-015-0359-2
 The effects of item familiarity on the neural correlates
 of successful associative memory encoding
 Nancy A. Dennis 1 & Indira C. Turney 1 & Christina E. Webb 1 & Amy A. Overman 2
 # Psychonomic Society, Inc. 2015"
-aaba2a04c025f12f839ac71fb248da0dd6985d58,A COMBINED FACE RECOGNITION APPROACH BASED ON LPD AND,"VOL. 10, NO. 6, APRIL 2015                                                                                                                      ISSN 1819-6608
-ARPN Journal of Engineering and Applied Sciences
-©2006-2015 Asian Research Publishing Network (ARPN). All rights reserved.
-www.arpnjournals.com
-A COMBINED FACE RECOGNITION APPROACH BASED ON LPD
-AND LVP
-Kabilan R.1, Ravi R.2, Rajakumar G.1, Esther Leethiya Rani S.1 and Mini Minar V. C.1
-Department of ECE, Francis Xavier Engineering College, Tirunelveli, Tamilnadu, India
-Department of IT, Francis Xavier Engineering College, Tirunelveli, Tamilnadu, India
-E-Mail:"
 aa5efcc4331da6b1902f2c900b79120226fdcf20,A ROBUST CLASS-BASED REFLECTANCE RENDERING FOR FACE IMAGES,A ROBUST CLASS-BASED REFLECTANCE RENDERING FOR FACE IMAGES
 aa5ed6ee0b2fd53df5cab952aa368f8c4908ffeb,REACH - Realtime crowd tracking using a hybrid motion model,"REACH - Realtime Crowd tracking using a Hybrid motion model
 Aniket Bera1 and Dinesh Manocha1
 http://gamma.cs.unc.edu/REACH"
-aa577652ce4dad3ca3dde44f881972ae6e1acce7,Deep Attribute Networks,"Deep Attribute Networks
-Junyoung Chung
-Department of EE, KAIST
-Daejeon, South Korea
-Donghoon Lee
-Department of EE, KAIST
-Daejeon, South Korea
-Youngjoo Seo
-Department of EE, KAIST
-Daejeon, South Korea
-Chang D. Yoo
-Department of EE, KAIST
-Daejeon, South Korea"
 aa2ad3df24d8d8c4a4d2fe85f0d4e635d595f0a2,PedCut: an iterative framework for pedestrian segmentation combining shape models and multiple data cues,"F. FLOHR, D. M. GAVRILA: PEDCUT
 PedCut: an iterative framework for
 pedestrian segmentation combining
@@ -53066,11 +44793,6 @@ The Johns Hopkins Univerisity
 #D17PC00345 and ONR grant N00014-15-1-2356.
 Qi Chen, Weichao Qiu, Yi Zhang
 Lingxi Xie(
-aa32f5b0a866b04a89f75cda32e0975a541864ff,Action-Driven Object Detection with Top-Down Visual Attentions,"Action-Driven Object Detection
-with Top-Down Visual Attentions
-Donggeun Yoo, Student Member, IEEE, Sunggyun Park, Student Member, IEEE,
-Kyunghyun Paeng, Student Member, IEEE, Joon-Young Lee, Member, IEEE,
-nd In So Kweon, Member, IEEE"
 aafb8dc8fda3b13a64ec3f1ca7911df01707c453,Excitation Backprop for RNNs,"Excitation Backprop for RNNs
 Sarah Adel Bargal∗1, Andrea Zunino∗ 2, Donghyun Kim1, Jianming Zhang3,
 Vittorio Murino2,4, Stan Sclaroff1
@@ -53118,8 +44840,6 @@ Mohammad Mahdi Dehshibi1, Azam Bastanfard2, and Alireza Abdi3
 Young Researchers Club, Islamic Azad University South Tehran Branch, Tehran, Iran
 IT Research Laboratory, Faculty of Engineering, Islamic Azad University Karaj Branch, Karaj, Iran
 Faculty of Electrical, Computer and IT, Islamic Azad University Qazvin Branch, Qazvin, Iran"
-aae0e417bbfba701a1183d3d92cc7ad550ee59c3,A Statistical Method for 2-D Facial Landmarking,"A Statistical Method for 2-D Facial Landmarking
-Hamdi Dibeklio˘glu, Student Member, IEEE, Albert Ali Salah, Member, IEEE, and Theo Gevers, Member, IEEE"
 aa94f214bb3e14842e4056fdef834a51aecef39c,Reconhecimento de padrões faciais : Um estudo,"Reconhecimento de padrões faciais: Um estudo
 Alex Lima Silva, Marcos Evandro Cintra
 Universidade Federal
@@ -53146,18 +44866,10 @@ Haoqi Fan
 Jitendra Malik
 Kaiming He
 Facebook AI Research (FAIR)"
-aaaefba1bd0a9a9ec6c66a822d11fb907a05625c,"On Detection, Data Association and Segmentation for Multi-target Tracking.","This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TPAMI.2018.2849374, IEEE
-Transactions on Pattern Analysis and Machine Intelligence
-On Detection, Data Association and
-Segmentation for Multi-target Tracking
-Yicong Tian, Member, IEEE, Afshin Dehghan, Member, IEEE, and Mubarak Shah, Fellow, IEEE"
 aa74e63360c341f47a921e0043c5d58d55807fe4,Multi-Residual Networks: Improving the Speed and Accuracy of Residual Networks,"SUBMITTED FOR PUBLICATION, 2016
 Multi-Residual Networks: Improving the Speed and
 Accuracy of Residual Networks
 Masoud Abdi, and Saeid Nahavandi, Senior Member, IEEE"
-aa8c3eb6e821cb44ed5a15a2f09fba332e5561c6,Object Detection in Multi-view X-Ray Images,"Object Detection in Multi-View X-Ray Images
-Thorsten Franzel, Uwe Schmidt, and Stefan Roth
-Department of Computer Science, TU Darmstadt"
 74d4224989b5937ee6c97eec1955e64ab0699f57,Facial Emotional Classifier For Natural Interaction,"Electronic Letters on Computer Vision and Image Analysis 7(4):1-12, 2008
 Facial Emotional Classifier For Natural Interaction
 Isabelle Hupont, Eva Cerezo, Sandra Baldassarri
@@ -53165,19 +44877,6 @@ Departamento de Informática e Ingeniería de Sistemas,
 Instituto de Investigación en Ingeniería de Aragón, Universidad de Zaragoza (Spain)
 Received 29th  November 2007,  Revised 26th February 2008,  Accepted 3rd June 2008
 {478953, ecerezo,"
-741b0ce40cc18449f350792af777cc54c390eda1,Comparative Study of Principal Component Analysis and Independent Component Analysis,"International Journal of Computer Applications (0975 – 8887)
-Volume 92 – No.15, April 2014
-Comparative Study of Principal Component Analysis
-nd Independent Component Analysis
-Sushma Niket Borade
-Research Scholar
-Ratnadeep R. Deshmukh, Ph. D
-Professor
-Dept. of Computer Science and I.T.
-Dept. of Computer Science and I.T.
-Dr. Babasaheb Ambedkar Marathwada University,
-Dr. Babasaheb Ambedkar Marathwada University,
-Aurangabad – 431004, India"
 74408cfd748ad5553cba8ab64e5f83da14875ae8,Facial Expressions Tracking and Recognition: Database Protocols for Systems Validation and Evaluation,"Facial Expressions Tracking and Recognition: Database Protocols for Systems Validation
 nd Evaluation"
 74f21f2edfa985280be63f8a01aa00541f3a5625,People Groping by Spatio-Temporal Features of Trajectories,"4-13
@@ -53217,13 +44916,6 @@ Niigata, Japan
 Systems Science
 603-1 Kamitomioka, Nagaoka
 Niigata, Japan"
-74325f3d9aea3a810fe4eab8863d1a48c099de11,Regression-Based Image Alignment for General Object Categories,"Regression-Based Image Alignment
-for General Object Categories
-Hilton Bristow1 and Simon Lucey2
-Queensland University of Technology (QUT)
-Brisbane QLD 4000, Australia
-Carnegie Mellon University (CMU)
-Pittsburgh PA 15289, USA"
 74b0095944c6e29837c208307a67116ebe1231c8,Manifold learning using Euclidean k-nearest neighbor graphs [image processing examples],"beindependentandidenticallydis-tributed(i.i.d.)randomvectorswithvaluesinacompactsubsetof.The(-)nearestneighborofinisgivenby!""$%&(*,.%13575where575istheusualEuclidean(<=)distanceinbe-tweenvectorand.Forgeneralinteger?,the-nearestneighborofapointisdeﬁnedinasimilarway.The-NNgraphputsanedgebetweeneachpointinandits-nearestneighbors.LetBCDBCDFHbethesetof-nearestneighborsofin.Thetotaledgelengthofthe-NNgraphisdeﬁnedas:<JDCFHMN
 M%&QRS1575J(1)whereVWXisapowerweightingconstant.2.1.ConvergencetoExtrinsicZ-EntropyThe-NNedgelengthliesinthelargeclassoffunctionalscalledcontinuousquasi-additiveEuclideanfunctionals[7].Othergraphsinthisclassincludetheminimalspanningtree,theminimalmatch-inggraphorthetravelingsalesmantouramongothers.Thesefunc-tionalshaveremarkableasymptoticbehaviorasincreases:Theorem1([7,Theorem8.3])Let
 bei.i.d.randomvectorswithvaluesinacompactsubsetofandLebesgueden-sity\.Let]?_,aVb]anddeﬁneZF]7VHf].Then,withprobability(w.p.)gh""jk<JDCFHmoDJDCp\mFrHtr(2)whereoDJDCisaconstantindependentof\.Furthermore,themeanlengthuv<JDCFHwfmconvergestothesamelimit.Thequantitythatdeterminesthelimit(2)inTheorem1istheex-trinsicR´enyiZ-entropyofthemultivariateLebesguedensity\:yz{mF\H7Zg!pz{\mFrHtr(3)III - 9880-7803-8484-9/04/$20.00 ©2004 IEEEICASSP 2004(cid:224)"
@@ -53239,14 +44931,6 @@ Chemnitz University of Technology, Professorship on Communications Engineering,
 09126 Chemnitz, Germany
 Chemnitz University of Technology, Chair Media Informatics, Straße der Nationen 62, 09111 Chemnitz, Germany
 Correspondence to: H. Lietz"
-74eae724ef197f2822fb7f3029c63014625ce1ca,Feature Extraction based on Local Directional Pattern with SVM Decision-level Fusion for Facial Expression Recognition,"International Journal of Bio-Science and Bio-Technology
-Vol. 5, No. 2, April, 2013
-Feature Extraction based on Local Directional Pattern with SVM
-Decision-level Fusion for Facial Expression Recognition
-Juxiang Zhou1, Tianwei Xu1,2 and Jianhou Gan1
-Key Laboratory of Education Informalization for Nationalities, Ministry of
-Education, Yunnan Normal University, Kunming, China
-College of Information, Yunnan Normal University, Kunming, China"
 74a1336f1fbc8b7bb3b6e159711af1a91336ce22,An overview of traffic sign detection methods,"An overview of trafﬁc sign detection methods
 Department of Electronics, Microelectronics, Computer and Intelligent Systems
 Faculty of Electrical Engineering and Computing
@@ -53319,10 +45003,6 @@ Timo Aila
 NVIDIA
 Jaakko Lehtinen
 NVIDIA and Aalto University"
-7405ed035d1a4b9787b78e5566340a98fe4b63a0,Self-Expressive Decompositions for Matrix Approximation and Clustering,"Self-Expressive Decompositions for
-Matrix Approximation and Clustering
-Eva L. Dyer, Member, IEEE, Tom A. Goldstein, Member, IEEE, Raajen Patel, Student Member, IEEE,
-Konrad P. K¨ording, and Richard G. Baraniuk, Fellow, IEEE"
 743bbf46557ec767f389c1ec5ac901ef64ffab37,DeepV2D: Video to Depth with Differentiable Structure from Motion,"DeepV2D: Video to Depth with Differentiable Structure from Motion
 Zachary Teed1
 Jia Deng1,2
@@ -53383,11 +45063,6 @@ Processing and Telecommunications,
 Computer Science Department,
 Computer Science Department,
 Faculty of Science and Technology,"
-74cbb3acfc401a397c9a4e151ff8e3ecf5ea76d0,Egocentric Video Description based on Temporally-Linked Sequences,"Egocentric Video Description based on Temporally-Linked Sequences
-Marc Bola˜nosa,b, ´Alvaro Perisc, Francisco Casacubertac, Sergi Solera, Petia Radevaa,b
-Universitat de Barcelona, Barcelona, Spain
-Computer Vision Center, Bellaterra, Spain
-PRHLT Research Center, Universitat Polit`ecnica de Val`encia, Val`encia, Spain"
 74032e526edb45bc6c79cb5576e69486e72a316d,Animated 3D Human Models for Use in Person Recognition Experiments,"Animated 3D Human Models for Use in Person Recognition Experiments
 Jean M. Vettel1,2,3, Justin Kantner1,2, Matthew Jaswa4, Michael Miller2
 U.S. Army Research Laboratory, 2University of California, Santa Barbara, 3University of
@@ -53445,16 +45120,6 @@ COULOMB GANS: PROVABLY OPTIMAL NASH EQUI-
 LIBRIA VIA POTENTIAL FIELDS
 Anonymous authors
 Paper under double-blind review"
-744108530678ee667b9c1220933bed074794d9e2,A Scene Recognition and Semantic Analysis Approach to Unhealthy Sitting Posture Detection during Screen-Reading,"Article
-A Scene Recognition and Semantic Analysis
-Approach to Unhealthy Sitting Posture Detection
-during Screen-Reading
-Weidong Min 1,2,* ID , Hao Cui 1 ID , Qing Han 1 and Fangyuan Zou 1
-School of Information Engineering, Nanchang University, Nanchang 330031, China;
-(H.C.); (Q.H.); (F.Z.)
-School of Software Engineering, Nanchang University, Nanchang 330029, China
-* Correspondence: Tel.: +86-791-8396-9277
-Received: 18 July 2018; Accepted: 29 August 2018; Published: 16 September 2018"
 744d23991a2c48d146781405e299e9b3cc14b731,Aging Face Recognition: A Hierarchical Learning Model Based on Local Patterns Selection,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TIP.2016.2535284, IEEE
 Transactions on Image Processing
 Aging Face Recognition: A Hierarchical Learning
@@ -53574,10 +45239,6 @@ recherche français ou étrangers, des laboratoires"
 02ccd5f0eb9a48a6af088197b950fb30a8e3abcc,Scaling for Multimodal 3D Object Detection,"Scaling for Multimodal 3D Object Detection
 Andrej Karpathy
 Stanford"
-02567fd428a675ca91a0c6786f47f3e35881bcbd,Deep Label Distribution Learning With Label Ambiguity,"ACCEPTED BY IEEE TIP
-Deep Label Distribution Learning
-With Label Ambiguity
-Bin-Bin Gao, Chao Xing, Chen-Wei Xie, Jianxin Wu, Member, IEEE, and Xin Geng, Member, IEEE"
 02f038ed453de0551813159284746126168f5e15,Multi Channel-Kernel Canonical Correlation Analysis for Cross-View Person Re-Identification,"This is a pre-print version, the ﬁnal version of the manuscript with more experiments can be found at:
 https://doi.org/10.1145/3038916
 Analysis for Cross-View Person Re-Identiﬁcation
@@ -53604,26 +45265,6 @@ Selection of our books indexed in the Book Citation Index
 in Web of Science™ Core Collection (BKCI)
 Interested in publishing with us?
 Contact"
-0291b43490e02303c9414f03980e606950ec7261,Pose-conditioned joint angle limits for 3D human pose reconstruction,"Pose-Conditioned Joint Angle Limits for 3D Human Pose Reconstruction
-Ijaz Akhter, Michael J. Black
-Max Planck Institute for Intelligent Systems, Tübingen, Germany
-Figure 1: Joint-limit dataset. We captured a new dataset for learning pose-
-dependent joint angle limits. This includes an extensive variety of stretching
-poses. A few sample images are shown here. We use this dataset to learn
-pose-conditioned joint-angle limits. The dataset and the learned joint-angle
-model will be made publicly available.
-Figure 2: We use our joint-angle-limit prior for 3D pose estimation given
-D joint locations in an image. The proposed prior helps in reducing the
-space of possible solutions to only valid 3D human poses. Our prior can
-e also used for many other problems where estimating 3D human pose is
-mbiguous.
-Accurate modeling of priors over 3D human pose is fundamental to many
-problems in computer vision. Most previous priors are either not general
-enough for the diverse nature of human poses or not restrictive enough to
-void invalid 3D poses. We propose a physically-motivated prior that only
-llows anthropometrically valid poses and restricts the ones that are invalid.
-One can use joint-angle limits to evaluate whether two connected bones
-re valid or not. However, it is established in biomechanics that there are"
 0273414ba7d56ab9ff894959b9d46e4b2fef7fd0,Photographic home styles in Congress: a computer vision approach,"Photographic home styles in Congress: a
 omputer vision approach∗
 L. Jason Anastasopoulos†.
@@ -53635,10 +45276,6 @@ December 1, 2016"
 02fbf86b975c3f45b04de8288d1565cce8b53f62,A real-time pedestrian detection system based on structure and appearance classification,"Anchorage Convention District
 May 3-8, 2010, Anchorage, Alaska, USA
 978-1-4244-5040-4/10/$26.00 ©2010 IEEE"
-029317f260b3303c20dd58e8404a665c7c5e7339,Character Identification in Feature-Length Films Using Global Face-Name Matching,"Character Identiﬁcation in Feature-Length Films
-Using Global Face-Name Matching
-Yi-Fan Zhang, Student Member, IEEE, Changsheng Xu, Senior Member, IEEE, Hanqing Lu, Senior Member, IEEE,
-nd Yeh-Min Huang, Member, IEEE"
 02cce8b08e4839d16f2142c5723fc009ccb4e3e1,Improving spatial codification in semantic segmentation,"IMPROVING SPATIAL CODIFICATION IN SEMANTIC SEGMENTATION
 Carles Ventura(cid:63)
 Kevin McGuinness†
@@ -53711,16 +45348,9 @@ Campus E1 4
 66123 Saarbrücken
 Germany
 m 4. February 2013 in Saarbrücken"
-02e17f547dd75eee7282af1b5ad2626829615ac9,"Beyond Counting: Comparisons of Density Maps for Crowd Analysis Tasks - Counting, Detection, and Tracking","JOURNAL OF LATEX CLASS FILES, VOL. XX, NO. X, MM YY
-Beyond Counting: Comparisons of Density Maps for Crowd
-Analysis Tasks - Counting, Detection, and Tracking
-Di Kang, Zheng Ma, Member, IEEE, Antoni B. Chan Senior Member, IEEE,"
 02a2c5b332d883d726929474060a7e62411c010a,Totally Corrective Multiclass Boosting with Binary Weak Learners,"SEPTEMBER 2010
 with Binary Weak Learners
 Zhihui Hao, Chunhua Shen, Nick Barnes, and Bo Wang"
-02601d184d79742c7cd0c0ed80e846d95def052e,Graphical Representation for Heterogeneous Face Recognition,"Graphical Representation for Heterogeneous
-Face Recognition
-Chunlei Peng, Xinbo Gao, Senior Member, IEEE, Nannan Wang, Member, IEEE, and Jie Li"
 0252256fa23eceb54d9eea50c9fb5c775338d9ea,Application-driven Advances in Multi-biometric Fusion,"Application-driven Advances
 in Multi-biometric Fusion
 dem Fachbereich Informatik
@@ -53851,12 +45481,6 @@ Reeach Sciei"
 022d74ae2f8680e780b18e0cbb041d5c5a57c7a5,Video Salient Object Detection via Fully Convolutional Networks,"Video Salient Object Detection via
 Fully Convolutional Networks
 Wenguan Wang, Jianbing Shen, Senior Member, IEEE, and Ling Shao, Senior Member, IEEE"
-02d7f9715cdce854d727ba763c81aae5b04d3a3b,Semantic Channels for Fast Pedestrian Detection,"Semantic Channels for Fast Pedestrian Detection
-Arthur Daniel Costea
-Sergiu Nedevschi
-Image Processing and Pattern Recognition Research Center
-Technical University of Cluj-Napoca, Romania
-{arthur.costea,"
 027beed800f7d5e20194caf6d689345045e8d0d4,Smoothed Dilated Convolutions for Improved Dense Prediction,"Smoothed Dilated Convolutions for Improved Dense Prediction
 Zhengyang Wang
 Washington State University
@@ -53915,10 +45539,6 @@ Tours, France
 Computer Science Department
 INSA Centre Val de Loire,
 Blois, France"
-0296fc4d042ca8657a7d9dd02df7eb7c0a0017ad,Subspace Learning from Image Gradient Orientations,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication.
-Subspace Learning from Image Gradient
-Orientations
-Georgios Tzimiropoulos, Member, IEEE, Stefanos Zafeiriou Member, IEEE, and Maja Pantic Fellow, IEEE"
 02af5e40653b5a545b62aa6aebfaca6557f4173d,Sensor fusion for human safety in industrial workcells,"Sensor Fusion for Human Safety in Industrial Workcells*
 Paul Rybski1, Peter Anderson-Sprecher1, Daniel Huber1, Chris Niessl1, Reid Simmons1
 Figure 1: An example of our approach. (a) The workcell as seen
@@ -53937,20 +45557,6 @@ Scrambled Support Vector Vaulted Veriﬁcation (S2V 3)
 Michael J. Wilber and Terrance E. Boult
 Vision and Security Technology Lab, UCCS
 Colorado Springs, CO, 80918, USA"
-02bee6bf61566cfc3963fe42b320a740a9458920,Efficient Pedestrian Detection via Rectangular Features Based on a Statistical Shape Model,"This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination.
-Efﬁcient Pedestrian Detection via Rectangular
-Features Based on a Statistical Shape Model
-Shanshan Zhang, Student Member, IEEE, Christian Bauckhage, Member, IEEE, and Armin B. Cremers"
-02b6acd8d1f2a5833a29b52766776fd70b3dbb56,Memory-Efficient Deep Salient Object Segmentation Networks on Gridized Superpixels,"Memory-Efﬁcient Deep Salient Object
-Segmentation Networks on Gridized Superpixels
-Caglar Aytekin, Xingyang Ni, Francesco Cricri, Lixin Fan, Emre Aksu
-Nokia Technologies, Tampere, Finland
-Corresponding Author’s Email:"
-0289786e0d5edf663c586c8552ec3708eff62331,Detecting Faces in Images: A Survey,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 24, NO. 1,
-JANUARY 2002
-Detecting Faces in Images: A Survey
-Ming-Hsuan Yang, Member, IEEE, David J. Kriegman, Senior Member, IEEE, and
-Narendra Ahuja, Fellow, IEEE"
 02e133aacde6d0977bca01ffe971c79097097b7f,Convolutional Neural Fabrics,
 023da8828f9c039c20ac9267a6b37813b74d4824,Free supervision from video games,"Free supervision from video games
 Philipp Kr¨ahenb¨uhl
@@ -54132,12 +45738,6 @@ L’archive ouverte pluridisciplinaire HAL, est
 destinée au dépôt et à la diffusion de documents
 scientifiques de niveau recherche, publiés ou non,
 émanant des établissements d’enseignement et de"
-ba7c01e1432bffc2fcde824d0b0ebd25ad7238c3,Face Recognition Techniques : A Review,"International Journal of Engineering Research and Development
-e-ISSN: 2278-067X, p-ISSN: 2278-800X, www.ijerd.com
-Volume 4, Issue 7 (November 2012), PP. 70-78
-Face Recognition Techniques: A Review
-Rajeshwar Dass, 2Ritu Rani, 3Dharmender Kumar
-,2,3 Deen Bandhu Chotu Ram University of Science & Technology Murthal, Haryana, India"
 bac748bf117cb5b06037413de92378b76ff358d0,Entropy-based sim(3) calibration of 2D lidars to egomotion sensors,"Entropy-Based Sim(3) Calibration of 2D Lidars to Egomotion Sensors
 Jacob Lambert1, Lee Clement1, Matthew Giamou2, and Jonathan Kelly1"
 ba816806adad2030e1939450226c8647105e101c,MindLAB at the THUMOS Challenge,"MindLAB at the THUMOS Challenge
@@ -54311,33 +45911,11 @@ BP 94, F-91191 Gif-sur-Yvette, France
 CNRS ; LAAS ;
 Université de Toulouse ; UPS, LAAS ;
 F-31077 Toulouse Cedex 4, France"
-656b6133fd671f129fce0091a8dab39c97e604f2,Multiview Discriminative Geometry Preserving Projection for Image Classification,"Hindawi Publishing Corporation
-e Scientiﬁc World Journal
-Volume 2014, Article ID 924090, 11 pages
-http://dx.doi.org/10.1155/2014/924090
-Research Article
-Multiview Discriminative Geometry Preserving
-Projection for Image Classification
-Ziqiang Wang, Xia Sun, Lijun Sun, and Yuchun Huang
-School of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China
-Correspondence should be addressed to Ziqiang Wang;
-Received 19 December 2013; Accepted 22 January 2014; Published 9 March 2014
-Academic Editors: X. Meng, Z. Zhou, and X. Zhu
-Copyright © 2014 Ziqiang Wang et al. This is an open access article distributed under the Creative Commons Attribution License,
-which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
-In many image classification applications, it is common to extract multiple visual features from different views to describe an image.
-Since different visual features have their own specific statistical properties and discriminative powers for image classification, the
-onventional solution for multiple view data is to concatenate these feature vectors as a new feature vector. However, this simple
-oncatenation strategy not only ignores the complementary nature of different views, but also ends up with “curse of dimensionality.”
-To address this problem, we propose a novel multiview subspace learning algorithm in this paper, named multiview discriminative
-geometry preserving projection (MDGPP) for feature extraction and classification. MDGPP can not only preserve the intraclass"
 656a59954de3c9fcf82ffcef926af6ade2f3fdb5,Convolutional Network Representation for Visual Recognition,"Convolutional Network Representation
 for Visual Recognition
 ALI SHARIF RAZAVIAN
 Doctoral Thesis
 Stockholm, Sweden, 2017"
-65babb10e727382b31ca5479b452ee725917c739,Label Distribution Learning,"Label Distribution Learning
-Xin Geng*, Member, IEEE"
 65817963194702f059bae07eadbf6486f18f4a0a,WhittleSearch: Interactive Image Search with Relative Attribute Feedback,"http://dx.doi.org/10.1007/s11263-015-0814-0
 WhittleSearch: Interactive Image Search with Relative Attribute
 Feedback
@@ -54347,50 +45925,12 @@ Received: date / Accepted: date"
 for Large-Scale Image Classiﬁcation
 Florent Perronnin, Jorge S´anchez, and Thomas Mensink
 Xerox Research Centre Europe (XRCE)"
-65696f1beb82be12e7e358bb0e5109dedf004783,Multi-view Discriminative Manifold Embedding for Pattern Classification,"Multi-view Discriminative Manifold Embedding for Pattern Classification
-X. Wang
-Departmen of Information
-Zhenghzou 450053, China
-Y. Guo
-Department of Digestive
-Zhengzhou 450053, China
-Z. Wang
-Henan University of Technology
-Zhengzhou 450001, China"
 65d588e2ff7b4f2903efbeded978885f7da5d0e0,UMPM benchmark: A multi-person dataset with synchronized video and motion capture data for evaluation of articulated human motion and interaction,"UMPM benchmark: a multi-person dataset with synchronized video and motion
 apture data for evaluation of articulated human motion and interaction
 N.P. van der Aa1,2, X. Luo1, G.J. Giezeman1, R.T. Tan1, R.C. Veltkamp1
 {x.luo, g.j.giezeman, r.t.tan,
 Utrecht University
 Noldus Information Technology"
-65874dd7220664762b5b25f47460b623a7eb0175,Tree Crown Mapping in Managed Woodlands (Parklands) of Semi-Arid West Africa Using WorldView-2 Imagery and Geographic Object Based Image Analysis,"Sensors 2014, 14, 22643-22669; doi:10.3390/s141222643
-OPEN ACCESS
-sensors
-ISSN 1424-8220
-www.mdpi.com/journal/sensors
-Article
-Tree Crown Mapping in Managed Woodlands (Parklands) of
-Semi-Arid West Africa Using WorldView-2 Imagery and
-Geographic Object Based Image Analysis
-Martin Karlson 1,*, Heather Reese 2,† and Madelene Ostwald 1,3,†
-Centre for Climate Science and Policy Research, Department of Thematic Studies/Environmental
-Change, Linköping University, Linköping 58183, Sweden; E-Mail:
-Section of Forest Remote Sensing, Department of Forest Resource Management,
-Swedish University of Agricultural Sciences, Umeå 901 83, Sweden; E-Mail:
-Centre for Environment and Sustainability, GMV, University of Gothenburg and
-Chalmers University of Technology, Göteborg 405 30, Sweden
-These authors contributed equally to this work.
-*  Author to whom correspondence should be addressed; E-Mail:
-Tel.: +46-1328-2977; Fax: +46-1313-3630.
-External Editor: Assefa M. Melesse"
-65cea66a59a4e75c8403daf3589f81627d5afd12,Social Behavior Prediction from First Person Videos,"Social Behavior Prediction from First Person Videos
-Shan Su
-UPenn
-Jung Pyo Hong
-KAIST
-Jianbo Shi
-UPenn
-Hyun Soo Park"
 653942873bc7ea6f1056739dc5015ec3631d9bbe,Face Detection Techniques-A Review,"International Journal of Current Engineering and Technology
 ISSN 2277 - 4106
 © 2013 INPRESSCO. All Rights Reserved.
@@ -54410,9 +45950,6 @@ Deb Roy
 MIT Media Lab
 0 Ames Street, E15-488
 Cambridge, Massachusetts 02139"
-65539436abf0eedabeb915a52f787b962722c99a,Satellite Image Classification via Two-Layer Sparse Coding With Biased Image Representation,"Satellite Image Classiﬁcation via Two-Layer Sparse
-Coding With Biased Image Representation
-Dengxin Dai and Wen Yang, Member, IEEE"
 65edab091e437d3b9d093dcb8be7c5dc4ce0fe0f,DeepOrgan: Multi-level Deep Convolutional Networks for Automated Pancreas Segmentation,"DeepOrgan: Multi-level Deep Convolutional
 Networks for Automated Pancreas Segmentation
 Holger R. Roth, Le Lu, Amal Farag, Hoo-Chang Shin, Jiamin Liu,
@@ -54476,10 +46013,6 @@ Duration: 48 months
 Organisation name of lead contractor for this deliverable: UJI
 Revision: Revised version, June 2007
 Dissemination level: PU"
-653d19e64bd75648cdb149f755d59e583b8367e3,"Decoupling ""when to update"" from ""how to update""","Decoupling “when to update” from “how to
-update”
-Eran Malach and Shai Shalev-Shwartz
-School of Computer Science, The Hebrew University, Israel"
 652d3f33fd0a99808dd646aed228b45eacdaf34f,A Framework for Binding and Retrieving Class-Specific Information to and from Image Patterns Using Correlation Filters,"A Framework for Binding and Retrieving
 Class-Speciﬁc Information to and from Image
 Patterns using Correlation Filters
@@ -54538,8 +46071,6 @@ ImageNet offers disambiguated la-
 els (LabelDisam), clean annotations (Clean), a dense hierarchy
 (DenseHie), full resolution images (FullRes) and is publicly avail-"
 a67e7ca0c7e1e3020169b5c59dc492e9f62f0022,FACE RECOGNITION PERFORMANCE UNDER ADVERSARIAL CONDITIONS,
-a65c76169bdb8479353806556f61bf94fdec7e10,Online Object Tracking With Sparse Prototypes,"Online Object Tracking With Sparse Prototypes
-Dong Wang, Huchuan Lu, Member, IEEE, and Ming-Hsuan Yang, Senior Member, IEEE"
 a6ebe013b639f0f79def4c219f585b8a012be04f,Facial Expression Recognition Based on Hybrid Approach,"Facial Expression Recognition Based on Hybrid
 Approach
 Md. Abdul Mannan, Antony Lam, Yoshinori Kobayashi, and Yoshinori Kuno
@@ -54648,9 +46179,6 @@ Yuan, Yu-Bo; East China University of Science and Technology, Department
 of Computer Science and Engineering
 Keyword:  IMAGE PROCESSING, IMAGE RECOGNITION, IMAGE RETRIEVAL
 IET Review Copy Only"
-a608c5f8fd42af6e9bd332ab516c8c2af7063c61,Age Estimation via Grouping and Decision Fusion,"Age Estimation via Grouping and Decision Fusion
-Kuan-Hsien Liu, Member, IEEE, Shuicheng Yan, Senior Member, IEEE,
-nd C.-C. Jay Kuo, Fellow, IEEE"
 a66373beaad40fb5a8e2e1b42c5a2213b166a55c,Childhood abuse is related to working memory impairment for positive emotion in female university students.,"Childhood abuse is related to working memory impairment for positive
 emotion in female university students
 Cromheeke S, Herpoel LA, Mueller SC.
@@ -54668,10 +46196,6 @@ CONS ID: sn 94001296
 US National Library of Medicine ID: 9602869
 This article was identified from a query of the SafetyLit database.
 Powered by TCPDF (www.tcpdf.org)"
-a6574d111bfb12d6a9988bdbbf24639d3c4534ec,Image denoising: Can plain neural networks compete with BM3D?,"Image denoising: Can plain Neural Networks compete with BM3D?
-Harold C. Burger, Christian J. Schuler, and Stefan Harmeling
-Max Planck Institute for Intelligent Systems, T¨ubingen, Germany
-http://people.tuebingen.mpg.de/burger/neural_denoising/"
 a66d89357ada66d98d242c124e1e8d96ac9b37a0,Failure Detection for Facial Landmark Detectors,"Failure Detection for Facial Landmark Detectors
 Andreas Steger, Radu Timofte, and Luc Van Gool
 Computer Vision Lab, D-ITET, ETH Zurich, Switzerland
@@ -54684,22 +46208,6 @@ D Interpreter Networks for Viewer-Centered Wireframe Modeling
 Jiajun Wu1 · Tianfan Xue2 · Joseph J. Lim3 · Yuandong Tian4 ·
 Joshua B. Tenenbaum1 · Antonio Torralba1 · William T. Freeman1,5
 Received: date / Accepted: date"
-db67edbaeb78e1dd734784cfaaa720ba86ceb6d2,SPECFACE — A dataset of human faces wearing spectacles,"SPECFACE - A Dataset of Human Faces Wearing Spectacles
-Anirban Dasgupta, Shubhobrata Bhattacharya and Aurobinda Routray
-Indian Institute of Technology Kharagpur
-India"
-dbe101c7c4b5ea5986be38e4d6de70bfc4324683,1 Deep convolutional neural networks capabilities for 2 binary classification of polar mesocyclones in 3 satellite mosaics 4,"Preprints (www.preprints.org)  |  NOT PEER-REVIEWED  |  Posted: 29 October 2018                   doi:10.20944/preprints201809.0361.v3
-Article
-Deep convolutional neural networks capabilities for
-inary classification of polar mesocyclones in
-satellite mosaics
-Mikhail Krinitskiy 1,*, Polina Verezemskaya 1,2, Kirill Grashchenkov1,3, Natalia Tilinina1,
-Sergey Gulev1 and Matthew Lazzara 4
-Shirshov Institute of Oceanology, Russian Academy of Sciences, Moscow, Russia;
-Research Computing Center of Lomonosov Moscow State University, Moscow, Russia
-Moscow Institute of Physics and Technology, Moscow, Russia
-University of Wisconsin-Madison and Madison Area Technical College, Madison, Wisconsin, USA
-*  Correspondence: Tel.: +7-926-141-6200"
 dbf360fa9997b2918a8076f1d0df9a1fffa94ed7,Recommending and Planning Trip Itineraries for Individual Travellers and Groups of Tourists,"Recommending and Planning Trip Itineraries for Individual Travellers and
 Groups of Tourists
 *Department of Computing and Information Systems, The University of Melbourne, Australia
@@ -54749,12 +46257,6 @@ Department of Electrical and Information Engineering,
 Covenant University,
 Ota, Ogun state, Nigeria
 Corresponding Author:"
-db625c4c26c7df67c9099e78961d479532628ec7,"All-in Text: Learning Document, Label, and Word Representations Jointly","Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16)
-All-in Text: Learning Document, Label, and Word Representations Jointly
-Jinseok Nam, Eneldo Loza Menc´ıa, Johannes F¨urnkranz
-Knowledge Discovery in Scientiﬁc Literature, TU Darmstadt
-Knowledge Engineering Group, TU Darmstadt
-Research Training Group AIPHES, TU Darmstadt"
 db480f100004e3ef075f9404041fe4f89fcf4e0c,Human Pose Estimation for RGBD Imagery with Multi-Channel Mixture of Parts and Kinematic Constraints,"Human Pose Estimation for RGBD Imagery with Multi-Channel
 Mixture of Parts and Kinematic Constraints
 ENRIQUE MARTINEZ-BERTI
@@ -54795,13 +46297,6 @@ CenterforAutomationResearch
 UniversityofMaryland
 Princeton,NJ
 CollegePark,MD
-dba7cf91feff6bdf26e9a3940015fd0c0cdc6520,Original Loop-Closure Detection Algorithm for Monocular vSLAM,"Original Loop-closure Detection Algorithm for
-Monocular vSLAM
-Andrey Bokovoy1,3 and Konstantin Yakovlev2,3
-Peoples’ Friendship University of Russia (RUDN University), Moscow, Russia
-Higher School of Economics, Moscow, Russia
-Institute for Systems Analysis of Federal Research Centre ""Computer Science and
-Control"" of Russian Academy of Sciences, Moscow, Russia"
 db68105a787d7ef60ebb5bb4cfce151d47748123,Improved RGB-D-T based face recognition,"Aalborg Universitet
 Improved RGB-D-T based Face Recognition
 Oliu Simon, Marc;   Corneanu, Ciprian; Nasrollahi, Kamal; Nikisins, Olegs; Guerrero, Sergio
@@ -54822,18 +46317,6 @@ nd it is a condition of accessing publications that users recognise and abide by
 ? Users may download and print one copy of any publication from the public portal for the purpose of private study or research.
 ? You may not further distribute the material or use it for any profit-making activity or commercial gain
 ? You may freely distribute the URL identifying the publication in the public portal ?"
-dbe255d3d2a5d960daaaba71cb0da292e0af36a7,Evolutionary Cost-Sensitive Extreme Learning Machine,"Evolutionary Cost-sensitive Extreme Learning
-Machine
-Lei Zhang, Member, IEEE, and David Zhang, Fellow, IEEE"
-dbcb6b4c0d73159ad4bc833fa4209b9600025fa5,Eleventh International Multi-Conference on Information Processing-2015 ( IMCIP-2015 ) Analysis of Attention Identification and Recognition of Faces through Segmentation and Relative Visual Saliency ( SRVS ),"Available online at www.sciencedirect.com
-ScienceDirect
-Procedia Computer Science   54  ( 2015 )  756 – 763
-Eleventh International Multi-Conference on Information Processing-2015 (IMCIP-2015)
-Analysis of Attention Identiﬁcation and Recognition of Faces
-through Segmentation and Relative Visual Saliency (SRVS)
-, Jogendra Garain, Goutam Sanyal and Dakshina Ranjan Kisku
-Ravi Kant Kumar
-Computer Science and Engineering Department, National Institute of Technology, Durgapur, India"
 dbaf89ca98dda2c99157c46abd136ace5bdc33b3,Nonlinear Cross-View Sample Enrichment for Action Recognition,"Nonlinear Cross-View Sample Enrichment for
 Action Recognition
 Ling Wang, Hichem Sahbi
@@ -54849,10 +46332,6 @@ dbb0a527612c828d43bcb9a9c41f1bf7110b1dc8,Machine Learning Techniques for Face An
 Machine Learning Techniques
 for Face Analysis
 Roberto Valenti, Nicu Sebe, Theo Gevers, and Ira Cohen"
-dbb7b563e84903dad4953a8e9f23e3c54c6d7e78,Joint Person Re-identification and Camera Network Topology Inference in Multiple Cameras,"Joint Person Re-identiﬁcation and Camera Network
-Topology Inference in Multiple Cameras
-Yeong-Jun Cho, Su-A Kim*, Jae-Han Park*, Kyuewang Lee, Student Member, IEEE
-nd Kuk-Jin Yoon, Member, IEEE"
 db227f72bb13a5acca549fab0dc76bce1fb3b948,Characteristic Based Image Search Using Re-Ranking Method,"International Refereed Journal of Engineering and Science (IRJES)
 ISSN (Online) 2319-183X, (Print) 2319-1821
 Volume 4, Issue 6 (June 2015), PP.169-169-174
@@ -54918,20 +46397,6 @@ Multiple Instance Support Vector Machines
 Nuno Barroso Monteiro1,2, Jo˜ao Pedro Barreto2, and Jos´e Gaspar1
 Institute for Systems and Robotics (ISR/IST), LARSyS, Univ. of Lisbon, Portugal
 Institute for Systems and Robotics, Univ. of Coimbra, Portugal"
-31f1c4cf34ce0bb35382c35b2f468cf72bffae0b,Are spatial and global constraints really necessary for segmentation?,"Are Spatial and Global Constraints Really Necessary for Segmentation?
-Aur´elien Lucchi1
-Yunpeng Li1
-Computer Vision Laboratory, EPFL, Lausanne
-Xavier Boix2
-Kevin Smith1
-Pascal Fua1
-BIWI, ETH Zurich"
-31d007eda3aca9c5114559ddd1f80c5275f3a84f,A Suitable Adaptive Illumination Compensation Method for Face Detection,"Proceedings of the 2nd International Conference on Industrial Application Engineering 2014
-A Suitable Adaptive Illumination Compensation Method for Face
-Detection
-Liu Yong-Jun*,    Xie Cong-Hua
-Department of Computer Science and Engineering,Changshu Institute of Technology, Changshu 215500,China
-* Corresponding Author:"
 318ee553c61888f2418280cb1d342c698d3444c9,Towards face unlock: on the difficulty of reliably detecting faces on mobile phones,"Towards Face Unlock: On the Difﬁculty of Reliably
 Detecting Faces on Mobile Phones
 Rainhard D. Findling
@@ -54944,10 +46409,6 @@ Department for Mobile Computing
 Upper Austria University of Applied Sciences
 Department for Mobile Computing
 Upper Austria University of Applied Sciences"
-31a2fb63a3fc67da9932474cda078c9ac43f85c5,Kernel Methods on Riemannian Manifolds with Gaussian RBF Kernels,"Kernel Methods on Riemannian Manifolds with
-Gaussian RBF Kernels
-Sadeep Jayasumana, Student Member, IEEE, Richard Hartley, Fellow, IEEE,
-Mathieu Salzmann, Member, IEEE, Hongdong Li, Member, IEEE, and Mehrtash Harandi, Member, IEEE"
 3130eb9bfab5e5a095ab989ba3cc6a2ec62c156d,Generating Facial Ground Truth with Synthetic Faces,"Generating Facial Ground Truth with Synthetic Faces
 Rossana Queiroz, Marcelo Cohen, Juliano L. Moreira, Adriana Braun, J´ulio C. Jacques J´unior, Soraia Raupp Musse
 Pontif´ıcia Universidade Cat´olica do Rio Grande do Sul - PUCRS
@@ -55008,11 +46469,6 @@ Ibrahim E. Ziedan
 Dept of Computer and Systems Engineering,
 Professor
 Zagazig University, Sharkia, Egypt"
-312b5c73d79ae80f9f8e4573118d372cf29a80e8,Multiple object video tracking using GRASP-MHT,"Multiple object video tracking using GRASP-MHT
-Xiaoyi Ren
-, Zhipei Huang, Dongyan Liu and Jiankang Wu
-Graduate University of Chinese Academy of Sciences, Beijing, China
-Email: Tel: +86 10 88256015"
 316e67550fbf0ba54f103b5924e6537712f06bee,Multimodal semi-supervised learning for image classification,"Multimodal semi-supervised learning
 for image classiﬁcation
 Matthieu Guillaumin, Jakob Verbeek, Cordelia Schmid
@@ -55063,9 +46519,6 @@ Ali Elqursh
 Google Research
 600 Amphitheater Parkway
 {vahid,"
-318e7e6daa0a799c83a9fdf7dd6bc0b3e89ab24a,Sparsity in Dynamics of Spontaneous Subtle Emotions: Analysis and Application,"Sparsity in Dynamics of Spontaneous
-Subtle Emotions: Analysis & Application
-Anh Cat Le Ngo, Member, IEEE, John See, Member, IEEE, Raphael C.-W. Phan, Member, IEEE"
 3107486fe666a3004b720125bd2b05ff9382fdb8,Generalized two-dimensional linear discriminant analysis with regularization,"JOURNAL OF LATEX CLASS FILES, VOL.
 , NO.
 Generalized two-dimensional linear discriminant
@@ -55076,9 +46529,6 @@ Mengyue Geng
 Yaowei Wang
 Tao Xiang
 Yonghong Tian"
-31ea778b6f5c9c2653eb2bed307ac7b02bcc6894,Dense error correction via l1-minimization,"IEEE TRANS. ON INFORMATION THEORY, 2009.
-Dense Error Correction via (cid:96)1-Minimization
-John Wright, Member, and Yi Ma, Senior Member."
 3174fceef3cf09ac35e8d1eb4e1b8b73a3b2c713,Unsupervised learning from videos using temporal coherency deep networks,"Computer Vision and Image Understanding
 journal homepage: www.elsevier.com
 Unsupervised learning from videos using temporal coherency deep networks
@@ -55212,10 +46662,6 @@ in Web of Science™ Core Collection (BKCI)
 Interested in publishing with us?
 Contact
 Numbers displayed above are based on latest data collected."
-c7c21e78bdadd1d2d98c43f0be3230e59f008b27,Heterogeneous Face Attribute Estimation: A Deep Multi-Task Learning Approach,"Heterogeneous Face Attribute Estimation:
-A Deep Multi-Task Learning Approach
-Hu Han, Member, IEEE, Anil K. Jain, Fellow, IEEE, Fang Wang,
-Shiguang Shan, Senior Member, IEEE and Xilin Chen, Fellow, IEEE"
 c72914e2e999c99753d1d0058c459af69af6662a,CEREALS - Cost-Effective REgion-based Active Learning for Semantic Segmentation,"MACKOWIAK ET AL.: CEREALS
 CEREALS – Cost-Effective REgion-based
 Active Learning for Semantic Segmentation
@@ -55245,15 +46691,6 @@ Shreyas Saxena
 Jakob Verbeek
 INRIA Grenoble, Laboratoire Jean Kuntzmann"
 c71f71200fc85d9fdbd5b3d8b4b6a9daf5a2b424,Machine Learning for Image Based Motion Capture,"INSTITUTNATIONALPOLYTECHNIQUEDEGRENOBLENum´eroattribu´eparlabiblioth`equeTH`ESEpourobtenirlegradedeDOCTEURDEL’INSTITUTNATIONALPOLYTECHNIQUEDEGRENOBLESp´ecialit´e:Imagerie,VisionetRobotiqueEcoleDoctorale:Math´ematiques,SciencesetTechnologiedel’Informationpr´esent´eeetsoutenuepubliquementparAnkurAgarwalle26Avril2006MachineLearningforImageBasedMotionCaptureDirecteurdeth`ese:M.WilliamTriggsJURYM.RogerMohrPr´esidentM.AndrewZissermanRapporteurM.PascalFuaRapporteurM.WilliamTriggsDirecteurdeth`eseM.PhilipTorrExaminateurTh`esepr´epar´eedanslelaboratoireGRAVIR–IMAGauseinduprojetLEARINRIARhˆone-Alpes,655avenuedel’Europe,38334SaintIsmier,France."
-c78fdd080df01fff400a32fb4cc932621926021f,Robust Automatic Facial Expression Detection Method,"Robust Automatic Facial Expression Detection
-Method
-Institute for Pattern Recognition and Artificial Intelligence/ Huazhong University of Science and Technology, Wuhan,
-Institute for Pattern Recognition and Artificial Intelligence/ Huazhong University of Science and Technology, Wuhan,
-Yan Ouyang
-China
-Nong Sang
-China
-Email:"
 c7f80cd585117ae7028148c38ddce8e63b311ba5,Real-Time Face Detection and Recognition via Local Binary Pattern Plus Sample Selective Biomimetic Pattern Recognition,"IEICE TRANS. INF. & SYST., VOL.E96–D, NO.3 MARCH 2013
 PAPER SpecialSectiononFacePerceptionandRecognition
 Real-Time Face Detection and Recognition via Local Binary
@@ -55511,12 +46948,6 @@ Master Programme in Geomatics
 Supervisor: Dr. Julia Åhlén
 Examiner: Prof. Dr. Bin Jiang
 Assistant examiner: Ding Ma"
-944ea33211d67663e04d0181843db634e42cb2ca,Crystal Loss and Quality Pooling for Unconstrained Face Verification and Recognition.,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015
-Crystal Loss and Quality Pooling for
-Unconstrained Face Veriﬁcation and Recognition
-Rajeev Ranjan, Member, IEEE, Ankan Bansal, Hongyu Xu, Member, IEEE,
-Swami Sankaranarayanan, Member, IEEE, Jun-Cheng Chen, Member, IEEE,
-Carlos D Castillo, Member, IEEE, and Rama Chellappa, Fellow, IEEE"
 940ab36a8b2cdf6cb6a08093bd382ad375717942,Human violence recognition and detection in surveillance videos,"Human Violence Recognition and Detection in Surveillance Videos
 Piotr Bilinski
 nd Francois Bremond
@@ -55562,22 +46993,7 @@ Faculty of Engineering, International Islamic University, Jalan Gombak, 53100 Ku
 USING GAN-BASED CLASSIFICATION
 Komei Sugiura and Hisashi Kawai
 National Institute of Information and Communications Technology, Japan"
-9458c518a6e2d40fb1d6ca1066d6a0c73e1d6b73,A Benchmark and Comparative Study of Video-Based Face Recognition on COX Face Database,"A Benchmark and Comparative Study of
-Video-Based Face Recognition
-on COX Face Database
-Zhiwu Huang, Student Member, IEEE, Shiguang Shan, Senior Member, IEEE,
-Ruiping Wang, Member, IEEE, Haihong Zhang, Member, IEEE,
-Shihong Lao, Member, IEEE, Alifu Kuerban,
-nd Xilin Chen, Senior Member, IEEE"
 94a11b601af77f0ad46338afd0fa4ccbab909e82,"Title of dissertation : EFFICIENT SENSING , SUMMARIZATION AND CLASSIFICATION OF VIDEOS",
-94b9c0a6515913bad345f0940ee233cdf82fffe1,Face Recognition using Local Ternary Pattern for Low Resolution Image,"International Journal of Science and Research (IJSR)
-ISSN (Online): 2319-7064
-Impact Factor (2012): 3.358
-Face Recognition using Local Ternary Pattern for
-Low Resolution Image
-Vikas1, Amanpreet Kaur2
-Research Scholar, CGC Group of Colleges, Gharuan, Punjab, India
-Assistant Professor, Department of Computer Science Engineering, Chandigarh University, Gharuan, Punjab, India"
 94eeae23786e128c0635f305ba7eebbb89af0023,On the Emergence of Invariance and Disentangling in Deep Representations,"Journal of Machine Learning Research 18 (2018) 1-34
 Submitted 01/17; Revised 4/18; Published 6/18
 Emergence of Invariance and Disentanglement
@@ -55674,19 +47090,6 @@ Chen Du1,2, Chunheng Wang1, Cunzhao Shi1, Baihua Xiao1
 Institute of Automation, Chinese Academy of Sciences(CASIA)
 University of Chinese Academy of Sciences(UCAS)
 {duchen2016, chunheng.wang, cunzhao.shi,"
-94826cb68980e3b89118569c93cfd36f3945fa99,Computer face-matching technology using two-dimensional photographs accurately matches the facial gestalt of unrelated individuals with the same syndromic form of intellectual disability,"Dudding-Byth et al. BMC Biotechnology  (2017) 17:90
-DOI 10.1186/s12896-017-0410-1
-Open Access
-R ES EAR CH A R T I C LE
-Computer face-matching technology using
-two-dimensional photographs accurately
-matches the facial gestalt of unrelated
-individuals with the same syndromic form
-of intellectual disability
-Tracy Dudding-Byth1,2,3,11*†
-Susan M. White5,6, John Attia3,4, Han Brunner7, Bert de Vries7, David Koolen7, Tjitske Kleefstra7, Seshika Ratwatte4,8,
-Carlos Riveros3, Steve Brain9 and Brian C. Lovell9,10
-, Anne Baxter1†, Elizabeth G. Holliday3,4, Anna Hackett1,4,11, Sheridan O’Donnell1,"
 940a675de8a48b54bac6b420f551529d2bc53b99,"Advances , Challenges , and Opportunities in Automatic Facial Expression Recognition","Advances, Challenges, and Opportunities in
 Automatic Facial Expression Recognition
 Brais Martinez and Michel F. Valstar"
@@ -55774,26 +47177,6 @@ Queen Mary College, London
 England, UK
 England, UK
 England, UK"
-b37f57edab685dba5c23de00e4fa032a3a6e8841,Towards social interaction detection in egocentric photo-streams,"Towards Social Interaction Detection in Egocentric Photo-streams
-Maedeh Aghaei, Mariella Dimiccoli, Petia Radeva
-University of Barcelona and Computer Vision Centre, Barcelona, Spain
-Recent advances in wearable camera technology have
-led to novel applications in the ﬁeld of Preventive Medicine.
-For some of them, such as cognitive training of elderly peo-
-ple by digital memories and detection of unhealthy social
-trends associated to neuropsychological disorders, social in-
-teraction are of special interest. Our purpose is to address
-this problem in the domain of egocentric photo-streams cap-
-tured by a low temporal resolution wearable camera (2fpm).
-These cameras are suited for collecting visual information
-for long period of time, as required by the aforementioned
-pplications. The major difﬁculties to be handled in this
-ontext are the sparsity of observations as well as the unpre-
-dictability of camera motion and attention orientation due
-to the fact that the camera is worn as part of clothing (see
-Fig. 1). Inspired by the theory of F-formation which is a
-pattern that people tend to follow when interacting [5], our
-proposed approach consists of three steps: multi-faces as-"
 b3d8705d46a1d63b40a76bbcf8822b2e90b3b9ad,Efficient Labelling of Pedestrian Supervisions,"Electronic Letters on Computer Vision and Image Analysis 15(1):77-99, 2016
 Efﬁcient Labelling of Pedestrian Supervisions
 Kyaw Kyaw Htike
@@ -55858,12 +47241,6 @@ Quality Embedding
 Jiangchao Yao, Jiajie Wang,
 Ivor Tsang, Ya Zhang, Jun Sun, Chengqi Zhang, Rui Zhang"
 b32631f456397462b3530757f3a73a2ccc362342,Discriminant Tensor Dictionary Learning with Neighbor Uncorrelation for Image Set Based Classification,Proceedings of the Twenty-Sixth International Joint Conference on Artiﬁcial Intelligence (IJCAI-17)
-b3c398da38d529b907b0bac7ec586c81b851708f,Removing Shadows from Face Images Using ICA,"Face Recognition under Varying Lighting Conditions Using Self Quotient
-Haitao Wang, 2Stan Z Li, 1Yangsheng Wang
-Image
-Institute of Automation, Chinese Academy of
-Sciences, Beijing, 100080, China,
-Email:"
 b32cf547a764a4efa475e9c99a72a5db36eeced6,Mimicry of ingroup and outgroup emotional expressions,"UvA-DARE (Digital Academic Repository)
 Mimicry of ingroup and outgroup emotional expressions
 Sachisthal, M.S.M.; Sauter, D.A.; Fischer, A.H.
@@ -55962,18 +47339,6 @@ Associate Professor,
 School of Computer Engineering
 E-mail:
 August 2010"
-b3ca58539e1407e0fb6b308194234279f78eb1d7,Structure Aligning Discriminative Latent Embedding for Zero-Shot Learning,"GUNE ET AL: STRUCTURE ALIGNING DISCRIMINATIVE LATENT EMBEDDING FOR ZSL 1
-Structure Aligning Discriminative Latent
-Embedding for Zero-Shot Learning
-Omkar Gune
-Biplab Banerjee
-Subhasis Chaudhuri
-Indian Institute of Technology Bombay,
-Mumbai, India
-Indian Institute of Technology Bombay,
-Mumbai, India
-Indian Institute of Technology Bombay,
-Mumbai, India"
 b30bdbad88c72938c476f1ea6827d8b10c300da4,Supervised Mixed Norm Autoencoder for Kinship Verification in Unconstrained Videos,"Supervised Mixed Norm Autoencoder for Kinship
 Veriﬁcation in Unconstrained Videos
 Naman Kohli, Student Member, IEEE, Daksha Yadav, Student Member, IEEE, Mayank Vatsa,
@@ -56045,13 +47410,6 @@ A Label Propagation Approach for
 Predicting Missing Biographic Labels
 in Face-Based Biometric Records
 Thomas Swearingen and Arun Ross"
-3d7a5d1fbec861542631fcb10f58e38f4f51a04c,Face Recognition Application of Blur-Robust Pitta,"International Journal of Science and Research (IJSR)
-ISSN (Online): 2319-7064
-Impact Factor (2012): 3.358
-Face Recognition Application of Blur-Robust
-Pitta Santhosh Kumar1, Ankush Jain2
-M.Tech student, Department of CSE, Anurag Group of Institutions, Hyderabad, India
-Assistant professor, Department of CSE, Anurag Group of Institutions, Hyderabad, India"
 3d8c8acb8c59e9f23f048f44a23f36ffd791cdf5,Visual tracking over multiple temporal scales,"Khan, Muhammad Haris (2015) Visual tracking over
 multiple temporal scales. PhD thesis, University of
 Nottingham.
@@ -56123,12 +47481,6 @@ Knexus Research Corporation;
 74 Waterfront Street Suite 310; National Harbor, MD 20745
 Navy Center for Applied Research in Artiﬁcial Intelligence;
 Naval Research Laboratory (Code 5514); Washington, DC 20375"
-3d6229044f6605604818f39f08c5270a5a132a03,Projective Nonnegative Matrix Factorization based on α-Divergence,"Projective Nonnegative Matrix Factorization based on
--Divergence
-Zhirong Yang and Erkki Oja
-Department of Information and Computer Science∗
-Aalto University School of Science and Technology
-P.O.Box 15400, FI-00076, Aalto, Finland"
 3ddb88f9294e962dfd9c99c5864b2b8690b56d90,Multimodal Image Alignment Through a Multiscale Chain of Neural Networks with Application to Remote Sensing,"Multimodal image alignment
 through a multiscale chain of neural networks
 with application to remote sensing
@@ -56140,18 +47492,11 @@ TAU team, INRIA, LRI, Universit´e Paris-Sud, France"
 Conﬁdential Draft: DO NOT DISTRIBUTE
 Composite-ISA Cores: Enabling Multi-ISA Heterogeneity
 Using a Single ISA"
-3db123d094c7ba33bbd3c4ccbea77e2093ad6174,Online Visual Multi-Object Tracking via Labeled Random Finite Set Filtering,"JOURNAL OF LATEX CLASS FILES, VOL. X, NO. X, X XXXX
-A Labeled Random Finite Set Online
-Multi-Object Tracker for Video Data
-Du Yong Kim, Ba-Ngu Vo, Member, IEEE, and Ba-Tuong Vo, Member, IEEE"
 3df7401906ae315e6aef3b4f13126de64b894a54,Robust learning of discriminative projection for multicategory classification on the Stiefel manifold,"Robust Learning of Discriminative Projection for Multicategory Classiﬁcation on
 the Stiefel Manifold
 Duc-Son Pham and Svetha Venkatesh
 Dept. of Computing, Curtin University of Technology
 GPO Box U1987, Perth, WA 6845, Australia"
-3da12b99cd8040bb374eed160f8016b3fe492967,Multiperson Tracking by Online Learned Grouping Model With Nonlinear Motion Context,"Multi-person Tracking by Online Learned Grouping
-Model with Non-linear Motion Context
-Xiaojing Chen, Zhen Qin, Le An, Member, IEEE, and Bir Bhanu, Fellow, IEEE"
 3d21b7b4f48e614bc2f2b87eb110aa329b7d66d8,Recognizing Human Actions by Using Effective Codebooks and Tracking,"Recognizing Human Actions by using Effective
 Codebooks and Tracking
 Lamberto Ballan, Lorenzo Seidenari, Giuseppe Serra, Marco Bertini and Alberto
@@ -56183,16 +47528,6 @@ in our experiments (aPY-25). In each ﬁgure, attribute groups are enclosed in s
 font labeling the boxes indicate the rationale for the grouping.
 .2 Features
 (see also Sec 3.2 and para on Features in Sec 4 in the paper)"
-3da97d97b12fcf22208c36f471119f33a08d9b6f,Multi-modal Biometric system using ear and face ( 2 D + 3 D ) Modalities,"Multi-modal Biometric system using ear and
-face(2D+3D) Modalities
-M.Pujitha Raj
-Computer Science and engineering
-Amrita University
-Coimbatore, India
-B.Achyut Sarma
-Computer Science and engineering
-Amrita University
-Coimbatore, India"
 3da9a9091cfa8f4bf625829faf7a4c35a8fe91e0,Working memory network alterations in high-functioning adolescents with an autism spectrum disorder.,"PDF hosted at the Radboud Repository of the Radboud University
 Nijmegen
 The following full text is a publisher's version.
@@ -56280,14 +47615,6 @@ Mount Sinai School of Medicine
 (cid:13) IEEE2000
 230 York Avenue, New York, NY 10021
 One Gustave L. Levy Place, New York, NY 10029"
-3d1b0c7e9ef0e31dd635041539e795dc07ebee86,Tracking people in 3D using a bottom-up top-down detector,"Tracking People in 3D Using a Bottom-Up Top-Down Detector
-Luciano Spinello, Matthias Luber and Kai O. Arras
-Social Robotics Lab, University of Freiburg, Germany
-{spinello, luber,"
-3dd1338a5d0aa47fa2aef31654ee1392b8089991,Crowdsourcing the construction of a 3D object recognition database for robotic grasping,"014 IEEE International Conference on Robotics & Automation (ICRA)
-Hong Kong Convention and Exhibition Center
-May 31 - June 7, 2014. Hong Kong, China
-978-1-4799-3685-4/14/$31.00 ©2014 IEEE"
 3d7fce66c1880f4b29171e415cfad57d8b96ced2,Exploiting Ambiguities in the Analysis of Cumulative Matching Curves for Person Re-identification,
 3dad8d0b5185503b3281bdeda10b9904ea19da50,Using probabilistic graphical models to detect dynamic objects for mobile robots by Daniek Brink,"Using probabilistic graphical models to detect
 dynamic objects for mobile robots
@@ -56299,10 +47626,6 @@ Co-promoter:
 Dr C.E. van Daalen
 Prof. B.M. Herbst
 December 2016"
-3d62b2f9cef997fc37099305dabff356d39ed477,Joint Face Alignment and 3D Face Reconstruction with Application to Face Recognition,"Joint Face Alignment and 3D Face
-Reconstruction with Application to Face
-Recognition
-Feng Liu, Qijun Zhao, Member, IEEE, Xiaoming Liu, Member, IEEE and Dan Zeng"
 3d5a1be4c1595b4805a35414dfb55716e3bf80d8,Hidden Two-Stream Convolutional Networks for Action Recognition,"Hidden Two-Stream Convolutional Networks for
 Action Recognition
 Yi Zhu, Zhenzhong Lan, Shawn Newsam, Alexander G. Hauptmann"
@@ -56310,26 +47633,6 @@ Yi Zhu, Zhenzhong Lan, Shawn Newsam, Alexander G. Hauptmann"
 Discovering Attribute Shades of Meaning with the Crowd
 Adriana Kovashka · Kristen Grauman
 Received: date / Accepted: date"
-3d67e97227846f579d1825e00d395d30e17f5d0e,Face and ECG Based Multi-Modal Biometric Authentication,"Face and ECG Based Multi-Modal
-Biometric Authentication
-Ognian Boumbarov1, Yuliyan Velchev1, Krasimir Tonchev1
-nd Igor Paliy2
-Technical University of Soﬁa
-Ternopil National Economic University
-Bulgaria
-Ukraine
-. Introduction
-A biometric system is essentially a pattern recognition system. This system measures
-nd analyses human body physiological characteristics, such as face and facial features,
-ﬁngerprints, eye, retinas, irises, voice patterns or behavioral characteristic for enrollment,
-veriﬁcation or identiﬁcation (Bolle & Pankanti, 1998). Uni-modal biometric systems have
-poor performance and accuracy, and over last few decades the multi-modal biometric systems
-have become very popular. The main objective of multi biometrics is to reduce one or more
-false accept rate, false reject rate and failure to enroll rate. Face Recognition (FR) is still
-onsidered as one of the most challenging problems in pattern recognition. The FR systems
-try to recognize the human face in video sequences as 3D object (Chang et al., 2003; 2005), in
-unconstrained conditions, in comparison to the early attempts of 2D frontal faces in controlled
-onditions. Despite the effort spent on research today there is not a single, clearly deﬁned,"
 3d5b8127ce57279f9fd77d3a24d8034b485163a4,System ( tm ) for Image and Vision Computing Manuscript Draft Manuscript Number : IMAVIS-D16-00270 R 2 Title : Extended three-dimensional rotation invariant local binary patterns,"Elsevier Editorial System(tm) for Image and
 Vision Computing
 Manuscript Draft
@@ -56368,12 +47671,6 @@ Hatﬁeld AL10 9AB, UK
 Margaret Hartnett
 GBG plc
 London E14 9QD, UK"
-3da4fa2365c01f53180050c7d332107089d913c0,Face Recognition Using Parzenfaces,"Face Recognition Using Parzenfaces
-Zhirong Yang and Jorma Laaksonen
-Laboratory of Computer and Information Science ⋆
-Helsinki University of Technology
-P.O. Box 5400, FI-02015 TKK, Espoo, Finland
-{zhirong.yang,"
 3dbb2ca6942eb49538d92823fe22c7475e866ca1,Institutionen för systemteknik Department of Electrical Engineering Examensarbete Autonomous Morphometrics using Depth Cameras for Object Classification and Identification,"Institutionen för systemteknik
 Department of Electrical Engineering
 Examensarbete
@@ -56401,26 +47698,6 @@ Julia Lasserre1, Katharina Rasch1 and Roland Vollgraf
 Zalando Research, Muehlenstr. 25, 10243 Berlin, Germany
 Keywords:
 omputer vision, deep learning, fashion, item recognition, street-to-shop"
-ef3697668eb643de27995827c630cfd029b10c37,Online self-supervised multi-instance segmentation of dynamic objects,"014 IEEE International Conference on Robotics & Automation (ICRA)
-Hong Kong Convention and Exhibition Center
-May 31 - June 7, 2014. Hong Kong, China
-978-1-4799-3685-4/14/$31.00 ©2014 IEEE"
-ef9081d153f96b96183666a5086c63cecf2f33e6,D Face Recognition Using Radon Transform and Symbolic PCA,"International Journal of Electronics and Computer Science Engineering           2342
-Available Online at www.ijecse.org                                                       ISSN- 2277-1956
-D Face Recognition Using Radon Transform and
-Symbolic PCA
-P. S. Hiremath  1, Manjunath Hiremath  2
-2Departmentof Computer Science
-Gulbarga University, Gulbarga-585106
-Karnataka, India"
-efb56e7488148d52d3b8a2dae9f8880b273f4226,"Efficient Facial Representations for Age, Gender and Identity Recognition in Organizing Photo Albums using Multi-output CNN","Ef‌f‌icient Facial Representations for Age, Gender
-nd Identity Recognition in Organizing Photo
-Albums using Multi-output CNN
-Andrey V. Savchenko
-Samsung-PDMI Joint AI Center, St. Petersburg Department of Steklov Institute of
-Mathematics
-National Research University Higher School of Economics
-Nizhny Novgorod, Russia"
 ef73e91b47c0043febed130896f610982fb89976,Layer-Structured 3D Scene Inference via View Synthesis,"Layer-structured 3D Scene Inference
 via View Synthesis
 Shubham Tulsiani1∗, Richard Tucker2, Noah Snavely2
@@ -56446,15 +47723,6 @@ neural networks.
 0.2.1 Neocognitron
 The Neocognitron, developed by Fukushima in the 80 [8], consisted on a multilayered network with"
 ef52f1e2b52fd84a7e22226ed67132c6ce47b829,Online Eye Status Detection in the Wild with Convolutional Neural Networks,
-ef5f604fef0a8bbc7c6f8732db17fb611a39adda,Principle Component Analysis of Low Level Feature Based Face Recognition System,"SHORT PAPER
-Int. J. of Recent Trends in Engineering and Technology, Vol. 2, No. 3, Nov 2009
-Principle Component Analysis of Low Level
-Feature Based Face Recognition System.
-First A. Prof. Deshmukh Sudarshan S.1, Second B. Mrs. Deshmukh Pooja S.2
-Army Institute of Technology, Pune, India
-Email:
-Cognizant Technology Solutions, Pune, India
-Email:"
 ef2084979a3191403c1b8b48f503d06f346afb8f,Une méthode de reconnaissance des expressions du visage basée sur la perception,"Une m´ethode de reconnaissance des expressions du
 visage bas´ee sur la perception
 Rizwan Khan, Alexandre Meyer, Hubert Konik, Saida Bouakaz
@@ -56487,13 +47755,6 @@ S. Nissi Paul and Y. Jayanta Singh
 Dept. Computer Science Engineering and information Technology
 Don Boco College of Engineering and Technology, Assam Don Bosco University
 Guwahati, Assam - India"
-efcedd5750f57f4c7f748783e91918e0f42da61f,Global Haar-Like Features: A New Extension of Classic Haar Features for Efficient Face Detection in Noisy Images,"Global Haar-like Features:
-A New Extension of Classic Haar Features for
-Ef‌f‌icient Face Detection in Noisy Images
-Mahdi Rezaei(cid:63), Hossein Ziaei Nafchi‡, and Sandino Morales†
-(cid:63)The University of Auckland, New Zealand
-Synchromedia Laboratory, ´Ecole de Technologie Sup´erieure, Canada
-The University of Auckland, New Zealand"
 ef42f6584d696513605b424752bd9fed6ed98fa0,Facial Motion Analysis using Clustered Shortest Path Tree Registration,"Author manuscript, published in ""The 1st International Workshop on Machine Learning for Vision-based Motion Analysis - MLVMA’08,
 Marseille : France (2008)"""
 ef4b5bcaad4c36d7baa7bc166bd1712634c7ad71,Towards Spatio-temporal Face Alignment in Unconstrained Conditions,
@@ -56525,49 +47786,9 @@ Dept. of ECE
 Karthikeyan.V
 Assistant Professor,
 Dept. of ECE"
-ef3ef27557fa7ba64ab1f4d89dbdac86c55b760c,Face Verification System based on Integral Normalized Gradient Image(INGI),"International Journal of Computer Applications (0975 – 8887)
-Volume 66– No.9, March 2013
-Face Verification System based on Integral Normalized
-Gradient Image (INGI)
-V. Karthikeyan
-Assistant Professor,
-Department of ECE,
-SVS College of
-Engg,
-M. Divya
-U.G Student,
-Department of ECE,
-SVS College of
-Engg,
-C.K. Chithra
-U.G Student,
-Department of ECE,
-SVS College of
-Engg,
-K. Manju Priya"
 efa65394d0ec5a16ecd57075951016502c541c0d,The Gap of Semantic Parsing: A Survey on Automatic Math Word Problem Solvers,"The Gap of Semantic Parsing: A Survey on Automatic
 Math Word Problem Solvers
 Dongxiang Zhang, Lei Wang, Nuo Xu, Bing Tian Dai and Heng Tao Shen"
-ef940b76e40e18f329c43a3f545dc41080f68748,A Face Recognition and Spoofing Detection Adapted to Visually-Impaired People,"Research Article                                                                                                                              Volume 7 Issue No.3
-ISSN XXXX XXXX © 2017 IJESC
-A Face Recognition and Spoofing Detection Adapted to Visually-
-Impaired People
-Rutuja R. Dengale1, Bhagyashri S. Deshmukh 2, Anuja R. Mahangade3, Shivani V. Ujja inkar4
-K.K Wagh Institute of Engineering and Education Research, Nashik, India
-Depart ment of Co mputer Engineering
-Abstrac t:
-According to estimates by the world Health organization, about 285 million people suffer fro m so me kind of v isual disabilit ies of
-which 39 million are  blind, resulting in  0.7 of the word population. As many v isual impaired peoples in  the word they are  unable
-to recognize the people who is standing in front of them and some peoples who have problem to re me mbe r na me of the person.
-They  can  easily  recognize   the  person  using  this  system.  A   co mputer  vision  technique  and  image  ana lysis  can  help  v isually
-the home using face identification and spoofing detection system. This system also provide feature to add newly  known people
-nd keep records of all peoples visiting their ho me.
-Ke ywor ds: face-recognition, spoofing detection, visually-impaired, system architecture.
-INTRODUCTION
-The  facia l  ana lysis  can  be  used  to  e xtract  very  useful  and
-relevant  information  in   order  to  help  people  with  visual
-impairment in several of  its tasks daily providing them with a
-greater  degree  of  autonomy  and  security.  Facia l  recognition"
 efd308393b573e5410455960fe551160e1525f49,Tracking Persons-of-Interest via Unsupervised Representation Adaptation,"Tracking Persons-of-Interest via
 Unsupervised Representation Adaptation
 Shun Zhang, Jia-Bin Huang, Jongwoo Lim, Yihong Gong, Jinjun Wang,
@@ -56581,21 +47802,6 @@ Emotion recognition from geometric facial patterns
 Krupali Joshi, Pradeep Narwade
 Electronics and Telecommunication, Ksiet, Hingoli, (M S) India
 Email- Email–"
-efa2b259407b5b9171dd085061d05b72b6309eb0,"Egocentric Activity Recognition Using HOG , HOF , MBH and Combined features","International Journal on Future Revolution in Computer Science & Communication Engineering
-Volume: 3 Issue: 8
-_______________________________________________________________________________________________
-74 – 79
-ISSN: 2454-4248
-Egocentric Activity Recognition Using HOG, HOF, MBH and
-Combined features
-K. P. Sanal Kumar
-Research Scholar
-Dept. of CSE
-Annamalai University
-R. Bhavani
-Professor
-Dept. of CSE
-Annamalai University"
 efe208a03e2f75ddcebf8bb0f10b1c0bea4824be,A data set for evaluating the performance of multi-class multi-object video tracking,"A data set for evaluating the performance of multi-class multi-object
 video tracking
 Avishek Chakrabortya, Victor Stamatescua, Sebastien C. Wongb, Grant Wigleya, David Kearneya
@@ -56611,40 +47817,6 @@ Faculty of Information Technology, University of Science – Vietnam National Un
 Van Cu street, HCMc, Vietnam"
 efa08283656714911acff2d5022f26904e451113,Active Object Localization in Visual Situations,"Active Object Localization in Visual Situations
 Max H. Quinn, Anthony D. Rhodes, and Melanie Mitchell"
-ef559d5f02e43534168fbec86707915a70cd73a0,DeepInsight: Multi-Task Multi-Scale Deep Learning for Mental Disorder Diagnosis,"DING, HUO, HU, LU: DEEPINSIGHT
-DeepInsight: Multi-Task Multi-Scale Deep
-Learning for Mental Disorder Diagnosis
-Mingyu Ding1
-Yuqi Huo2
-Jun Hu2
-Zhiwu Lu1
-School of Information
-Renmin University of China
-Beijing, 100872, China
-Beijing Key Laboratory
-of Big Data Management
-nd Analysis Methods
-Beijing, 100872, China"
-ef88a02f9b624fe34f4b20ac7beb9ca4f44afe83,Scale robust IMU-assisted KLT for stereo visual odometry solution,"doi:10.1017/S0263574716000552
-Scale robust IMU-assisted KLT for stereo visual
-odometry solution
-L. Chermak
-, N. Aouf and M. A. Richardson
-Centre of Electronic Warfare, Cranﬁeld University, Shrivenham, SN6 8LA, UK
-E-mails:
-(Accepted July 23, 2016)
-SUMMARY
-We propose a novel stereo visual IMU-assisted (Inertial Measurement Unit) technique that extends
-to large inter-frame motion the use of KLT tracker (Kanade–Lucas–Tomasi). The constrained
-nd coherent inter-frame motion acquired from the IMU is applied to detected features through
-homogenous transform using 3D geometry and stereoscopy properties. This predicts efﬁciently
-the projection of the optical flow in subsequent images. Accurate adaptive tracking windows
-limit tracking areas resulting in a minimum of lost features and also prevent tracking of dynamic
-objects. This new feature tracking approach is adopted as part of a fast and robust visual odometry
-lgorithm based on double dogleg trust region method. Comparisons with gyro-aided KLT and
-variants approaches show that our technique is able to maintain minimum loss of features and low
-omputational cost even on image sequences presenting important scale change. Visual odometry
-solution based on this IMU-assisted KLT gives more accurate result than INS/GPS solution for"
 efef00465e1b2f4003e838e50f9c8fa1c8ffaf3e,SceneNet: A Perceptual Ontology for Scene Understanding,"SceneNet: A Perceptual Ontology for Scene
 Understanding
 Ilan Kadar and Ohad Ben-Shahar
@@ -56665,15 +47837,6 @@ ef4ecb76413a05c96eac4c743d2c2a3886f2ae07,Modeling the importance of faces in nat
 Jin B.a, Yildirim G.a, Lau C.a, Shaji A.a, Ortiz Segovia M.b and S¨usstrunk S.a
 EPFL, Lausanne, Switzerland;
 Oc´e, Paris, France"
-ef2c56cc84f4392d537af740abbfc371d015ef03,3D Pose from Detections,"D Pose from Detections
-Cosimo Rubino
-Marco Crocco
-Alessio Del Bue
-Alessandro Perina
-Vittorio Murino
-Pattern Analysis and Computer Vision Department (PAVIS)
-Istituto Italiano di Tecnologia
-Via Morego 30, 16163 Genova, Italy"
 ef032afa4bdb18b328ffcc60e2dc5229cc1939bc,Attribute-enhanced metric learning for face retrieval,"Fang and Yuan EURASIP Journal on Image and Video
 Processing  (2018) 2018:44
 https://doi.org/10.1186/s13640-018-0282-x
@@ -56717,10 +47880,6 @@ nd Search in Urban Surveillance Videos
 Rogerio Schmidt Feris, Associate Member, IEEE, Behjat Siddiquie, James Petterson,
 Yun Zhai, Associate Member, IEEE, Ankur Datta, Lisa M. Brown, Senior Member, IEEE, and
 Sharath Pankanti, Fellow, IEEE"
-97d1d561362a8b6beb0fdbee28f3862fb48f1380,Age Synthesis and Estimation via Faces: A Survey,"Age Synthesis and Estimation via Faces:
-A Survey
-Yun Fu, Member, IEEE, Guodong Guo, Senior Member, IEEE, and
-Thomas S. Huang, Fellow, IEEE"
 978c6e9c01dd6fa64dd0e357bc750345b06ff6bb,Query-Driven Approach to Face Clustering and Tagging,"Query-Driven Approach to Face
 Clustering and Tagging
 Liyan Zhang, Xikui Wang, Dmitri V. Kalashnikov, Sharad Mehrotra, and Deva Ramanan"
@@ -56754,15 +47913,6 @@ Department of Electrical Engineering
 Link¨oping University
 Link¨oping, Sweden
 e-mail: {tohid, larsson, fredrik, schon,"
-978d9a5251028da5a23fd0aed8234ed22b4918c5,Reduced Eigen Space Dimensionality for Fast Face Recognition,"www.ijemr.net
-ISSN (ONLINE): 2250-0758, ISSN (PRINT): 2394-6962
-Volume-5, Issue-2, April-2015
-International Journal of Engineering and Management Research
-Page Number: 33-39
-Reduced Eigen Space Dimensionality for Fast Face Recognition
-Research Scholar, Department of Computer Science and Applications, Panjab University, Chandigarh, INDIA
-Professor, Department of Computer Science and Applications, Panjab University, Chandigarh, INDIA
-Davoud Aflakian1, M. Syamala Devi2"
 9755554b13103df634f9b1ef50a147dd02eab02f,How Transferable Are CNN-Based Features for Age and Gender Classification?,"How Transferable are CNN-based Features for
 Age and Gender Classification?
 Gökhan Özbulak1, Yusuf Aytar2 and Hazım Kemal Ekenel1"
@@ -56788,19 +47938,6 @@ O.B.  Efremides
 School  of  Web  Media
 Bahrain  Polytechnic
 Isa  Town,  Kingdom  of  Bahrain"
-97ee35db6b389a7bcc4b7975d12dbcd165226aad,Structured Learning of Human Interactions in TV Shows,"Structured Learning
-of Human Interactions in TV Shows
-Alonso Patron-Perez, Member, IEEE, Marcin Marszalek,
-Ian Reid, Member, IEEE, and Andrew Zisserman"
-972ef9ddd9059079bdec17abc8b33039ed25c99c,Novel on understanding How IRIS Recognition works,"International Journal of Innovations in Engineering and Technology (IJIET)
-A Novel on understanding How IRIS
-Recognition works
-Vijay Shinde
-Dept. of Comp. Science
-M.P.M. College, Bhopal, India
-Prof. Prakash Tanwar
-Asst. Professor CSE
-M.P.M. College, Bhopal, India"
 97865d31b5e771cf4162bc9eae7de6991ceb8bbf,Face and Gender Classification in Crowd Video,"Face and Gender Classiﬁcation in Crowd Video
 Priyanka Verma
 IIIT-D-MTech-CS-GEN-13-100
@@ -56868,11 +48005,6 @@ Junming Zhang1, Katherine A. Skinner2, Ram Vasudevan3 and Matthew Johnson-Robers
 High-Order Information
 Puneet K. Dokania1, Aseem Behl2, C. V. Jawahar2, and M. Pawan Kumar1
 Ecole Centrale de Paris1, INRIA Saclay1, IIIT Hyderabad - India2"
-97d811ae99bcbcf9f63c2f447041ab6d74a20b1e,Face recognition using truncated transform domain feature extraction,"The International Arab Journal of Information Technology, Vol. 12, No. 3, May 2015                                                              211
-Face Recognition using Truncated Transform
-Domain Feature Extraction
-Rangan Kodandaram, Shashank Mallikarjun, Manikantan Krishnamuthan, and Ramachandran Sivan
-Department of Electronics and Communication Engineering, M.S. Ramaiah Institute of Technology, India"
 97cf04eaf1fc0ac4de0f5ad4a510d57ce12544f5,"Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyond","manuscript No.
 (will be inserted by the editor)
 Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge,
@@ -56884,9 +48016,6 @@ Zafeiriou4"
 Holistic Multi-modal Memory Network
 for Movie Question Answering
 Anran Wang, Anh Tuan Luu, Chuan-Sheng Foo, Hongyuan Zhu, Yi Tay, Vijay Chandrasekhar"
-97b54703c267deef8c86ab6240c24d76a59864e7,Pixel Objectness: Learning to Segment Generic Objects Automatically in Images and Videos,"Pixel Objectness: Learning to Segment Generic
-Objects Automatically in Images and Videos
-Bo Xiong∗, Suyog Dutt Jain∗, and Kristen Grauman, Member, IEEE"
 970e723404885e94e77780766b39ee951dd7abb3,Multimodal Learning of Geometry-Preserving Binary Codes for Semantic Image Retrieval,"IEICE TRANS. INF. & SYST., VOL.E100–D, NO.4 APRIL 2017
 INVITED PAPER SpecialSectiononAward-winningPapers
 Multimodal Learning of Geometry-Preserving Binary Codes for
@@ -56982,19 +48111,6 @@ Marker Placement to Virtualized Real-Time
 Facial Emotions
 Vasanthan Maruthapillai, Murugappan Murugappan*
 School of Mechatronic Engineering, Universiti Malaysia Perlis, 02600, Ulu Pauh, Arau, Perlis, West Malaysia"
-5db075a308350c083c3fa6722af4c9765c4b8fef,The Novel Method of Moving Target Tracking Eyes Location based on SIFT Feature Matching and Gabor Wavelet Algorithm,"The Novel Method of Moving Target Tracking Eyes
-Location based on SIFT Feature Matching and Gabor
-Wavelet Algorithm
-* Jing Zhang, Caixia Yang, Kecheng Liu
-College of Computer and Information Engineering, Nanyang Institute of Technology,
-Henan Nanyang, 473004, China
-* Tel.: 0086+13838972861
-* E-mail:
-Sensors & Transducers, Vol. 154, Issue 7, July 2013, pp. 129-137
-SSSeeennnsssooorrrsss   &&&   TTTrrraaannnsssddduuuccceeerrrsss
-© 2013 by IFSA
-http://www.sensorsportal.com
-Received: 28 April 2013   /Accepted: 19 July 2013   /Published: 31 July 2013"
 5d09d5257139b563bd3149cfd5e6f9eae3c34776,Pattern recognition with composite correlation fi lters designed with multi-objective combinatorial optimization,"Optics Communications 338 (2015) 77–89
 Contents lists available at ScienceDirect
 Optics Communications
@@ -57151,11 +48267,6 @@ Universidad Politécnica de Baja California, Mexicali, Baja California, Mexico"
 5d14cc415a93e6f3a625ed7794e1fdcf99ea5713,Predicting Face Recognition Performance Using Image Quality,"Predicting Face Recognition Performance Using
 Image Quality
 Abhishek Dutta, Raymond Veldhuis, Senior Member, IEEE and Luuk Spreeuwers,"
-5d7395085f2636dd2b6262bc7f3fef14058f4765,Regularizing Deep Networks by Modeling and Predicting Label Structure,"Regularizing Deep Networks by Modeling and Predicting Label Structure
-Mohammadreza Mostajabi
-Michael Maire
-Gregory Shakhnarovich
-Toyota Technological Institute at Chicago"
 5db4fe0ce9e9227042144758cf6c4c2de2042435,Recognition of Facial Expression Using Haar Wavelet Transform,"INTERNATIONAL JOURNAL OF ELECTRICAL AND ELECTRONIC SYSTEMS RESEARCH, VOL.3, JUNE 2010
 Recognition of Facial Expression Using Haar
 Wavelet Transform
@@ -57163,10 +48274,6 @@ M. Satiyan,  M.Hariharan,  R.Nagarajan
 paper
 features
 investigates"
-5da53a17165fcc64e8fb6e9ca532bfb6d95ff622,RSCM: Region Selection and Concurrency Model for Multi-Class Weather Recognition,"RSCM: Region Selection and Concurrency Model
-for Multi-Class Weather Recognition
-Di Lin, Cewu Lu, Member, IEEE, Hui Huang, Member, IEEE, and Jiaya Jia, Senior Member, IEEE
-ondition"
 5da2ae30e5ee22d00f87ebba8cd44a6d55c6855e,"When facial expressions do and do not signal minds: The role of face inversion, expression dynamism, and emotion type.","This is an Open Access document downloaded from ORCA, Cardiff University's institutional
 repository: http://orca.cf.ac.uk/111659/
 This is the author’s version of a work that was submitted to / accepted for publication.
@@ -57212,28 +48319,6 @@ Computer Science Department – Federal University of Minas Gerais
 Av. Antˆonio Carlos, 6627, Pampulha, CEP 31270–901, Belo Horizonte, MG, Brazil
 Exact and Technological Sciences Department – State University of Santa Cruz
 Rodovia Ilh´eus-Itabuna, km 16 – Pavilh˜ao Jorge Amado, CEP 45600-000, Ilh´eus, BA, Brazil"
-7a2d1ab82eacbc92ec4cedbf2d7432bf0194c6df,Face Spoof Detection System Based on Genetic Algorithm and Artificial Intelligence Technique : A Review,"International Journals of Advanced Research in
-Computer Science and Software Engineering
-ISSN: 2277-128X (Volume-8, Issue-6)
-Research  Article
-Face Spoof Detection System Based on Genetic Algorithm
-nd Artificial Intelligence Technique: A Review
-Diksha Anand, Kamal Gupta(Assistant Professor)
-GNIT Mullana, Ambala, Haryana, India"
-7af667b6c1b4b32f513dd70fe3ef36fcf344a741,A transfer learning based approach for automated grading of Gliomas using deep Residual Networks,"A transfer learning based approach for automated
-grading of Gliomas using deep Residual Networks
-Varghese Alex Kollerathu
-Department of Engineering Design
-Indian Institute of Technology Madras
-Chennai, India
-Chandrasekharan Kesavadas
-Imaging Sciences and Intervention Radiology Department
-Sree Chitra Tirunal Institute for Medical Sciences and Technology
-Trivandrum, India
-Ganapathy Krishnamurthi
-Department of Engineering Design
-Indian Institute of Technology Madras
-Chennai, India"
 7a0fb972e524cb9115cae655e24f2ae0cfe448e0,Facial Expression Classification Using RBF AND Back-Propagation Neural Networks,"Facial Expression Classification Using RBF AND Back-Propagation Neural Networks
 R.Q.Feitosa1,2,
 M.M.B.Vellasco1,2,
@@ -57343,35 +48428,11 @@ Orlando, FL 32
 ker.com
 http://www.enriqueg
 http://www.briancbec"
-7a8ba1a6c90b56ae0a98fe43d015ab0f2a73912e,A Vision-Based Hybrid Method for Eye Detection and Tracking,"A Vision-Based Hybrid Method for Eye Detection and Tracking
-International Journal of Security and Its Applications
-Vol. 7, No. 4, July, 2013
-Kun Mu
-Department of Computer Science and Engineering, Henan Institute of Engineering,
-Zhengzhou 451191, China"
 7af6d86139aa86cb5897904563a9f67c016a176d,Performance of Correlation Filters in Facial Recognition,"Performance of Correlation Filters in Facial
 Recognition
 Everardo Santiago-Ramirez, J.A. Gonzalez-Fraga, and J.I. Ascencio-Lopez
 Facultad de Ciencias, Universidad Autónoma de Baja California, Km. 103, Carretera Tijuana-
 Ensenada, Ensenada, Baja California C. P. 22860"
-7a3676dcf55e22c7249eac7615174309617c8246,Joint Feature Learning With Robust Local Ternary Pattern for Face Recognition,"International Journal of Application or Innovation in Engineering & Management (IJAIEM)
-Web Site: www.ijaiem.org Email:
-ISSN 2319 - 4847
-Volume 5, Issue 6, June  2016
-Joint Feature Learning With Robust Local
-Ternary Pattern for Face Recognition
-Yuvaraju.M1, Shalini.S2
-Nadu, India
-Assistant Professor, Department of Electrical and Electronics Engineering, Anna University Regional Campus, Coimbatore, Tamil
-Pg Scholar, Department of Electrical and Electronics Engineering, Anna University Regional Campus, Coimbatore, Tamil Nadu,
-India"
-7a7db5a1325844b62d2ecf8489872c8f515f1c37,Nuclear Norm-Based 2-DPCA for Extracting Features From Images,"Nuclear Norm-Based 2-DPCA for Extracting
-Features From Images
-Fanlong Zhang, Jian Yang, Member, IEEE, Jianjun Qian, and Yong Xu, Member, IEEE"
-7ac25c5391251611696d16e677bd71040d80d583,Person Re-Identification by Saliency Learning,"MANUSCRIPT DRAFT
-Person Re-identiﬁcation by saliency Learning
-Rui Zhao, Student Member, IEEE, Wanli Oyang, Member, IEEE, and
-Xiaogang Wang, Member, IEEE"
 7a81967598c2c0b3b3771c1af943efb1defd4482,Do We Need More Training Data?,"Do We Need More Training Data?
 Xiangxin Zhu · Carl Vondrick · Charless C. Fowlkes · Deva Ramanan"
 7a7a53b05e22305b2963c05ac89830e099146767,Assessing fish abundance from underwater video using deep neural networks,"Assessing ﬁsh abundance from underwater video
@@ -57429,11 +48490,6 @@ ISSN: 2321-0869, Volume-2, Issue-8, August 2014
 Fusion of Silhouette Based Gait Features for Gait
 Recognition
 Mohan Kumar H P,  Nagendraswamy H S"
-7ad204758df6c921010d9967a5b7449dd406ea56,Deep Face Quality Assessment,"Deep Face Quality Assessment
-Vishal Agarwal
-Department of Electronics and Electrical Engineering
-Indian Institute of Technology Guwahati
-India"
 7acc05ae92823c12b28d6ad73cb2a7707ccb6c7b,Single view-based 3D face reconstruction robust to self-occlusion,"Lee et al. EURASIP Journal on Advances in Signal Processing 2012, 2012:176
 http://asp.eurasipjournals.com/content/2012/1/176
 R ES EAR CH
@@ -57457,12 +48513,6 @@ Centre d’Excellence en Troubles Envahissants du De´veloppement de l’Univers
 Neural Systems Group, Massachusetts General Hospital, Boston, Massachusetts
 (CETEDUM), Montre´al, QC, Canada"
 a92b5234b8b73e06709dd48ec5f0ec357c1aabed,Disjoint Multi-task Learning Between Heterogeneous Human-Centric Tasks,
-a996492cad4ee17945f6b8ba06ae87cf38223242,Memetic Approach for Matching Sketches with Digital Face Images,"SUBMITTED TO IEEE TRANSACTIONS ON PAMI
-Memetic Approach for Matching Sketches with
-Digital Face Images
-Himanshu S. Bhatt, Student Member, IEEE, Samarth Bharadwaj, Student Member, IEEE, Richa
-Singh, Member, IEEE, Mayank Vatsa, Member, IEEE.
-face images. Structural"
 a93781e6db8c03668f277676d901905ef44ae49f,Recent Data Sets on Object Manipulation: A Survey.,"Recent Datasets on Object Manipulation: A Survey
 Yongqiang Huang, Matteo Bianchi, Minas Liarokapis and Yu Sun"
 a91d0ebc1255d6de1c4588767b3b5e1fc630e56f,FBI-HH-M-345 / 10 eTRIMS Scene Interpretation Datasets,"Universit¨at Hamburg
@@ -57476,9 +48526,6 @@ Kasim Terzi´c
 {hartz | koopmann |
 informatik.uni-hamburg.de
 November 15, 2010"
-a9ebeca46445b8af728118b05e56d95d4985000c,Restricted Isometry Property of Subspace Projection Matrix Under Random Compression,"Restricted Isometry Property of Subspace Projection
-Matrix Under Random Compression
-Xinyue Shen, Student Member, IEEE, and Yuantao Gu, Member, IEEE"
 a9978df0b4df4d7b04bc4e9464c67f9ff7c31d3d,FROM TRADITIONAL TO INTERACTIVE PLAYSPACES FROM TRADITIONAL TO INTERACTIVE PLAYSPACES FROM TRADITIONAL TO INTERACTIVE PLAYSPACES Automatic Analysis of Player Behavior in the Interactive Tag Playground,"FROM TRADITIONAL TO
 FROM TRADITIONAL TO
 INTERACTIVE PLAYSPACES
@@ -57502,11 +48549,6 @@ Irina Higgins, Loic Matthey, Arka Pal, Christopher Burgess, Xavier Glorot,
 Matthew Botvinick, Shakir Mohamed, Alexander Lerchner
 Google DeepMind
 {irinah,lmatthey,arkap,cpburgess,glorotx,"
-a969efee78149357ec109c1de2238a0cc670858a,Automatic 2.5-D Facial Landmarking and Emotion Annotation for Social Interaction Assistance,"Automatic 2.5-D Facial Landmarking and Emotion
-Annotation for Social Interaction Assistance
-Xi Zhao, Member, IEEE, Jianhua Zou, Member, IEEE, Huibin Li, Student Member, IEEE,
-Emmanuel Dellandréa, Member, IEEE, Ioannis A. Kakadiaris, Senior Member, IEEE,
-nd Liming Chen, Senior Member, IEEE"
 a975f1aea5dbb748955da0e17eef8d2270a49f25,Object Recognition Sensory Data Acquisition Light Intensity Images,"OBJECT RECOGNITION
 Object recognition is a subproblem of the more general
 problem of perception, and can be deﬁned as follows. Given
@@ -57527,17 +48569,6 @@ for bin picking, inspection, and mobile robotics.
 Various types of object recognition problems can be
 stated based on the dimensionality of their spatial descrip-
 tion: (1) recognition of a 2-D object from a single 2-D im-"
-a955033ca6716bf9957b362b77092592461664b4,Video Based Face Recognition Using Artificial Neural Network,"ISSN(Online): 2320-9801
-ISSN (Print):  2320-9798
-International Journal of Innovative Research in Computer
-nd Communication Engineering
-(An ISO 3297: 2007 Certified Organization)
-Video Based Face Recognition Using Artificial
-Vol. 3, Issue 6, June 2015
-Neural Network
-Santhy Mol T, Neethu Susan Jacob
-Pursuing M.Tech, Dept. of CSE, Caarmel Engineering College, MG University, Kerala, India
-Assistant Professor, Dept of CSE, Caarmel Engineering College, MG University, Kerala, India"
 a9f03e4bb90addab234423994bfd8c25854484ea,OBJECT BASED IMAGE RETRIEVAL USING LBP AND FUZZY CLUSTERING METHOD,"Volume1, Issue 3, 15 May- 15 August 2015
 International Journal In Applied Studies And
 Production Management
@@ -57548,13 +48579,6 @@ Jiwanjot kaur Bhinder
 Department of Computer Science & Engg, RIMT(IET) Mandigobindgarh
 Kirti joshi
 Department of Computer Science & Engg, RIMT(IET) Mandigobindgarh"
-a99cf14afb556187233f772fa9bf561d7cf0c088,A SURVEY ON SCLERA VEIN RECOGNITION TECHNIQUES,"INTERNATIONAL JOURNAL OF ADVANCED RESEARCH IN COMPUTER SCIENCE AND APPLICATIONS
-ISSN 2321-872X ONLINE ISSN 2321-8932 PRINT
-VOLUME  2, ISSUE 12, DECEMBER 2014.
-A SURVEY ON SCLERA VEIN RECOGNITION TECHNIQUES
-Dr.S.BABU 1        S.SUBA 2
-Associate Professor / CSE, IFET College of Engineering, Viluppuram, Tamilnadu, India
-PG Scholar, IFET College of Engineering, Viluppuram, Tamilnadu, India"
 a9453721f35f364e176a5aaa7bdb622f72fbcaec,Learning Articulated Motion Models from Visual and Lingual Signals,"Learning Articulated Motion Models from Visual and Lingual Signals
 Zhengyang Wu
 Georgia Tech
@@ -57568,20 +48592,6 @@ Chicago, IL 60637"
 a9286519e12675302b1d7d2fe0ca3cc4dc7d17f6,Learning to Succeed while Teaching to Fail: Privacy in Closed Machine Learning Systems,"Learning to Succeed while Teaching to Fail:
 Privacy in Closed Machine Learning Systems
 Jure Sokoli´c, Qiang Qiu, Miguel R. D. Rodrigues, and Guillermo Sapiro"
-a93ecf7b9780989c709714dde0f93f4d81eea640,Unconstrained Face Recognition Using SVM Across Blurred And Illuminated Images With Pose,"International Journal of Innovative Research in Computer and Communication Engineering
-(An ISO 3297: 2007 Certified Organization)
-Vol.2, Special Issue 1, March 2014
-Proceedings of International Conference On Global Innovations In Computing Technology (ICGICT’14)
-Department of CSE, JayShriram Group of Institutions, Tirupur, Tamilnadu, India on 6th & 7th March 2014
-Organized by
-Unconstrained Face Recognition Using SVM
-Across Blurred And Illuminated Images With Pose
-Variation
-Nadeena M1, S.Sangeetha, M.E, 2
-ISSN(Online): 2320-9801
-ISSN (Print):  2320-9798
-II M.E CSE, Dhanalakshmi Srinivasan College of Engineering, Coimbatore, India1
-Assistant Professor, Dhanalakshmi Srinivasan College of Engineering, Coimbatore, India 2"
 a9eb6e436cfcbded5a9f4b82f6b914c7f390adbd,A Model for Facial Emotion Inference Based on Planar Dynamic Emotional Surfaces,"(IJARAI) International Journal of Advanced Research in Artificial Intelligence,
 Vol. 5, No.6, 2016
 A Model for Facial Emotion Inference Based on
@@ -57782,29 +48792,6 @@ A Recursive Framework for Expression Recognition: From
 Web Images to Deep Models to Game Dataset
 Wei Li · Christina Tsangouri · Farnaz Abtahi · Zhigang Zhu
 Received: date / Accepted: date"
-df2494da8efa44d70c27abf23f73387318cf1ca8,Supervised Filter Learning for Representation Based Face Recognition,"RESEARCH ARTICLE
-Supervised Filter Learning for Representation
-Based Face Recognition
-Chao Bi1, Lei Zhang2, Miao Qi1, Caixia Zheng1, Yugen Yi3, Jianzhong Wang1*,
-Baoxue Zhang4*
-College of Computer Science and Information Technology, Northeast Normal University, Changchun,
-China, 2 Changchun Institute of Optics, Fine Mechanics and Physics, CAS, Changchun, China, 3 School of
-Software, Jiangxi Normal University, Nanchang, China, 4 School of Statistics, Capital University of
-Economics and Business, Beijing, China
-11111
-* (JW); (BZ)"
-df8da144a695269e159fb0120bf5355a558f4b02,Face Recognition using PCA and Eigen Face Approach,"International Journal of Computer Applications (0975 – 8887)
-International Conference on Recent Trends in engineering & Technology - 2013(ICRTET'2013)
-Face Recognition using PCA and Eigen Face
-Approach
-Anagha A. Shinde
-ME EXTC [VLSI & Embedded System]
-Sinhgad Academy of Engineering
-EXTC Department
-Pune, India"
-df80fed59ffdf751a20af317f265848fe6bfb9c9,Learning Deep Sharable and Structural Detectors for Face Alignment,"Learning Deep Sharable and Structural
-Detectors for Face Alignment
-Hao Liu, Jiwen Lu, Senior Member, IEEE, Jianjiang Feng, Member, IEEE, and Jie Zhou, Senior Member, IEEE"
 df310591dfba9672252d693bc87da73c246749c9,Fusion of Holistic and Part Based Features for Gender Classification in the Wild,"Fusion of Holistic and Part Based Features
 for Gender Classiﬁcation in the Wild
 Modesto Castrill´on-Santana(B), Javier Lorenzo-Navarro,
@@ -57846,20 +48833,6 @@ Beijing  ·  Cambridge  ·  Farnham  ·  Köln  ·  Sebastopol  ·  Taipei  ·
 dfe7700ed053d4788ecea4a18431806581e03291,Grammatical facial expression recognition using customized deep neural network architecture,"Grammatical facial expression recognition using customized
 deep neural network architecture
 Devesh Walawalkar"
-dfd2a3cfb8250ff39de498105d3f31122f314811,Content Based Image Retrieval of Corel Images Along With Face Recognition,"Deepa Joseph et al, International Journal of Computer Science and Mobile Computing, Vol.4 Issue.11, November- 2015, pg. 136-142
-Available Online at www.ijcsmc.com
-International Journal of Computer Science and Mobile Computing
-A Monthly Journal of Computer Science and Information Technology
-ISSN 2320–088X
-IJCSMC, Vol. 4, Issue. 11, November 2015, pg.136 – 142
-RESEARCH ARTICLE
-Content Based Image Retrieval of Corel
-Images Along With Face Recognition
-Deepa Joseph1, Ajai Mathew2
-¹Student, Department of Electronics and Communication Engineering
-Amal Jyothi College of Engineering, Kanjirappally, India
-²Assistant Professor, Department of Electronics and Communication Engineering
-Amal Jyothi College of Engineering, Kanjirappally, India"
 df8aee8aef6f0c71f968979318dafcd53da04bdc,Bending the Curve: Improving the ROC Curve Through Error Redistribution,"Bending the Curve: Improving the ROC Curve Through Error
 Redistribution
 Oran Richman
@@ -57934,17 +48907,6 @@ of autistic language include echolalia (echoing the utterances of others),
 pronoun reversal, idiosyncratic language use and neologisms (the creation
 of new words), difficulty with pragmatics (problems interpreting the use
 of language in context and the non-literal use of language), and abnormal"
-df51dfe55912d30fc2f792561e9e0c2b43179089,Face Hallucination Using Linear Models of Coupled Sparse Support,"Face Hallucination using Linear Models of Coupled
-Sparse Support
-Reuben A. Farrugia, Member, IEEE, and Christine Guillemot, Fellow, IEEE
-grid and fuse them to suppress the aliasing caused by under-
-sampling [5], [6]. On the other hand, learning based meth-
-ods use coupled dictionaries to learn the mapping relations
-etween low- and high- resolution image pairs to synthesize
-high-resolution images from low-resolution images [4], [7].
-The research community has lately focused on the latter
-ategory of super-resolution methods, since they can provide
-higher quality images and larger magniﬁcation factors."
 dfbf49ed66a9e48671964872c84f75d7f916c131,Supplementary Material for Sparsity Invariant CNNs,"Supplementary Material for
 Sparsity Invariant CNNs
 Jonas Uhrig(cid:63),1,2 Nick Schneider(cid:63),1,3
@@ -57993,22 +48955,12 @@ Tengda Han
 Jue Wang
 Anoop Cherian
 Stephen Gould"
-dfee9e83ccf015a3835c399beda5d57d49d25d04,Road side video surveillance in traffic scenes using mapreduce framework for accident analysis,"Biomedical Research 2016; Special Issue: : S257-S266
-ISSN 0970-938X
-www.biomedres.info
-Road side video surveillance in traffic scenes using map-reduce framework
-for accident analysis.
-Maha Vishnu VC*, Rajalakshmi M
-Department of Computer Science and Engineering and Information Technology, Coimbatore Institute of Technology,
-Coimbatore, India"
 dfcb4773543ee6fbc7d5319b646e0d6168ffa116,Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks,"Unifying Variational Autoencoders and Generative Adversarial Networks
 Adversarial Variational Bayes:
 Lars Mescheder 1
 Sebastian Nowozin 2
 Andreas Geiger 1 3"
 df353e3a46cca8c1ef274994f5a6dcb580231726,Data-driven fundamental models for pedestrian movements THÈSE,"POUR L'OBTENTION DU GRADE DE DOCTEUR ÈS SCIENCESacceptée sur proposition du jury:Prof. P. Frossard, président du juryProf. M. Bierlaire, directeur de thèseProf. H. Mahmassani, rapporteurProf. S. Hoogendoorn, rapporteurProf. N. Geroliminis, rapporteurData-driven fundamental models for pedestrian movementsTHÈSE NO 7613 (2017)ÉCOLE POLYTECHNIQUE FÉDÉRALE DE LAUSANNEPRÉSENTÉE LE 5 MAI 2017À LA FACULTÉ DE L'ENVIRONNEMENT NATUREL, ARCHITECTURAL ET CONSTRUITLABORATOIRE TRANSPORT ET MOBILITÉPROGRAMME DOCTORAL EN GÉNIE ÉLECTRIQUE Suisse2017PARMarija NIKOLIĆ"
-dfaa547451aae219cd2ca7a761e6c16c1e1d0add,Representation Learning by Rotating Your Faces,"Representation Learning by Rotating Your Faces
-Luan Tran, Xi Yin, and Xiaoming Liu, Member, IEEE"
 df577a89830be69c1bfb196e925df3055cafc0ed,"Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions","Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions
 Bichen Wu, Alvin Wan∗, Xiangyu Yue∗, Peter Jin, Sicheng Zhao,
 Noah Golmant, Amir Gholaminejad, Joseph Gonzalez, Kurt Keutzer
@@ -58033,10 +48985,6 @@ Recognition by Probabalistic Hypothesis Construction
 P. Moreels and M. Maire and P. Perona [13]
 • Extension of Perona’s work, simplifying model.
 Human Detection Based on a Probabalistic Assembly of Robust Part Detectors"
-dfb342327c5e883d21a1f91cd283b36dbc2a3661,Game of Sketches: Deep Recurrent Models of Pictionary-Style Word Guessing,"Deep Recurrent Models of Pictionary-style Word
-Guessing
-Ravi Kiran Sarvadevabhatla, Member, IEEE, Shiv Surya, Trisha Mittal and R. Venkatesh Babu Senior
-Member, IEEE"
 dfd18b71f5c53ec2a95fcbe327cf7710da3b4851,Robust Submodular Maximization: A Non-Uniform Partitioning Approach,"Robust Submodular Maximization:
 A Non-Uniform Partitioning Approach
 Ilija Bogunovic 1 Slobodan Mitrovi´c 2 Jonathan Scarlett 1 Volkan Cevher 1"
@@ -58092,11 +49040,6 @@ Universit´e de Lyon, CNRS, ´Ecole Centrale de Lyon
 LIRIS UMR5205, F-69134 Lyon, France
 Univ. Grenoble Alpes, Inria, CNRS
 Grenoble INP, LIG, F-38000 Grenoble, France"
-ca8b529e389381c8b51ddf83788b7a3eafb8f859,Efficient CNN Implementation for Eye-Gaze Estimation on Low-Power/Low-Quality Consumer Imaging Systems,"Efﬁcient CNN Implementation for Eye-Gaze
-Estimation on Low-Power/Low-Quality Consumer
-Imaging Systems
-Joseph Lemley, Student Member, IEEE, Anuradha Kar, Student Member, IEEE, Alexandru
-Drimbarean, Member, IEEE, and Peter Corcoran, Fellow, IEEE"
 ca400e0c7a739ce5555b2e3eccccbcea65e71b11,Neural Mechanisms of Emotion Regulation in Autism Spectrum Disorder.,"J Autism Dev Disord
 DOI 10.1007/s10803-015-2359-z
 S I : E M O T I O N R E G U L A T I O N A N D P S Y C H I A T R I C C O M O R B I D I T Y I N A S D
@@ -58137,10 +49080,6 @@ Review
 Advanced Communication & Signal Processing Laboratory, Department of Electronics & Communication
 engineering, Government College of Engineering Kannur, Kerala, India.
 Rishin C. K, Aswani Pookkudi, A. Ranjith Ram"
-ca1db9dc493a045e3fadf8d8209eaa4311bbdc70,Effective Image Retrieval via Multilinear Multi-index Fusion,"JOURNAL OF LATEX CLASS FILES, VOL. XX, NO. X, JUNE 2017
-Effective Image Retrieval via Multilinear
-Multi-index Fusion
-Zhizhong Zhang, Yuan Xie, Member, IEEE, Wensheng Zhang, Qi Tian, Fellow, IEEE,"
 cae87d5a724507e06f6d8178cfbec043db854fe3,Bayesian Nonparametric Latent Feature Models,"Bayesian Nonparametric Latent Feature Models
 Kurt Miller
 Electrical Engineering and Computer Sciences
@@ -58180,23 +49119,6 @@ Department of Informatics
 Box 451
 54124 Thessaloniki, Greece
 email:"
-ca05fadeb6e0d3414fd21870320545be4582e408,Deep Part-Based Generative Shape Model with Latent Variables,"KIRILLOV ET AL.: DEEP PART-BASED GENERATIVE SHAPE MODEL
-Deep Part-Based Generative Shape Model
-with Latent Variables
-Alexander Kirillov1
-Mikhail Gavrikov2
-Ekaterina Lobacheva4
-Anton Osokin3
-Dmitry Vetrov4
-TU Dresden,
-Dresden, Germany
-Rubbles,
-Moscow, Russia
-INRIA – École Normale Supérieure,
-Paris, France
-National Research University
-Higher School of Economics (HSE),
-Moscow, Russia"
 cad52d74c1a21043f851ae14c924ac689e197d1f,From Ego to Nos-Vision: Detecting Social Relationships in First-Person Views,"From Ego to Nos-vision:
 Detecting Social Relationships in First-Person Views
 Stefano Alletto, Giuseppe Serra, Simone Calderara, Francesco Solera and Rita Cucchiara
@@ -58216,34 +49138,6 @@ Author: Juli´an Fi´errez Aguilar
 A Thesis submitted for the degree of:
 Doctor of Philosophy
 Madrid, May 2006"
-ca50d76d065b22bf40d8144729f89e36e732e046,Robust Face Recognition and Impostors Detection with Partial Occlusion and Small Number of Training Samples ⋆,"Journal of Information & Computational Science 9: 1 (2012) 1–14
-Available at http://www.joics.com
-Robust Face Recognition and Impostors Detection with
-Partial Occlusion and Small Number of Training
-Samples ⋆
-Yujie Hao a, Jie Lin a;b;∗
-, Jianping Li a, Ji Ming b
-School of Computer Science and Engineering, University of Electronic Science and Technology of
-China, Chengdu 610054, China
-School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast
-Belfast BT7 1NN, UK"
-cac24ea3b301c4aba0f84470b175198c10d03199,Study of the Changing Trends in Facial Expression Recognition,"International Journal of Computer Applications (0975 – 8887)
-Volume 21– No.5, May 2011
-Study of the Changing Trends in Facial
-Expression Recognition
-Dr. S. Ravi
-Department of Computer Science,
-School of Engineering and Technology
-Pondicherry University
-Pudhucherry, India
-Mahima S
-Centre for Information Technology and
-Engineering
-Manonmaniam Sundarnar University
-Tirunelveli, India"
-ca5e9973a4494c608548f639eb9a391f6235d4f0,Robust RGB-D Face Recognition Using Attribute-Aware Loss,"Robust RGB-D Face Recognition Using
-Attribute-Aware Loss
-Luo Jiang, Juyong Zhang†, Member, IEEE, and Bailin Deng, Member, IEEE"
 ca228b42de0f0311f4826292a2996d3348ca43fe,Modeling and Inferring Human Intents and Latent Functional Objects for Trajectory Prediction,"FOR REVIEW: IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
 Modeling and Inferring Human Intents and Latent
 Functional Objects for Trajectory Prediction
@@ -58297,10 +49191,6 @@ Dipl.-math. Christian Joachim Herdtweck
 vorgelegt von
 us Stuttgart
 Tübingen"
-cadb9a014a4c5bbec57aaf30391f472fa4b69b4d,PCA versus LDA,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 23, NO. 2, FEBRUARY 2001
-PCA versus LDA
-Aleix M. Martı´nez, Member, IEEE, and
-Avinash C. Kak"
 ca1accedbc1c698c03e9835d9f960c40e9d3ef51,Implementing a Cloud Platform for Autonomous Driving,"Implementing a Cloud Platform for Autonomous Driving
 Shaoshan Liu, Jie Tang, Chao Wang, Quan Wang, and Jean-Luc Gaudiot, Fellow, IEEE
 unified
@@ -58311,11 +49201,6 @@ infrastructure"
 ca494a2f20c267210a677ed9c509c4570f420fdf,Learning to Globally Edit Images with Textual Description,"Learning to Globally Edit Images
 with Textual Description
 Hai Wang † Jason D. Williams ‡ Sing Bing Kang §"
-cab372bc3824780cce20d9dd1c22d4df39ed081a,"DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs","DeepLab: Semantic Image Segmentation with
-Deep Convolutional Nets, Atrous Convolution,
-nd Fully Connected CRFs
-Liang-Chieh Chen, George Papandreou, Senior Member, IEEE, Iasonas Kokkinos, Member, IEEE,
-Kevin Murphy, and Alan L. Yuille, Fellow, IEEE"
 ca8dc160836a87055579ea9bc4fc379a95f3156a,Face Recognition Based on Nonlinear DCT Discriminant Feature Extraction Using Improved Kernel DCV,"IEICE TRANS. INF. & SYST., VOL.E92–D, NO.12 DECEMBER 2009
 LETTER
 Face Recognition Based on Nonlinear DCT Discriminant Feature
@@ -58363,12 +49248,6 @@ information. However, it is registered with the shape channel, and intensity
 an now be associated with shape attributes such as the surface normal.
 The shape channel does not suffer from certain problems that the texture"
 21b0b2f5df87318912d58d3b843da363a4fb91c3,"Distributed and Higher-Order Graphical Models: towards Segmentation, Tracking, Matching and 3D Model Inference Defended by","ECOLECENTRALEPARISPHDTHESIStoobtainthetitleofDoctorofEcoleCentraleParisSpecialty:APPLIEDMATHEMATICSDistributedandHigher-OrderGraphicalModels:towardsSegmentation,Tracking,Matchingand3DModelInferenceDefendedbyChaohuiWANGpreparedatEcoleCentraleParis,MASlaboratorydefendedonSeptember29,2011JURYChairman:Prof.HenriMAITRE-TélécomParisTechReviewers:Prof.MichaelJ.BLACK-MaxPlanckInstituteforIntelligentSystemsProf.PhilipH.S.TORR-OxfordBrookesUniversityAdvisor:Prof.NikosPARAGIOS-EcoleCentraleParisExaminers:Prof.PatrickBOUTHEMY-INRIA-RennesProf.VladimirKOLMOGOROV-InstituteofScienceandTechnologyAustriaProf.DimitrisSAMARAS-StonyBrookUniversity"
-21e82350472bf6a12af0f761b8dea91cb16bf42f,Cost-Sensitive Convolution based Neural Networks for Imbalanced Time-Series Classification,"Cost-Sensitive Convolution based Neural
-Networks for Imbalanced Time-Series
-Classification
-Yue Geng* and Xinyu Luo
-Mechanical and Electrical Engineering Institute of CUMTB, Beijing, 100083, China
-E-mail:"
 21ac5d1c34675bf6056d2670f9fa3dde530b1716,ALB at SemEval-2018 Task 10: A System for Capturing Discriminative Attributes,"Proceedings of the 12th International Workshop on Semantic Evaluation (SemEval-2018), pages 963–967
 New Orleans, Louisiana, June 5–6, 2018. ©2018 Association for Computational Linguistics"
 218595e1979007ccd6b1bc5a30a3484841c0eafa,Discovering Beautiful Attributes for Aesthetic Image Analysis,"Noname manuscript No.
@@ -58376,10 +49255,6 @@ New Orleans, Louisiana, June 5–6, 2018. ©2018 Association for Computational L
 Discovering beautiful attributes for aesthetic image analysis
 Luca Marchesotti · Naila Murray · Florent Perronnin
 Received: date / Accepted: date"
-218603147709344d4ff66625d83603deee2854bf,Learning Deep Embeddings with Histogram Loss,"Learning Deep Embeddings with Histogram Loss
-Evgeniya Ustinova and Victor Lempitsky
-Skolkovo Institute of Science and Technology (Skoltech)
-Moscow, Russia"
 21262e01039e5994114b4c102fc80e9afa3f1bde,Pedestrian Detection and Tracking in Thermal Images from Aerial MPEG Videos,
 2118b1ce0c2551e75d30fb6ba24482e50b319a90,Ensemble Projection for Semi-supervised Image Classification,"Ensemble Projection for Semi-supervised Image Classiﬁcation
 Dengxin Dai
@@ -58412,26 +49287,6 @@ Triplet Loss Function
 De Cheng, Yihong Gong, Sanping Zhou, Jinjun Wang, Nanning Zheng
 Institute of Artiﬁcial Intelligence and Robotics
 Xi’an Jiaotong University,Xi’an, Shaanxi, P.R. China"
-219b7b157f2a559ecdffe21c2a0edf5285931298,Deep hashing for compact binary codes learning,"Deep Hashing for Compact Binary Codes Learning
-Venice Erin Liong1, Jiwen Lu1, Gang Wang1,2, Pierre Moulin1,3, and Jie Zhou4
-ADSC, Singapore, 2NTU, Singapore, 3UIUC, USA, 4Tsinghua University, China
-Large scale visual search has attracted great attention in computer vision
-due to its wide potential applications [1]. Hashing is a powerful technique
-for large-scale visual search and a variety of hashing-based methods have
-een proposed in the literature [3, 4, 7]. The basic idea of hashing-based
-pproach is to construct a series of hash functions to map each visual object
-into a binary feature vector so that visually similar samples are mapped into
-similar binary codes.
-In this paper, we propose a new deep hashing (DH) method to learn
-ompact binary codes for large scale visual search. Figure 1 illustrates the
-asic idea of the proposed approach. Different from most existing binary
-odes learning methods which usually seek a single linear projection to map
-each sample into a binary vector [2, 5, 6], we develop a deep neural network
-to seek multiple hierarchical non-linear transformations to learn these bina-
-ry codes. For a given sample xn, we obtain a binary vector bn by passing
-it to a network which contains multiple stacked layers of nonlinear trans-
-formations. Assume we have M + 1 layers, the output for the mth layer is:
-n = s(Wmhm−1"
 2198a3d3342442d6ed6608f2e2b0687f644b67d6,Dynamic High Resolution Deformable Articulated Tracking,"Dynamic High Resolution
 Deformable Articulated Tracking
 Aaron Walsman
@@ -58451,14 +49306,6 @@ Simulation, Faculty of Medicine, University of Porto, Porto, Portugal, 4 Departm
 Diabetes and Metabolism, Centro Hospitalar Sāo Joāo, Faculty of Medicine, University of Porto, Porto,
 Portugal, 5 Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
 11111"
-21f59ece2dfe0181a3c4763318fcae254e80b7db,Human Object Tracking in Video Sequences,"S. SARAVANAKUMAR et.al. : HUMAN OBJECT TRACKING IN VIDEO SEQUENCES
-DOI: 10.21917/ijivp.2011.0039
-HUMAN OBJECT TRACKING IN VIDEO SEQUENCES
-S. Saravanakumar1, A. Vadivel2 and C.G. Saneem Ahmed3
-, 2Department of Computer Applications, National Institute of Technology, Tiruchirappalli, Tamil Nadu, India
-E-mail:
-Department of Electronics and Communication Engineering, National Institute of Technology, Tiruchirappalli, Tamil Nadu, India
-E-mail:"
 21241d07840e3cc30feda59642571a9b459c817b,Biometrics via Oculomotor Plant Characteristics: Impact of Parameters in Oculomotor Plant Model,"This is a pre-print. Final version of the paper will be available at ACM digital library.
 Biometrics via Oculomotor Plant Characteristics:
 Impact of Parameters in Oculomotor Plant Model
@@ -58526,11 +49373,6 @@ to  demonstrate
 lustering,  but
 locality-sensitive  hashing
 the  proposed  method  can"
-214ac8196d8061981bef271b37a279526aab5024,Face Recognition Using Smoothed High-Dimensional Representation,"Face Recognition Using Smoothed High-Dimensional
-Representation
-Juha Ylioinas, Juho Kannala, Abdenour Hadid, and Matti Pietik¨ainen
-Center for Machine Vision Research, PO Box 4500,
-FI-90014 University of Oulu, Finland"
 21b16df93f0fab4864816f35ccb3207778a51952,Recognition of Static Gestures Applied to Brazilian Sign Language (Libras),"Recognition of Static Gestures applied to Brazilian Sign Language (Libras)
 Igor L. O. Bastos
 Math Institute
@@ -58666,17 +49508,6 @@ Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horiz
 Email:"
 72ecaff8b57023f9fbf8b5b2588f3c7019010ca7,Facial Keypoints Detection,"Facial Keypoints Detection
 Shenghao Shi"
-72a55554b816b66a865a1ec1b4a5b17b5d3ba784,Real-Time Face Identification via CNN and Boosted Hashing Forest,"Real-Time Face Identification
-via CNN
-nd Boosted Hashing Forest
-Yury Vizilter, Vladimir Gorbatsevich, Andrey Vorotnikov and Nikita Kostromov
-State Research Institute of Aviation Systems (GosNIIAS), Moscow, Russia
-IEEE Computer Society Workshop on Biometrics
-In conjunction with CVPR 2016, June 26, 2016"
-726f76f11e904d7fcb12736c276a0b00eb5cde49,A Performance Comparison of Loss Functions for Deep Face Recognition,"A Performance Comparison of Loss Functions for
-Deep Face Recognition
-Computer Vision Group, Indian Institute of Information Technology, Sri City, India
-Yash Srivastava∗, Vaishnav Murali† and Shiv Ram Dubey‡"
 72944b4266523effe97708bff89e1d57d6aebf50,Multisensory Versus Unisensory Integration : Contrasting Modes in the Superior Colliculus,"A Multi-Sensory, Automated and Accelerated
 Sensory Integration Program
 The Research
@@ -58885,18 +49716,9 @@ Xuelin Qian1 Yanwei Fu2,5,* Yu-Gang Jiang1,3 Tao Xiang4 Xiangyang Xue1,2
 Shanghai Key Lab of Intelligent Info. Processing, School of Computer Science, Fudan University;
 School of Data Science, Fudan University; 3Tencent AI Lab;
 Queen Mary University of London; 5University of Technology Sydney;"
-72fb849144aea8e01f141419914cde87bb7972f3,Fuzzy Bidirectional Weighted Sum for Face Recognition,"The Open Automation and Control Systems Journal, 2014, 6, 447-452
-Send Orders for Reprints to
-Fuzzy Bidirectional Weighted Sum for Face Recognition
-Open Access
-Pengli Lu and Xingbin Jiang*
-School of Computer and Communication, Lanzhou University of Technology, Lanzhou, 730050, China"
 72591a75469321074b072daff80477d8911c3af3,Group Component Analysis for Multiblock Data: Common and Individual Feature Extraction,"Group Component Analysis for Multi-block Data:
 Common and Individual Feature Extraction
 Guoxu Zhou, Andrzej Cichocki Fellow, IEEE, Yu Zhang, and Danilo Mandic Fellow, IEEE"
-725b4d2ae7de22856200d1e4511e1d697d42b37b,The ParallelEye Dataset: Constructing Large-Scale Artificial Scenes for Traffic Vision Research,"The ParallelEye Dataset: Constructing Large-Scale
-Artiﬁcial Scenes for Trafﬁc Vision Research
-Xuan Li, Kunfeng Wang, Member, IEEE, Yonglin Tian, Lan Yan, and Fei-Yue Wang, Fellow, IEEE"
 72a6044a0108e0f8f1e68cd70ada46c81a416324,Improved Training of Generative Adversarial Networks Using Representative Features,"Improved Training of Generative Adversarial Networks
 using Representative Features
 Duhyeon Bang 1 Hyunjung Shim 1"
@@ -59057,20 +49879,6 @@ Accepted: August 2, 2017"
 0322e69172f54b95ae6a90eb3af91d3daa5e36ea,Face Classification using Adjusted Histogram in Grayscale,"Face Classiﬁcation using Adjusted Histogram in
 Grayscale
 Weenakorn Ieosanurak, and Watcharin Klongdee"
-0394acc70f58fbb6326d1fbf44e0a6da5a0345d1,Automated Recognition of Text in Images : A Survey,"International Journal of Computer Applications (0975 – 8887)
-Volume 127 – No.15, October 2015
-Automated Recognition of Text in Images: A Survey
-Kanika Wadhawan
-M.Tech Scholar
-E. Gajendran, PhD
-Research Guide
-Christ University, Faculty of Engineering
-Christ University, Faculty of Engineering
-Bengaluru, India"
-031532cc5c4e64e02e796360a16f89580a0ba552,Nonnegative Decompositions for Dynamic Visual Data Analysis,"Nonnegative Decompositions for
-Dynamic Visual Data Analysis
-Lazaros Zafeiriou, Member, IEEE, Yannis Panagakis, Member, IEEE,
-Maja Pantic, Fellow, IEEE, and Stefanos Zafeiriou, Member, IEEE"
 036a8cb922a30d766b0fc0ba5954098a1d2a09f5,Learning Similarities for Rigid and Non-rigid Object Detection,"Learning Similarities for Rigid and Non-Rigid Object Detection
 Asako Kanezaki
 The Univ. of Tokyo
@@ -59125,21 +49933,11 @@ Tete Xiao Gang Yu Xiangyu Zhang
 Jian Sun
 {shaoshuai, zhaozijian, liboxun, xtt, yugang, zhangxiangyu,
 Megvii Inc. (Face++)"
-03ed6f09a29fe5d0dbf6d59798f88a5311c966d3,Re-identification with RGB-D Sensors,"Re-identi(cid:12)cation with RGB-D sensors
-Igor Barros Barbosa1;3, Marco Cristani1;2, Alessio Del Bue1,
-Loris Bazzani1, and Vittorio Murino1
-Pattern Analysis and Computer Vision (PAVIS) - Istituto Italiano di Tecnologia
-(IIT), Via Morego 30, 16163 Genova, Italy
-Dipartimento di Informatica, University of Verona,
-Strada Le Grazie 15, 37134 Verona, Italy
-Universit(cid:19)e de Bourgogne, 720 Avenue de lEurope, 71200 Le Creusot, France"
 035ef7b25991b0f7ea841a2270ed053198aab09e,"Retrieval of Images with Objects of Specific Size, Location, and Spatial Configuration","Retrieval of images with objects of speciﬁc size, location and spatial conﬁguration
 Niloufar Pourian
 B.S. Manjunath
 Department of Electrical and Computer Engineering
 University of California, Santa Barbara, United States"
-03f7041515d8a6dcb9170763d4f6debd50202c2b,Clustering Millions of Faces by Identity,"Clustering Millions of Faces by Identity
-Charles Otto, Student Member, IEEE, Dayong Wang, Member, IEEE, and Anil K. Jain, Fellow, IEEE"
 0332ae32aeaf8fdd8cae59a608dc8ea14c6e3136,Large Scale 3D Morphable Models,"Int J Comput Vis
 DOI 10.1007/s11263-017-1009-7
 Large Scale 3D Morphable Models
@@ -59212,22 +50010,6 @@ C ONVOLUTIONAL NETWORKS (ConvNets) trace back
 to the early works on digit and character recognition
 [11], [23]. Prior to 2012, though, in computer vision ﬁeld,
 neural networks were more renowned for their propensity to"
-0342029ad13c337ef09b1413229a8945c0aebdd9,Collarette Region Recognition based on Wavelets and Direct Linear Discriminant Analysis,"International Journal of Computer Applications (0975 – 8887)
-Volume 40– No.9, February 2012
-Collarette Region Recognition based on Wavelets and
-Direct Linear Discriminant Analysis
-Akanksha Joshi
-Abhishek Gangwar
-Zia Saquib
-Center for Development of
-Advanced Computing
-Mumbai, India
-Center for Development of
-Advanced Computing
-Mumbai, India
-Center for Development of
-Advanced Computing
-Mumbai, India"
 03a8f53058127798bc2bc0245d21e78354f6c93b,Max-margin additive classifiers for detection,"Max-Margin Additive Classiﬁers for Detection
 Subhransu Maji and Alexander C. Berg
 Sam Hare
@@ -59282,10 +50064,6 @@ Expression and Gesture Data"
 Ramazan Gokberk Cinbis
 Jakob Verbeek Cordelia Schmid
 Inria∗"
-031d22b08d9e8235f46679b89e273ab8723d3e67,Zero-Aliasing Correlation Filters for Object Recognition,"Zero-Aliasing Correlation Filters for Object
-Recognition
-Joseph A. Fernandez, Student Member, IEEE, Vishnu Naresh Boddeti, Member, IEEE, Andres Rodriguez,
-Member, IEEE, B. V. K. Vijaya Kumar, Fellow, IEEE"
 03c56c176ec6377dddb6a96c7b2e95408db65a7a,A Novel Geometric Framework on Gram Matrix Trajectories for Human Behavior Understanding,"A Novel Geometric Framework on Gram Matrix
 Trajectories for Human Behavior Understanding
 Anis Kacem, Mohamed Daoudi, Boulbaba Ben Amor, Stefano Berretti, and Juan Carlos Alvarez-Paiva"
@@ -59365,11 +50143,6 @@ Michael Klostermann
 Dietrich Paulus
 Active Vision Group, University of Koblenz-Landau, 56070 Koblenz, Germany
 {mhaeselich, michaelk,"
-03c53fb96a9acd2ec6ba52a2497410f980793bfa,Trainable Convolution Filters and Their Application to Face Recognition,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication.
-Trainable Convolution Filters and their
-Application to Face Recognition
-Ritwik Kumar, Member, IEEE, Arunava Banerjee, Member, IEEE,
-Baba C. Vemuri, Fellow, IEEE, and Hanspeter Pﬁster, Senior Member, IEEE"
 0315c68902edca77d2c15cfc1f1335d55343c715,Towards optimal distortion-based visual privacy filters,"TOWARDS OPTIMAL DISTORTION-BASED VISUAL PRIVACY FILTERS
 Pavel Korshunov and Touradj Ebrahimi
 Multimedia Signal Processing Group, EPFL, Lausanne, Switzerland"
@@ -59401,14 +50174,6 @@ Institute International, Kyoto 619-0288, Japan; E-Mails: (F.Z.); (T.I.);
 Tel.: +81-774-95-1405.
 Received: 14 December 2012; in revised form: 20 December 2012 / Accepted: 4 January 2013 /
 Published: 14 January 2013"
-034516f37171e7e6cffb8afa84c1f5d6d12d887f,Comparative Analysis of Content Based Image Retrieval using Texture Features for Plant Leaf Diseases,"International Journal of Applied Engineering Research ISSN 0973-4562 Volume 11, Number 9 (2016) pp6244-6249
-© Research India Publications.  http://www.ripublication.com
-Comparative Analysis of Content Based Image Retrieval using Texture
-Features for Plant Leaf Diseases
-Ph.D. Scholar, Bharati Vidyapeeth Deemed University College of Engineering Pune, Maharashtra, India
-Jayamala K.Patil
-Professor, Defense Institute of Advanced Tech., Deemed University, Girinagar
-Raj Kumar"
 038b8b2b629a8ba1e2ad6f9319e16b68e83e518a,Assessing Water Stress of Desert Tamarugo Trees Using in situ Data and Very High Spatial Resolution Remote Sensing,"Remote Sens. 2013, 5, 5064-5088; doi:10.3390/rs5105064
 OPEN ACCESS
 ISSN 2072-4292
@@ -59428,26 +50193,6 @@ Av. Salamanca s/n, Rengo, Chile
 Tel.: +31-317-481-552; Fax: +31-317-419-000.
 Received: 24 July 2013; in revised form: 12 September 2013 / Accepted: 9 October 2013 /
 Published: 15 October 2013"
-0394e684bd0a94fc2ff09d2baef8059c2652ffb0,Median Robust Extended Local Binary Pattern for Texture Classification,"Median Robust Extended Local Binary Pattern
-for Texture Classiﬁcation
-Li Liu, Songyang Lao, Paul W. Fieguth, Member, IEEE, Yulan Guo,
-Xiaogang Wang, and Matti Pietikäinen, Fellow, IEEE
-Index Terms— Texture descriptors, rotation invariance, local
-inary pattern (LBP), feature extraction, texture analysis.
-how the texture recognition process works in humans as
-well as in the important role it plays in the wide variety of
-pplications of computer vision and image analysis [1], [2].
-The many applications of texture classiﬁcation include medical
-image analysis and understanding, object recognition, biomet-
-rics, content-based image retrieval, remote sensing, industrial
-inspection, and document classiﬁcation.
-As a classical pattern recognition problem, texture classiﬁ-
-ation primarily consists of two critical subproblems: feature
-extraction and classiﬁer designation [1], [2]. It is generally
-greed that the extraction of powerful texture features plays a
-relatively more important role, since if poor features are used
-even the best classiﬁer will fail to achieve good recognition
-results. Consequently, most research in texture classiﬁcation"
 03ae36b2ed0215b15c5bc7d42fbe20b1491e551a,Learning scene-specific pedestrian detectors without real data,"Learning Scene-Speciﬁc Pedestrian Detectors without Real Data
 Hironori Hattori1, Vishnu Naresh Boddeti2, Kris Kitani2, Takeo Kanade2
 Sony Corporation. 2Carnegie Mellon University.
@@ -59492,26 +50237,6 @@ DEEP MODELS CALIBRATION WITH BAYESIAN NEURAL
 NETWORKS
 Anonymous authors
 Paper under double-blind review"
-cb310356d1c5f567b2a8796b708f6e1e10fa1917,Serotonin and the neural processing of facial emotions in adults with autism: an fMRI study using acute tryptophan depletion.,"ORIGINAL ARTICLE
-Serotonin and the Neural Processing
-of Facial Emotions in Adults With Autism
-An fMRI Study Using Acute Tryptophan Depletion
-Eileen M. Daly, BA; Quinton Deeley, PhD; Christine Ecker, MSc, PhD; Michael Craig, PhD; Brian Hallahan, MRCPsych;
-Clodagh Murphy, MRCPsych; Patrick Johnston, PhD; Debbie Spain, MSc; Nicola Gillan, MSc; Michael Brammer, PhD;
-Vincent Giampietro, PhD; Melissa Lamar, PhD; Lisa Page, MRCPsych; Fiona Toal, MRCPsych; Anthony Cleare, PhD;
-Simon Surguladze, MD, PhD; Declan G. M. Murphy, FRCPsych
-Context: People with autism spectrum disorders (ASDs)
-have lifelong deficits in social behavior and differences
-in behavioral as well as neural responses to facial expres-
-sions of emotion. The biological basis to this is incom-
-pletely understood, but it may include differences in the
-role of neurotransmitters such as serotonin, which modu-
-late facial emotion processing in health. While some in-
-dividuals with ASD have significant differences in the sero-
-tonin system, to our knowledge, no one has investigated
-its role during facial emotion processing in adults with
-ASD and control subjects using acute tryptophan deple-
-tion (ATD) and functional magnetic resonance imaging."
 cbca355c5467f501d37b919d8b2a17dcb39d3ef9,Super-resolution of Very Low Resolution Faces from Videos,"CANSIZOGLU, JONES: SUPER-RESOLUTION OF VERY LR FACES FROM VIDEOS
 Super-resolution of Very Low-Resolution
 Faces from Videos
@@ -59549,35 +50274,11 @@ Sanping Zhou, Jinjun Wang, Rui Shi, Qiqi Hou, Yihong Gong, Nanning Zheng"
 cbdca5e0f1fd3fd745430497d372a2a30b7bb0c5,Towards Distributed Coevolutionary GANs,"Towards Distributed Coevolutionary GANs
 Abdullah Al-Dujaili, Tom Schmiedlechner, Erik Hemberg and Una-May O’Reilly
 CSAIL, MIT, USA"
-cb004e9706f12d1de83b88c209ac948b137caae0,Face Aging Effect Simulation Using Hidden Factor Analysis Joint Sparse Representation,"Face Aging Effect Simulation using Hidden Factor
-Analysis Joint Sparse Representation
-Hongyu Yang, Student Member, IEEE, Di Huang, Member, IEEE, Yunhong Wang, Member, IEEE, Heng Wang,
-nd Yuanyan Tang, Fellow, IEEE"
 cb7bbede1c2eae831dd73440f439955c4310837f,Cross-Cultural and Cultural-Specific Production and Perception of Facial Expressions of Emotion in the Wild,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015
 Cross-Cultural and Cultural-Speciﬁc Production
 nd Perception of Facial Expressions of Emotion
 in the Wild
 Ramprakash Srinivasan, Aleix M. Martinez"
-cb2e10d1a6792354bc0ce24ee99ecf2142d16f9b,Enhancing Real-Time Human Detection Based on Histograms of Oriented Gradients,"Enhancing Real-time Human Detection based
-on Histograms of Oriented Gradients
-Marco Pedersoli1, Jordi Gonz`alez2, Bhaskar Chakraborty1, and Juan J.
-Villanueva1
-Computer Vision Center and Departament d’Inform`atica. Universitat Aut`onoma
-de Barcelona, 08193 Bellaterra, Spain
-Institut de Rob`otica i Inform`atica Industrial(UPC-CSIC), Ediﬁci U Parc
-Tecnol`ogic de Barcelona. 08028, Spain.
-Summary. In this paper we propose a human detection framework based on an
-enhanced version of Histogram of Oriented Gradients (HOG) features. These feature
-descriptors are computed with the help of a precalculated histogram of square-blocks.
-This novel method outperforms the integral of oriented histograms allowing the
-alculation of a single feature four times faster. Using Adaboost for HOG feature
-selection and Support Vector Machine as weak classiﬁer, we build up a real-time
-human classiﬁer with an excellent detection rate.
-Introduction
-Human detection is the task of ﬁnding presence and position of human beings
-in images. Many applications take advantage of it, mainly in the videosurvel-
-liance and human-computer iteration domains. Thus, human detection is the
-ﬁrst step of the full process of Human Sequence Evaluation [5]."
 cb6be69c67b0b15ebbda89a126f4dd62a4d32958,Igure Qa : a N a Nnotated F Igure D Ataset for V Isual R Easoning,"Workshop track - ICLR 2018
 FIGUREQA: AN ANNOTATED FIGURE DATASET FOR
 VISUAL REASONING
@@ -59625,26 +50326,6 @@ Evangello Flouty1, Odysseas Zisimopoulos1, and Danail Stoyanov1,2
 Wellcome / ESPRC Centre for Interventional and Surgical Sciences, London,
 Digital Surgery, London, United Kingdom
 United Kingdom"
-cb3ba84146d1324e1cdbde3764ca3b354ee09a2a,"On the Interplay Between Throughput, Fairness and Energy Efficiency on Asymmetric Multicore Processors","On the interplay between throughput,
-fairness and energy ef‌f‌iciency on
-symmetric multicore processors
-J. C. Saez1, A. Pousa2, A. E. de Giusti2, M. Prieto-Matias1
-ArTeCS Group, Facultad de Inform´atica, Complutense University of Madrid
-III-LIDI, Facultad de Inform´atica, National University of La Plata
-Email:
-Asymmetric single-ISA multicore processors (AMPs), which integrate high-
-performance big cores and low-power small cores, were shown to deliver
-higher performance per watt than symmetric multicores. Previous work has
-highlighted that this potential of AMP systems can be realizable by scheduling
-the various applications in a workload on the most appropriate core type. A
-number of scheduling schemes have been proposed to accomplish different goals,
-such as system throughput optimization, enforcing fairness or reducing energy
-onsumption. While the interrelationship between throughput and fairness on
-AMPs has been comprehensively studied, the impact that optimizing energy
-ef‌f‌iciency has on the other two aspects is still unclear. To ﬁll this gap, we carry out
-comprehensive analytical and experimental study that illustrates the interplay
-etween throughput, fairness and energy ef‌f‌iciency on AMPs. Our analytical
-study allowed us to deﬁne the energy-ef‌f‌iciency factor (EEF) metric, which aids"
 cb658e9e0823dc7afe66b593307b230cc2747790,Nouveau modèle pour la datation automatique de photographies à partir de caractéristiques visuelles,"Nouveau modèle pour la datation
 utomatique de photographies
 à partir de caractéristiques visuelles1
@@ -59663,10 +50344,6 @@ relle. Dans leur approche soit une prédiction est bonne (période valide) soit
 plusieurs. Nos travaux, s’appuient sur des avancées récentes en classiﬁcation ordinale. Nous
 onsidérons les dates comme des attributs à la fois ordonnés et relatifs et nous proposons un
 adre spéciﬁque pour les manipuler."
-cb08f679f2cb29c7aa972d66fe9e9996c8dfae00,Action Understanding with Multiple Classes of Actors,"JOURNAL OF LATEX CLASS FILES, VOL. 13, NO. 9, SEPTEMBER 2014
-Action Understanding
-with Multiple Classes of Actors
-Chenliang Xu, Member, IEEE, Caiming Xiong, and Jason J. Corso, Senior Member, IEEE"
 cb76c7002b9a813405359b2bc2a29756bf426bb4,Combination of In Vogue Algorithms for Human Detection and Tracking,"International Journal of Computer Applications (0975 – 8887)
 National Conference “Electronics, Signals, Communication and Optimization"" (NCESCO 2015)
 Combination of In Vogue Algorithms for Human
@@ -59702,17 +50379,6 @@ Hang Chu1,2 Wei-Chiu Ma3 Kaustav Kundu1,2 Raquel Urtasun1,2,3 Sanja Fidler1,2
 University of Toronto 2Vector Institute 3Uber ATG
 {chuhang1122, kkundu,
 {weichiu,"
-cb53c8a85d58ccb2635be5b7ff978ea6e8b78cde,Face Recognition Based on Wavelet Transform and Regional Directional Weighted Local Binary Pattern,"Face Recognition Based on Wavelet Transform
-nd Regional Directional Weighted Local Binary
-Pattern
-Wu Fengxiang
-North China Career Academy of Water Resources, Henan Zhengzhou, China
-Email:
-independent  application  technology  area"
-cbd20c2199062724eee841016f1575cb7d5309b4,Dropout training for SVMs with data augmentation,"JOURNAL OF LATEX CLASS FILES, VOL. X, NO. X, MAY 2015
-Dropout Training for SVMs with
-Data Augmentation
-Ning Chen and Jun Zhu, Member, IEEE, Jianfei Chen and Ting Chen"
 cb3d38cd18c99aca9c2a228aeb4998f394c7b1b3,Impairments in facial affect recognition associated with autism spectrum disorders: a meta-analysis.,"# Cambridge University Press 2014
 doi:10.1017/S0954579414000479
 Impairments in facial affect recognition associated with autism
@@ -59798,13 +50464,6 @@ If you consider content in White Rose Research Online to be in breach of UK law,
 emailing including the URL of the record and the reason for the withdrawal request.
 https://eprints.whiterose.ac.uk/"
 a85007fe09e96e13cc30992ba19d71cae75634c6,BlazeIt : An OptimizingQuery Engine for Video at Scale Extended Abstract,BlazeIt: An Optimizing Query Engine for Video at Scale
-a84032e66db042a57722b4a3bc7301ebe567fb8b,A Face Recognition Technique using Principal Component Analysis,"IJSRD - International Journal for Scientific Research & Development| Vol. 3, Issue 01, 2015 | ISSN (online): 2321-0613
-Review of Energy Enhancements of Modified LEACH
-Kirti Sharma1
-Department of Electronics & Communication Engineering
-Maharishi Ved Vyas Engineering College, Jagadhri, India
-using
-minimized"
 a83fc450c124b7e640adc762e95e3bb6b423b310,Deep Face Feature for Face Alignment and Reconstruction,"Deep Face Feature for Face Alignment
 Boyi Jiang, Juyong Zhang, Bailin Deng, Yudong Guo and Ligang Liu"
 a887937b813f267507203d4faef1013043cf09d0,Automatic Process to Build a Contextualized Detector,"AUTOMATIC PROCESS TO BUILD A CONTEXTUALIZED
@@ -59835,42 +50494,11 @@ ackground  modeling,  pedestrian  detection,  real-time
 pplications, video surveillance applications.
 Manuscript received May 22, 2014; revised Jan. 1, 2015; accepted Jan. 17, 2015.
 This work was partly supported by the ICT R&D program of the MSIP, Rep. of Korea (No."
-a8f032b300b99dedb9c0f8362557302696d5ee9a,Intelligent Video Object Classification Scheme using Offline Feature Extraction and Machine Learning based Approach,"Intelligent Video Object Classification Scheme using Offline Feature Extraction and
-Machine Learning based Approach
-Chandra Mani Sharma1, Alok Kumar Singh Kushwaha2 ,Rakesh Roshan3 , Rabins Porwal4 and Ashish Khare5
-,3,4Department of Information Technology, Institute of Technology and Science
-Ghaziabad, U.P., India
-Department of Computer Engg. and Application, G.L.A. University,
-Mathura, U.P., India
-5 Department of Electronics and Communication, University of Allahabad,
-U.P., India"
-a8117a4733cce9148c35fb6888962f665ae65b1e,A Good Practice Towards Top Performance of Face Recognition: Transferred Deep Feature Fusion,"IEEE TRANSACTIONS ON XXXX, VOL. XX, NO. XX, XX 201X
-A Good Practice Towards Top Performance of Face
-Recognition: Transferred Deep Feature Fusion
-Lin Xiong1∗†, Jayashree Karlekar1∗, Jian Zhao2∗†, Jiashi Feng2, Member, IEEE, Sugiri Pranata1, and
-Shengmei Shen1"
 a8bf49021017e19df051a3efb7337d93ea263e37,Deep Multiple Instance Hashing for Object-based Image Retrieval,"Proceedings of the Twenty-Sixth International Joint Conference on Artiﬁcial Intelligence (IJCAI-17)
 queryRetrieval ResultFigure1:Queryingaboutmultipleobjects.toryresults.Inparticular,theerrorsinthesegmentationstepwillbepropagatedtotheindex,anditisdifﬁculttoﬁndop-timalhand-craftedfeaturesforindexcreation.Ontheotherhand,mostexistingobject-basedimageretrievalapproachesconcentrateonqueryingbyasingleobject.However,usersmayalsowanttoqueryaboutmultipleobjects,asillustratedinFig.1:intheupperexampletheuserisinterestedinpho-toscontainingbothhumanandhorses,asinthequery;inthelowercasetheusermaywanttowriteapoliticalcommentaryaboutObamaandPutinbutthereisnogroupphotoofthemathand.Duetothelackofabilitytodetectvariousobjects,previousapproacheswillincurpoorperformancewhentheyaredirectlyusedtocopewithmulti-objectqueries.Recentadvancesindeeplearninghaveprovedthatconvo-lutionalneuralnetworks(CNNs)trainedend-to-endcanlearnpowerfulfeaturerepresentations.Intermsofobjectdetec-tion,anumberoftechniquesbasedondeepCNNshavebeenproposed[Renetal.,2015;Liuetal.,2016]andachievedgoodresultsonsomehigh-qualitypublicimagedatasetslikeImageNet,PASCALVOCandMSCOCO.However,theseapproachesnecessitatelarge-scaletrainingdatawithlabelsofobjectlocationstolearnmodelstoharvest“objectness”,whereasthelabelingworkisverytediousandexpensive.Itisoftenthecasethatweonlyhaveimage-levelobjectlabelswithoutobjectlocations,i.e.weaklabelsforobjectdetection"
 a81d396c9210282d461f9f08b7b9794b096ecdfe,FFDNet: Toward a Fast and Flexible Solution for CNN-Based Image Denoising,"FFDNet: Toward a Fast and Flexible Solution for
 CNN based Image Denoising
 Kai Zhang, Wangmeng Zuo, Senior Member, IEEE, and Lei Zhang, Fellow, IEEE"
-a843bc90343ceeb25b59f6e54de3663e363f5fd3,Learning to predict where to look in interactive environments using deep recurrent q-learning,"LEARNING TO PREDICT WHERE TO LOOK IN INTER-
-ACTIVE ENVIRONMENTS USING DEEP RECURRENT Q-
-LEARNING
-Sajad Mousavi, Michael Schukat, Enda Howley
-The College of Engineering and Informatics
-National University of Ireland, Galway
-Ali Borji
-Department of Computer Science
-University of Central Florida (UCF)
-Orlando, Florida 32816-2365, USA
-Nasser Mozayani
-School of Computer Engineering
-Iran university of Science and Technology (IUST)
-Tehran, Iran"
-a8e75978a5335fd3deb04572bb6ca43dbfad4738,Sparse graphical representation based discriminant analysis for heterogeneous face recognition,"Sparse Graphical Representation based Discriminant
-Analysis for Heterogeneous Face Recognition
-Chunlei Peng, Xinbo Gao, Senior Member, IEEE, Nannan Wang, Member, IEEE, and Jie Li"
 a8a45d083e5535812f991afb686b4e36ea9f0717,Face Recognition Using Gradient Derivative Local Binary Patterns,"International Journal of Applied Engineering Research ISSN 0973-4562 Volume 12, Number 7 (2017) pp. 1316-1323
 © Research India Publications.  http://www.ripublication.com
 Face Recognition Using Gradient Derivative Local Binary Patterns"
@@ -59879,17 +50507,6 @@ Alexandros Stergiou
 Department of Information and Computing Sciences, Utrecht University,Buys Ballotgebouw, Princetonplein 5, Utrecht, 3584CC, Netherlands
 Department of Information and Computing Sciences, Utrecht University,Buys Ballotgebouw, Princetonplein 5, Utrecht, 3584CC, Netherlands
 Ronald Poppe1"
-a85e9e11db5665c89b057a124547377d3e1c27ef,Dynamics of Driver's Gaze: Explorations in Behavior Modeling and Maneuver Prediction,"Dynamics of Driver’s Gaze: Explorations in
-Behavior Modeling & Maneuver Prediction
-Sujitha Martin, Member, IEEE, Sourabh Vora, Kevan Yuen, and Mohan M. Trivedi, Fellow, IEEE"
-a8eebadc262594d1ca86d5520f312c1779d00b33,Improved Minimum Squared Error Algorithm with Applications to Face Recognition,"Improved Minimum Squared Error Algorithm with
-Applications to Face Recognition
-Qi Zhu1,2,3, Zhengming Li1,3,4, Jinxing Liu5, Zizhu Fan1,6, Lei Yu7, Yan Chen8*
-Bio-Computing Center, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China, 2 School of Optical-Electrical and Computer Engineering, University
-of Shanghai for Science and Technology, Shanghai, China, 3 Key Laboratory of Network Oriented Intelligent Computation, Shenzhen, China, 4 Guangdong Industrial
-Training Center, Guangdong Polytechnic Normal University, Guangzhou, China, 5 College of Information and Communication Technology, Qufu Normal University, Rizhao,
-China, 6 School of Basic Science, East China Jiaotong University, Nanchang, China, 7 School of Urban Planning and Management, Harbin Institute of Technology Shenzhen
-Graduate School, Shenzhen, China, 8 Shenzhen Sunwin Intelligent Co., Ltd., Shenzhen, China"
 a825364ada04007221577d305cbc42d413239f03,LaFiDa - A Laserscanner Multi-Fisheye Camera Dataset,"Article
 LaFiDa—A Laserscanner Multi-Fisheye Camera Dataset
 Steffen Urban * and Boris Jutzi *
@@ -59958,31 +50575,9 @@ KNOWLEDGE ENGINEERING AND
 MANAGEMENT + KNOWLEDGE ACQUISITION
 Chair(s)
 Int'l Conf. Information and Knowledge Engineering | IKE'13 |1"
-8c661e613d96210a02e5c7faad6d000b7d683e26,Support Vector Machines for Face Recognition,"International Research Journal of Engineering and Technology (IRJET)               e-ISSN: 2395-0056
-Volume: 02 Issue: 08 | Nov-2015           www.irjet.net                                                      p-ISSN: 2395-0072
-Support Vector Machines for Face Recognition
-Navin Prakash1, Dr.Yashpal Singh2
-1Research Scholar, IFTM University, Moradabad, UP, INDIA
-Associate Professor, Deptt. Of CS&E, B.I.E.T.-Jhansi, UP, INDIA
-……………………………………………………………………………****……………………………………………………………………………
-to  achieve
-orrect  and"
-8c6427cc1f4e1bbe5d6da34a4511842361f4fbb6,Hypothesis Only Baselines in Natural Language Inference,"Hypothesis Only Baselines in Natural Language Inference
-Adam Poliak1 Jason Naradowsky1 Aparajita Haldar1,2
-Rachel Rudinger1 Benjamin Van Durme1
-Johns Hopkins University 2BITS Pilani, Goa Campus, India"
 8c6db488bebf3fb2c50d951c4a9f002a531f9b61,Modeling Multimodal Dynamic Spatiotemporal Graphs,"Modeling Multimodal Dynamic Spatiotemporal Graphs
 Boris Ivanovic
 Marco Pavone"
-8cf679ef0ea28557acb86546e4b1b1a617d1c698,Long Term Multi-Target Tracking based on Detection and Data Association,"International Journal of Electronics and Electrical Engineering Vol. 1, No. 3, September, 2013
-Long Term Multi-Target Tracking based on
-Detection and Data Association
-Ai Min Li
-Shandong Polytechnic University, Jinan, China
-Email:
-Pil Seong Park
-University of Suwon, Suwon, Korea
-Email:"
 8c7f4c11b0c9e8edf62a0f5e6cf0dd9d2da431fa,Dataset Augmentation for Pose and Lighting Invariant Face Recognition,"Dataset Augmentation for Pose and Lighting
 Invariant Face Recognition
 Daniel Crispell∗, Octavian Biris∗, Nate Crosswhite†, Jeffrey Byrne†, Joseph L. Mundy∗
@@ -60123,10 +50718,6 @@ Chun-Guang Li, Chong You, and Ren´e Vidal"
 8ce4a669358dadbfac69ff0d313af042aeb94de1,Pedestrian intention recognition using Latent-dynamic Conditional Random Fields,"Pedestrian Intention Recognition using Latent-dynamic Conditional
 Random Fields
 Andreas Th. Schulz1 and Rainer Stiefelhagen2"
-8cd61bb3469aa253d4411ef2295b50683a031d17,Random Occlusion-recovery for Person Re-identification,"Random Occlusion-recovery for Person Re-identification
-Institute of Machine Learning and Systems Biology, School of Electronics and Information Engineering, Tongji
-Di Wu1, Kun Zhang1 and De-Shuang Huang1
-University, Caoan Road 4800, Shanghai 201804, China"
 8cf3b70f9247be23de9cc42272464e0363acb426,Multi-label classification of a real-world image dataset,"Multi-label classification of a real-world
 image dataset
 Nikita Uvarov
@@ -60258,24 +50849,11 @@ L’archive ouverte pluridisciplinaire HAL, est
 destin´ee au d´epˆot et `a la diffusion de documents
 scientiﬁques de niveau recherche, publi´es ou non,
 ´emanant des ´etablissements d’enseignement et de"
-b1444b3bf15eec84f6d9a2ade7989bb980ea7bd1,Local Directional Relation Pattern for Unconstrained and Robust Face Retrieval,"LOCAL DIRECTIONAL RELATION PATTERN
-Local Directional Relation Pattern for
-Unconstrained and Robust Face Retrieval
-Shiv Ram Dubey, Member, IEEE"
 b19f24ec92388513d1516d71292559417c776006,CAUSALGAN: LEARNING CAUSAL IMPLICIT GENER-,"Under review as a conference paper at ICLR 2018
 CAUSALGAN: LEARNING CAUSAL IMPLICIT GENER-
 ATIVE MODELS WITH ADVERSARIAL TRAINING
 Anonymous authors
 Paper under double-blind review"
-b14fb84db85ab4bbbcc8c92200e9c69b00737f91,A REVIEW ON CLASSIFIERS USED IN FACE RECOGNITION METHODS UNDER POSE AND ILLUMINATION VARIATION,"A REVIEW ON CLASSIFIERS USED IN FACE
-RECOGNITION METHODS UNDER POSE AND
-ILLUMINATION VARIATION
-R.Rajalakshmi1,   Dr.M.K.Jeyakumar2
-Research Scholar, Department of Computer Application Noorul Islam University, Kumaracoil, TamilNadu, India
-Professor, Department of Computer Application, Noorul IslamUniversity, Kumracoil, Tamil Nadu, India"
-b137480d2ccf3b53433de208815ce891d95af912,Visual Sentences for Pose Retrieval Over Low-Resolution Cross-Media Dance Collections,"Visual Sentences for Pose Retrieval over
-Low-resolution Cross-media Dance Collections
-Reede Ren, Member, IEEE, John Collomosse, Member, IEEE"
 b1451721864e836069fa299a64595d1655793757,Criteria Sliders: Learning Continuous Database Criteria via Interactive Ranking,"Criteria Sliders: Learning Continuous
 Database Criteria via Interactive Ranking
 James Tompkin,1∗ Kwang In Kim,2∗ Hanspeter Pﬁster,3 and Christian Theobalt4
@@ -60299,12 +50877,6 @@ François Brémond
 004, route des Lucioles, BP93
 06902 Sophia Antipolis Cedex - France
 Javier Ortiz"
-b1a3b19700b8738b4510eecf78a35ff38406df22,Automatic Analysis of Facial Actions : A Survey,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TAFFC.2017.2731763, IEEE
-Transactions on Affective Computing
-JOURNAL OF LATEX CLASS FILES, VOL. 13, NO. 9, SEPTEMBER 2014
-Automatic Analysis of Facial Actions: A Survey
-Brais Martinez, Member, IEEE, Michel F. Valstar, Senior Member, IEEE, Bihan Jiang,
-nd Maja Pantic, Fellow, IEEE"
 b16ff1331f961b2067c9464c491b7cbe90694758,Automatic plankton image classification combining multiple view features via multiple kernel learning,"Zheng et al. BMC Bioinformatics 2017, 18(Suppl 16):570
 DOI 10.1186/s12859-017-1954-8
 RESEARCH
@@ -60378,15 +50950,6 @@ Rishabh Iyer
 Microsoft Corporation
 Ganesh Ramakrishnan
 IIT Bombay"
-b1bd58bb76ae9e4504622a941e1da21a24b5cfdd,"International conference on Advanced Computing , Communication and Networks ’ 11 1087 Face Recognition Using Incremental Principal Component Analysis","International conference on Advanced Computing, Communication and Networks’11
-Face Recognition Using Incremental Principal Component Analysis
-Satish S. Banait1, Vivek Kshirsagar2, Meghana Nagori3, Archana R. Ugale4
-Dept. of Computer Engg. KK Wagh Institute of Engg. Education & Research Centre, Nashik
-, 3 Dept. of Computer Science & Engineering, Govt. College Of Engineering, Aurangabad, India
-Dept. of Computer Engg. MET’s BKC College of Engg., Nashik
-space
--  IN
-feature"
 b1fe9715f3f49980785db00066cb9062990a58ac,Study of the Changing Trends in Facial Expression Recognition,"Study of the Changing Trends in Facial Expression Recognition
 {tag}                                                                   {/tag}
 International Journal of Computer Applications
@@ -60444,12 +51007,6 @@ Mauricio Correa · Gabriel Hermosilla ·
 Rodrigo Verschae · Javier Ruiz-del-Solar
 Received: 11 December 2010 / Accepted: 30 May 2011 / Published online: 12 July 2011
 © Springer Science+Business Media B.V. 2011"
-6ed559a0d04e7d4185eeea43f77e372483982e4b,Paper on Player Tracking and Automated Analysis in Sports Videos,"International Journal of Emerging Technology and Advanced Engineering
-Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 5, Issue 6, June 2015)
-A Review Paper on Player Tracking and Automated Analysis in
-Sports Videos
-Nikhil M.1, Sreejith S.2
-,2Department of ECE, Government College of Engineering Kannur, kerala, India"
 6e99832e265999194aa88958d892db62afbd7ac9,Is Combinational Strategy Better For Image Memorability Prediction,"Is Combinational Strategy Better For Image
 Memorability Prediction
 Wenting Zhu"
@@ -60460,22 +51017,9 @@ Xiang Yu†
 NEC Laboratories America
 Jianchao Yang‡ Wilmot Li§
 Snapchat"
-6ee5205408fc6db03460c05765ae0f21a6eb9552,A literature review on recent multi-object tracking methods based on HMM and particle filter,"IOSR Journal of Computer Engineering (IOSR-JCE)
-e-ISSN: 2278-0661, p- ISSN: 2278-8727Volume 16, Issue 2, Ver. VII (Mar-Apr. 2014), PP 05-07
-www.iosrjournals.org
-A literature review on recent multi-object tracking methods
-ased on HMM and particle filter
-Kalyani Ahire1, Prof.P.S Mohod2
-Department of Computer Science & Engineering,, G.H.R.I.E.T.W.,RashtrasantTukdojiMaharaj Nagpur
-University Nagpur, India"
 6ebc601bba067af64b57d59039319650168df4c9,CNN-based Real-time Dense Face Reconstruction with Inverse-rendered Photo-realistic Face Images.,"CNN-based Real-time Dense Face Reconstruction
 with Inverse-rendered Photo-realistic Face Images
 Yudong Guo, Juyong Zhang†, Jianfei Cai, Boyi Jiang and Jianmin Zheng"
-6e885d831568520aa95f523f625623e46578efd0,Camera Selection for Adaptive Human-Computer Interface,"JOURNAL OF LATEX CLASS FILES, VOL. 11, NO. 4, DECEMBER 2012
-Camera Selection for Adaptive
-Human-Computer Interface
-Niki Martinel Student Member, IEEE, Christian Micheloni, Member, IEEE,
-Claudio Piciarelli, Member, IEEE and Gian Luca Foresti, Senior Member, IEEE"
 6e1802874ead801a7e1072aa870681aa2f555f35,Exploring Feature Descritors for Face Recognition,"424407281/07/$20.00 ©2007 IEEE
 I  629
 ICASSP 2007
@@ -60528,8 +51072,6 @@ New Delhi"
 6e6f516ed1ce0089d4f6d113797d711d5997802b,Face Analysis and Recognition in Mobile Devices,"Face Analysis and Recognition in Mobile Devices Valencia, November 2008 Departamento de Sistemas Informáticos y ComputaciónUniversidad Politécnica de ValenciaMauricio Villegas Santamaría"
 6ee2173c06c84cae6aae2912a4439ec956ecc3bb,Zero-shot Sim-to-Real Transfer with Modular Priors,"Zero-shot Sim-to-Real Transfer with Modular Priors
 Robert Lee1,2, Serena Mou1,2, Vibhavari Dasagi2, Jake Bruce2, J¨urgen Leitner1,2, Niko S¨underhauf1,2"
-6e297f10a02580dfc74595ff8d7db34020002ec4,Correlation Net : spatio temporal multimodal deep learning,"learning
-Novanto Yudistira, Takio Kurita, Member, IEEE,"
 6eabb24b358dea9c66ad28d2efc2c9c469e115c4,On the use of dynamic features in face biometrics: recent advances and challenges,"(will be inserted by the editor)
 On the Use of Dynamic Features in Face Biometrics: Recent Advances
 nd Challenges
@@ -60668,15 +51210,6 @@ Email: {eez138300, brejesh, eet152695"
 6ef0b43cf897f527540c29cae0618aabb7329072,Parallel Algorithms for Nearest Neighbor Search Problems in High Dimensions,"PARALLEL ALGORITHMS FOR NEAREST NEIGHBOR SEARCH
 PROBLEMS IN HIGH DIMENSIONS.
 BO XIAO∗ AND GEORGE BIROS†"
-6e32c368a6157fb911c9363dc3e967a7fb2ad9f7,Hybrid Stochastic / Deterministic Optimization for Tracking Sports Players and Pedestrians,"Hybrid Stochastic / Deterministic Optimization
-for Tracking Sports Players and Pedestrians(cid:2)
-Robert T. Collins1 and Peter Carr2
-The Pennsylvania State University, USA
-Disney Research Pittsburgh, USA"
-6ef6e6e8b295c90ab9390f07d91c9ef8304a409d,Preserving privacy by de-identifying face images,"Preserving Privacy
-y De-Identifying Face Images
-Elaine M. Newton, Student Member, IEEE, Latanya Sweeney, Member, IEEE Computer Society, and
-Bradley Malin, Student Member, IEEE"
 6e82ce9897093ce4f5fa795887273992489c380d,Face recognition using Eigensurface on Kinect depth-maps,"Int'l Conf. IP, Comp. Vision, and Pattern Recognition |  IPCV'16  |
 Face recognition using Eigensurface on Kinect depth-maps
 Marcelo Romero1, Cesar Flores1, Vianney Muñoz1 and Luis Carlos Altamirano2
@@ -60694,15 +51227,6 @@ The content must not be changed in any way or sold commercially in any format or
 medium without the formal permission of the author.
 When referring to this work, full bibliographic details including the author, title,
 warding institution and date of the thesis must be given."
-6e8c7e0f6a83fd02f0cc6872ca16d755406723e5,Spatio-Temporal Closed-Loop Object Detection,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TIP.2017.2651367, IEEE
-Transactions on Image Processing
-Spatio-Temporal Closed-Loop Object Detection
-Leonardo Galteri, Lorenzo Seidenari, Marco Bertini, and Alberto Del Bimbo, Member, IEEE"
-6eb2972abed9507e21b959ba7754b599a7af41fb,Face Recognition and Verification : A Literature Review,"International Journal of Emerging Technology and Advanced Engineering
-Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 7, Issue 8, August 2017)
-Face Recognition and Verification: A Literature Review
-1,2Jaipur National University, Department of Electronics & Communication Engineering, Jaipur, Rajasthan, India
-Aditi Upadhyay1, Sudhir Kumar Sharma2"
 6e198f6cc4199e1c4173944e3df6f39a302cf787,MORPH-II : Inconsistencies and Cleaning Whitepaper,"MORPH-II: Inconsistencies and Cleaning Whitepaper
 Participants: G. Bingham, B. Yip, M. Ferguson, and C. Nansalo
 Mentors: C. Chen, Y. Wang, and T. Kling
@@ -60720,13 +51244,6 @@ Professor Alfred O. Hero III, Chair
 Professor Jeﬁrey A. Fessler
 Professor Susan A. Murphy
 Professor David L. Neuhoﬁ"
-6e396401b3950eccdaf8265aeae8a4f0da8965a0,Obstacle Detection Quality as a Problem-Oriented Approach to Stereo Vision Algorithms Estimation in Road Situation Analysis,"Obstacle Detection Quality as a Problem-Oriented
-Approach to Stereo Vision Algorithms Estimation
-in Road Situation Analysis
-A.A. Smagina, D.A. Shepelev, E.I. Ershov, A.S. Grigoryev
-Institute for Information Transmission Problems (Kharkevich Institute) –IITP RAS,
-Bolshoy Karetny per. 19, build.1, Moscow, Russia, 127051
-E-mail:"
 6e604946a0a51911db0e887378ba1ae103dcfb9e,Detection and Classification of a Moving Object in a Video Stream,"Proc. of the Intl. Conf. on Advances in Computing and Information Technology-- ACIT 2014
 Copyright © Institute of Research Engineers and Doctors. All rights reserved.
 ISBN: 978-981-07-8859-9 doi: 10.3850/ 978-981-07-8859-9_23
@@ -60777,19 +51294,6 @@ nd it is a condition of accessing publications that users recognise and abide by
 ? Users may download and print one copy of any publication from the public portal for the purpose of private study or research.
 ? You may not further distribute the material or use it for any profit-making activity or commercial gain
 ? You may freely distribute the URL identifying the publication in the public portal ?"
-6ecd4025b7b5f4894c990614a9a65e3a1ac347b2,Automatic Naming of Character using Video Streaming for Face Recognition with Graph Matching,"International Journal on Recent and Innovation Trends in Computing and Communication
-ISSN: 2321-8169
-Volume: 2 Issue: 5
-1275– 1281
-_______________________________________________________________________________________________
-Automatic Naming of Character using Video Streaming for Face
-Recognition with Graph Matching
-Nivedita.R.Pandey
-Ranjan.P.Dahake
-PG Student at MET’s IOE Bhujbal Knowledge City,
-PG Student at MET’s IOE Bhujbal Knowledge City,
-Nasik, Maharashtra, India,
-Nasik, Maharashtra, India,"
 6ee8a94ccba10062172e5b31ee097c846821a822,How to solve classification and regression problems on high-dimensional data with a supervised extension of slow feature analysis,"Submitted 3/13; Revised 10/13; Published 12/13
 How to Solve Classiﬁcation and Regression Problems on
 High-Dimensional Data with a Supervised
@@ -60806,26 +51310,6 @@ Xingyu Chen, Junzhi Yu, Senior Member, IEEE, Shihan Kong, Zhengxing Wu, and Li W
 01a152e7ca6accce4fa52e29b27feb76418583fb,Tracking Multiple High-Density Homogeneous Targets,"IEEE TRANSACTION ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, VOL. X, NO. X, XXXX
 Tracking multiple high-density homogeneous targets
 Fabio Poiesi and Andrea Cavallaro"
-01d94d568447075d9f32f6c1e7af9255188a6938,A biometric database with rotating head videos and hand-drawn face sketches,"A Biometric Database with Rotating Head Videos and
-Hand-drawn Face Sketches
-Hanan A. Al Nizami, Jeremy P. Adkins-Hill, Yong Zhang, John R. Sullins,
-Christine McCullough, Shaun Canavan, and Lijun Yin
-infrared cameras, or 3D laser scanners), a particular biometric
-feature (fingerprint, face, ear, iris, or gait), or an application
-domain (data security, access control, health care registration,
-or forensic investigation).
-The database presented here includes two unique types of
-data:  (i)  Rotating  head  videos  with  strong  shadows;  (ii)
-Hand-drawn face sketches. In addition, video frames of ten
-face  pose  angles  were  determined  manually  using  the
-Reference  Images  and  empirical  rules.  Although  the  initial
-motivation of building such a database is to study multi-frame
-fusion  for  video-based  face  recognition  and  quantitative
-ssessment of sketch effectiveness in criminal investigations,
-the database is useful for a wide range of research topics.
-In video-based face recognition, experiments have shown
-that multi-frame fusion is an effective method to improve the
-recognition  rate  [13,  14,  15].  The  performance  gain  is"
 01bef320b83ac4405b3fc5b1cff788c124109fb9,Translating Head Motion into Attention - Towards Processing of Student's Body-Language.,"de Lausanne
 RLC D1 740, CH-1015
 Lausanne
@@ -60852,9 +51336,6 @@ Solving Uncalibrated Photometric Stereo using Total
 Variation
 Yvain Qu´eau · Fran¸cois Lauze · Jean-Denis Durou
 the date of receipt and acceptance should be inserted later"
-01e812ad00b7743e9b24aa070a24023f05710b8b,A Distributed Representation Based Query Expansion Approach for Image Captioning,"Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics
-nd the 7th International Joint Conference on Natural Language Processing (Short Papers), pages 106–111,
-Beijing, China, July 26-31, 2015. c(cid:13)2015 Association for Computational Linguistics"
 014b4335d055679bc680a6ceb6f1a264d8ce8a4a,Are You Sure You Want To Do That? Classification with Verification,"Are You Sure You Want To Do That?
 Classiﬁcation with Veriﬁcation
 Harris Chan∗
@@ -60868,11 +51349,6 @@ Fernanda Viegas Rory Sayres"
 Model
 K. Jüngling1, S. Becker1, and M. Arens1
 Object Recognition, Fraunhofer IOSB, Ettlingen, Germany"
-01f21ad0eccdbb56dd60c397a27415b9f33d5ec3,Learning Contextual Dependence With Convolutional Hierarchical Recurrent Neural Networks,"Learning Contextual Dependencies with
-Convolutional Hierarchical Recurrent
-Neural Networks
-Zhen Zuo, Student Member, IEEE, Bing Shuai, Student Member, IEEE, Gang Wang, Member, IEEE,
-Xiao Liu, Xingxing Wang, and Bing Wang, Student Member, IEEE"
 01591390da1356b871aefe11d4bb92c1df5ba082,Online Appendix to : Content-based Image Retrieval,"Content-based Image Retrieval
 Haoran Wang,
 Yuanbin Wang,
@@ -60924,12 +51400,6 @@ Murilo Varges da Silva1,2 and Aparecido Nilceu Marana3
 UFSCar - Federal University of Sao Carlos, Sao Carlos, SP, Brazil
 IFSP - Federal Institute of Education of Sao Paulo, Birigui, SP, Brazil
 UNESP - Sao Paulo State University, Bauru, SP, Brazil"
-01f5689a4010ae14ca444c36bec81f12ce528912,"EXTENDED FAST SEARCH CLUSTERING ALGORITHM: WIDELY DENSITY CLUSTERS, NO DENSITY PEAKS","EXTENDED FAST SEARCH CLUSTERING
-ALGORITHM: WIDELY DENSITY
-CLUSTERS, NO DENSITY PEAKS
-Zhang WenKai1 and Li Jing2
-,2School of Computer Science and Technology, University of Science and
-Technology of China, Hefei, 230026, China"
 0135747b4d3c9a2d983f7d0d9f4c39e094825149,Embedded wavelet-based face recognition under variable position,"Embedded wavelet-based face recognition under variable
 position
 Pascal Cotreta, Stéphane Chevobbea and Mehdi Darouicha
@@ -61082,12 +51552,6 @@ Computer Engineering
 Bo˜gazic.i University
 ˙Istanbul, Turkey
 Email:"
-013e9e0f712d8caa89dd0881ab8dcf90d687ba50,Face Recognition using LBP and LVQ Classifier,"Face Recognition using LBP and LVQ Classifier
-Abdul Quyoom
-Department of Computer Science Engineering
-Central University of Rajasthan
-Ajmer, Rajasthan, India
-each  human"
 01381e2faeb26489ae9c24c84c42df33901cfe61,Multi-scale Deep Learning Architectures for Person Re-identification,"Multi-scale Deep Learning Architectures for Person Re-identiﬁcation
 Xuelin Qian1 Yanwei Fu2,5,* Yu-Gang Jiang1,3 Tao Xiang4 Xiangyang Xue1,2
 Shanghai Key Lab of Intelligent Info. Processing, School of Computer Science, Fudan University;
@@ -61113,33 +51577,8 @@ portant use for the elderly population.
 In particular, pupil
 size may be a valuable source of information, since, apart
 from pathological cases, it can reveal the emotional state, the"
-0163d847307fae508d8f40ad193ee542c1e051b4,Classemes and Other Classifier-Based Features for Efficient Object Categorization,"JOURNAL OF LATEX CLASS FILES, VOL. 6, NO. 1, JANUARY 2007
-Classemes and Other Classiﬁer-based
-Features for Efﬁcient Object Categorization
-- Supplementary material -
-Alessandro Bergamo, and Lorenzo Torresani, Member, IEEE
-LOW-LEVEL FEATURES
-We extract the SIFT [1] features for our descriptor
-ccording to the following pipeline. We ﬁrst convert
-each image to gray-scale, then we normalize the con-
-trast by forcing the 0.01% of lightest and darkest pixels
-to be mapped to white and black respectively, and
-linearly rescaling the values in between. All images
-exceeding 786,432 pixels of resolution are downsized
-to this maximum value while keeping the aspect ratio.
-The 128-dimensional SIFT descriptors are computed
-from the interest points returned by a DoG detec-
-tor [2]. We ﬁnally compute a Bag-Of-Word histogram
-of these descriptors, using a K-means vocabulary of
-500 words.
-CLASSEMES"
 01915181692c821cc5a0a703047bd5b07c1f9af5,Cross-Caption Coreference Resolution for Automatic Image Understanding,"Proceedings of the Fourteenth Conference on Computational Natural Language Learning, pages 162–171,
 Uppsala, Sweden, 15-16 July 2010. c(cid:13)2010 Association for Computational Linguistics"
-017ce398e1eb9f2eed82d0b22fb1c21d3bcf9637,FACE RECOGNITION WITH HARMONIC DELIGHTING,"FACE RECOGNITION WITH HARMONIC DE-LIGHTING
-Laiyun Qing1,2, Shiguang Shan2, Wen Gao1,2
-ICT-ISVISION Joint R&D Laboratory for Face Recognition, CAS, Beijing, China, 100080
-Graduate School, CAS, Beijing, China, 100080
-Emails: {lyqing, sgshan, wgao}jdl.ac.cn"
 01ece1dd9a0a2a7289d791625c6c7446d38584e7,A Comparative Analysis of Classification Algorithms Applied to M 5 AIE-Extracted Human Poses,"A Comparative Analysis of Classiﬁcation Algorithms
 Applied to M5AIE-Extracted Human Poses
 Andr´e Brand˜ao, Leandro A. F. Fernandes, and Esteban Clua
@@ -61153,14 +51592,6 @@ phone: + (34)934011066, fax: + (34)934016447, email:
 Jordi Girona, 1-3, 08034 Barcelona, SPAIN
 Image Processing Group, Universitat Polit`ecnica de Catalunya
 web: gps-tsc.upc.es/imatge"
-01c8d7a3460422412fba04e7ee14c4f6cdff9ad7,Rule Based System for Recognizing Emotions Using Multimodal Approach,"(IJACSA) International Journal of Advanced Computer Science and Applications,
-Vol. 4, No. 7, 2013
-Rule Based System for Recognizing Emotions Using
-Multimodal Approach
-Preeti Khanna
-Information System
-SBM, SVKM’s NMIMS
-Mumbai, India"
 01f42436042ddaa48998c87109cbe46cad6e7e52,Schedtask: a hardware-assisted task scheduler,"SchedTask: A Hardware-Assisted Task Scheduler
 Prathmesh Kallurkar∗
 Microarchitecture Research Lab
@@ -61183,17 +51614,6 @@ of Gray Matter
 Moo K. Chung*, Kim M. Dalton, Li Shen, Alan C. Evans, and Richard J. Davidson"
 0113b302a49de15a1d41ca4750191979ad756d2f,Matching Faces with Textual Cues in Soccer Videos,"424403677/06/$20.00 ©2006 IEEE
 ICME 2006"
-01350214f850f43d72268df4f98b05901fbbe06c,1 Deep convolutional neural networks for detection of 2 polar mesocyclones from satellite mosaics 3,"Preprints (www.preprints.org)  |  NOT PEER-REVIEWED  |  Posted: 19 September 2018                   doi:10.20944/preprints201809.0361.v1
-Article
-Deep convolutional neural networks for detection of
-polar mesocyclones from satellite mosaics
-Mikhail Krinitskiy 1,*, Polina Verezemskaya 1,2, Kirill Grashchenkov1,3, Natalia Tilinina1,
-Sergey Gulev1 and Matthew Lazzara 4
-Shirshov Institute of Oceanology, Russian Academy of Sciences, Moscow, Russia;
-Research Computing Center of Lomonosov Moscow State University, Moscow, Russia
-Moscow Institute of Physics and Technology, Moscow, Russia
-University of Wisconsin-Madison and Madison Area Technical College, Madison, Wisconsin, USA
-*  Correspondence: Tel.: +7-926-141-6200"
 015d25f66514ce0a966300944201d45968a104ba,SIMPLE IMAGE DESCRIPTION GENERATOR VIA A LINEAR PHRASE-BASED MODEL Rémi Lebret,"SIMPLE IMAGE DESCRIPTION GENERATOR
 VIA A LINEAR PHRASE-BASED MODEL
 Rémi Lebret        Pedro H. O. Pinheiro
@@ -61380,20 +51800,6 @@ Portland State University and Los Alamos National Laboratory
 Nicolas W. Hengartner, Kevin R. Vixie, and Brendt E. Wohlberg
 Los Alamos National Laboratory
 Los Alamos, NM 87545"
-c6638c7c1ec7b8fd5cdba039536fb44d12cff5c2,Towards a Development of Augmented Reality for Jewellery App,"Revati Mukesh Raspayle et al, International Journal of Computer Science and Mobile Computing, Vol.5 Issue.6, June- 2016, pg. 129-137
-Available Online at www.ijcsmc.com
-International Journal of Computer Science and Mobile Computing
-A Monthly Journal of Computer Science and Information Technology
-ISSN 2320–088X
-IMPACT FACTOR: 5.258
-IJCSMC, Vol. 5, Issue. 6, June 2016, pg.129 – 137
-Towards a Development of Augmented
-Reality for Jewellery App
-Er. Revati Mukesh Raspayle1, Prof. Kavita Kelkar2
-¹Student (M.Tech) CSE, Mumbai University, Computer Engineering, K.J SOMAIYA COE Vidyavihar,
-²Assistant Professor, Mumbai University, Computer Engineering, K.J SOMAIYA COE Vidyavihar,
-Mumbai 400077, India
-Mumbai 400077, India"
 c6eb026d3a0081f4cb5cde16d3170f8ecf8ce706,Face Recognition: From Traditional to Deep Learning Methods,"Face Recognition: From Traditional to Deep
 Learning Methods
 Daniel S´aez Trigueros, Li Meng
@@ -61609,12 +52015,6 @@ Department of Information Technology
 Cummins College of Engineering for Women
 Karve Nagar, Pune - 411052
 for  more  effective"
-f65896855e5df3db5422b57ab360287efa213066,DETECTION OF UNCONTROLLED MOTION BEHAVIOR IN HUMAN,"IJRET: International Journal of Research in Engineering and Technology        eISSN: 2319-1163 | pISSN: 2321-7308
-DETECTION OF UNCONTROLLED MOTION BEHAVIOR IN HUMAN
-CROWDS
-Vijitha V. A1
-Student of M. Tech., Computer Science & Engineering, Sahyadri College of Engineering & Management, Karnataka,
-India"
 f6684367e7925cd90fb8974640d41823191c7cff,CNN-based Pore Detection and Description for High-Resolution Fingerprint Recognition,"Automatic Dataset Annotation to Learn CNN Pore
 Description for Fingerprint Recognition
 Gabriel Dahia
@@ -61650,16 +52050,6 @@ f6ce34d6e4e445cc2c8a9b8ba624e971dd4144ca,Cross-Label Suppression: A Discriminati
 Dictionary Learning with Group Regularization
 Xiudong Wang and Yuantao Gu∗
 April 24, 2017"
-f67a73c9dd1e05bfc51219e70536dbb49158f7bc,A Gaussian Mixture Model for Classifying the Human Age using DWT and Sammon Map,"Journal of Computer Science 10 (11): 2292-2298, 2014
-ISSN: 1549-3636
-© 2014 Nithyashri and Kulanthaivel, This open access article is distributed under a Creative Commons Attribution
-(CC-BY) 3.0 license
-A GAUSSIAN MIXTURE MODEL FOR CLASSIFYING THE
-HUMAN AGE USING DWT AND SAMMON MAP
-J. Nithyashri and 2G. Kulanthaivel
-Department of Computer Science and Engineering, Sathyabama University, Chennai, India
-Department of Electronics Engineering, NITTTR, Chennai, India
-Received 2014-05-08; Revised 2014-05-23; Accepted 2014-11-28"
 f621f4cdb4158f72f12fdd55564bcdce322dce7c,Recursive Coarse-to-Fine Localization for Fast Object Detection,"International Journal of Control and Automation
 Vol.7, No.1 (2014), pp.235-242
 http://dx.doi.org/10.14257/ijca.2014.7.1.20
@@ -61706,42 +52096,15 @@ f6ce7e947f1cfe75abda61f018c3ca7e38fceb20,NLE@MediaEval'17: Combining Cross-Media
 Embeddings for Retrieving Diverse Social Images
 Jean-Michel Renders and Gabriela Csurka
 Naver Labs Europe, Meylan, France"
-f672bf42dbefb6b40921c00a05f60284934e9948,LDS-Inspired Residual Networks,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCSVT.2018.2869680, IEEE
-Transactions on Circuits and Systems for Video Technology
-LDS-Inspired Residual Networks
-Anastasios Dimou, Dimitrios Ataloglou, Kosmas Dimitropoulos, Member, IEEE,
-Federico Alvarez, Member, IEEE, and Petros Daras, Senior Member, IEEE"
 f676cdb17ccd5b65f44ce67677d8646b48d8939e,Occupancy Networks: Learning 3D Reconstruction in Function Space,"Occupancy Networks: Learning 3D Reconstruction in Function Space
 Lars Mescheder1 Michael Oechsle1,2 Michael Niemeyer1
 Sebastian Nowozin3† Andreas Geiger1
 Autonomous Vision Group, MPI for Intelligent Systems and University of T¨ubingen
 ETAS GmbH, Stuttgart
 Google AI Berlin"
-f6551620737ea608da36842929681fee811239db,Object Tracking via Partial Least Squares Analysis,"Object Tracking via Partial Least
-Squares Analysis
-Qing Wang, Student Member, IEEE, Feng Chen, Member, IEEE,
-Wenli Xu, and Ming-Hsuan Yang, Senior Member, IEEE"
 f60070d3a4d333aa1436e4c372b1feb5b316a7ba,Face Recognition via Centralized Coordinate Learning,"Face Recognition via Centralized Coordinate
 Learning
 Xianbiao Qi, Lei Zhang"
-f6f06be05981689b94809130e251f9e4bf932660,An Approach to Illumination and Expression Invariant Multiple Classifier Face Recognition,"An Approach to Illumination and Expression Invariant
-International Journal of Computer Applications (0975 – 8887)
-Volume 91 – No.15, April 2014
-Multiple Classifier Face Recognition
-Dalton Meitei Thounaojam
-National Institute of Technology
-Silchar
-Assam: 788010
-India
-Hidangmayum Saxena Devi
-National Institute of Technology
-Silchar
-Assam: 788010
-India
-Romesh Laishram
-Manipur Institute of Technology
-Imphal West: 795001
-India"
 7dba0e39bb059103e10fb81bce2fe831f520fb38,Articulated human pose estimation in natural images,"Articulated Human Pose Estimation
 in Natural Images
 Samuel Alan Johnson
@@ -61806,15 +52169,6 @@ Johann Schleier-Smith
 San Francisco, CA 94111
 if(we) Inc.
 848 Battery St."
-7d9fe410f24142d2057695ee1d6015fb1d347d4a,Facial Expression Feature Extraction Based on FastLBP,"Facial Expression Feature Extraction Based on
-FastLBP
-Computer and Information Engineering Department of Beijing Technology and Business University, Beijing, China
-Ya Zheng
-Email:
-Computer and Information Engineering Department of Beijing Technology and Business University, Beijing, China
-Email:
-Xiuxin Chen, Chongchong Yu and Cheng Gao
-facial  expression"
 7d96ecb24b3d8595267365cfc9878d46280f1e8c,End-to-end steering angle prediction and object detection using convolutional neural networks,"End-to-end steering angle prediction and
 object detection using convolutional
 neural networks
@@ -61936,10 +52290,6 @@ Chen Change Loy, Ke Chen, Shaogang Gong, and Tao Xiang"
 7dd654ac5e775fa1fa585e257565455ae8832caf,Deep Pictorial Gaze Estimation,"Deep Pictorial Gaze Estimation
 Seonwook Park, Adrian Spurr, and Otmar Hilliges
 AIT Lab, Department of Computer Science, ETH Zurich"
-7d6539d637f919fa20a9261e03aedcf59f92598e,Improving Cross-Resolution Face Matching Using Ensemble-Based Co-Transfer Learning,"Improving Cross-resolution Face Matching using
-Ensemble based Co-Transfer Learning
-Himanshu S. Bhatt, Student Member, IEEE, Richa Singh, Senior Member, IEEE, Mayank Vatsa, Senior
-Member, IEEE, and Nalini K. Ratha, Fellow, IEEE"
 7d841607ce29ff4a75734ffbf569431425d8342f,Bimodal 2D-3D face recognition using a two-stage fusion strategy,"Bimodal 2D-3D face recognition using a two-stage fusion
 strategy
 Amel AISSAOUI1 and Jean MARTINET2
@@ -61951,10 +52301,6 @@ CRIStAL
 Lille 1 University
 Villeneuve d’Ascq, France
 Email:"
-7da961cb039b1a01cad9b78d93bdfe2a69ed3ccf,Hierarchical Gaussian Descriptors with Application to Person Re-Identification,"Hierarchical Gaussian Descriptors with
-Application to Person Re-Identiﬁcation
-Tetsu Matsukawa, Member, IEEE, Takahiro Okabe, Member, IEEE,
-Einoshin Suzuki, Non Member, IEEE and Yoichi Sato, Member, IEEE"
 7dcd927b3651d9230f074d19a9b65d1c96fc4604,How to Train a CAT: Learning Canonical Appearance Transformations for Direct Visual Localization Under Illumination Change,"How to Train a CAT: Learning Canonical
 Appearance Transformations for Direct Visual
 Localization Under Illumination Change
@@ -62051,9 +52397,6 @@ Dimitris Metaxas*, Mark Dilsizian*, Carol Neidle**
 *Rutgers University, **Boston University
 *Rutgers University, CBIM, Department of Computer Science, 617 Bowser Road, Piscataway, NJ  08854
 **Boston University Linguistics, 621 Commonwealth Ave., Boston, MA  02215"
-2d294c58b2afb529b26c49d3c92293431f5f98d0,Maximum Margin Projection Subspace Learning for Visual Data Analysis,"Maximum Margin Projection Subspace Learning
-for Visual Data Analysis
-Symeon Nikitidis, Anastasios Tefas, Member, IEEE, and Ioannis Pitas, Fellow, IEEE"
 2d1b8f60f2724efd6c9344870fb60e8525157d70,Parallel Multiscale Autoregressive Density Estimation,"Parallel Multiscale Autoregressive Density Estimation
 Scott Reed 1 A¨aron van den Oord 1 Nal Kalchbrenner 1 Sergio G´omez Colmenarejo 1 Ziyu Wang 1
 Yutian Chen 1 Dan Belov 1 Nando de Freitas 1"
@@ -62062,15 +52405,6 @@ using Means of Covariance Descriptors
 Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB
 J¨urgen Metzler
 76131 Karlsruhe, Germany"
-2d8f08dbb012621504753a4df493b785ad22ef0f,Face Recognition Techniques for Authentication in Smart Devices-Comparative Study,"International Journal of Applied Information Systems (IJAIS) – ISSN : 2249-0868
-Foundation of Computer Science FCS, New York, USA
-Volume 12 – No. 1, April 2017 – www.ijais.org
-Face Recognition Techniques for Authentication in
-Smart Devices - Comparative Study
-Jerin George
-Post Graduate Student, MCA
-Department of Computer Science, Christ University
-Bengaluru, India"
 2df4d05119fe3fbf1f8112b3ad901c33728b498a,A regularization scheme for structured output problems : an application to facial landmark detection,"Facial landmark detection using structured output deep
 neural networks
 Souﬁane Belharbi ∗1, Cl´ement Chatelain∗1, Romain H´erault∗1, and S´ebastien
@@ -62098,10 +52432,6 @@ x − c1n2
 The forward process is described by equations (3),(4),
 nd (5) in the main paper. We now provide the backward
 process, i.e., the partial derivatives ∂Si"
-2d4d463b1bf1c26afafea7b98ad8f7f06b5b1a4c,Improving Image Captioning with Conditional Generative Adversarial Nets,"Improving Image Captioning with Conditional Generative Adversarial Nets
-Chen Chen, Shuai Mu, Wanpeng Xiao, Zexiong Ye, Liesi Wu, Qi Ju
-{beckhamchen, harrymou, wanpengxiao, joeyye, henrylwu,
-Tencent AI Lab, Shenzhen, China 518000"
 2d950a3e8c74efb08197bfcb9c64a6b111f6bcd9,DENSE MATCHING COMPARISON BETWEEN CENSUS AND A CONVOLUTIONAL NEURAL NETWORK ALGORITHM FOR PLANT RECONSTRUCTION,"DENSE MATCHING COMPARISON BETWEEN CENSUS AND A CONVOLUTIONAL
 NEURAL NETWORK ALGORITHM FOR PLANT RECONSTRUCTION
 Y. Xia, J. Tian, P. d’Angelo, P. Reinartz
@@ -62131,12 +52461,6 @@ CITATION
 Gündemir, S., Carton, A. M., & Homan, A. C. (2018, September 24). The Impact of Organizational
 Performance on the Emergence of Asian American Leaders. Journal of Applied Psychology.
 Advance online publication. http://dx.doi.org/10.1037/apl0000347"
-2dd853b617c176810e3dda008f7cacea6473f0ae,Image captioning using deep neural architectures,"Image Captioning using Deep Neural
-Architectures
-Parth Shah (orcid.org/0000-0002-7880-2228), Vishvajit Bakarola
-(orcid.org/0000-0002-6602-9194), and Supriya Pati
-(orcid.org/0000-0001-5528-6104)
-Chhotubhai Gopalbhai Patel Institute of Technology, Bardoli, India"
 2d9e30680a17bbdf83ce27287bc1901da7198f74,"Symmetry, probability, and recognition in face space.","Symmetry, probability, and recognition in face space
 Lawrence Sirovich1 and Marsha Meytlis
 Laboratory of Applied Mathematics, Mount Sinai School of Medicine, 1 Gustave L. Levy Place, New York, NY 10029
@@ -62162,12 +52486,6 @@ Multiple-View Face Hallucination by a Novel
 Regression Analysis in Tensor Space
 Faculty of Engineering and Technology, Panyapiwat Institute of Management, Thailand
 Parinya Sanguansat"
-2dbb4b45b6a392268ce45d16fb944a652d434bd2,Maximal Cliques that Satisfy Hard Constraints with Application to Deformable Object Model Learning,"Maximal Cliques that Satisfy Hard Constraints with
-Application to Deformable Object Model Learning
-Xinggang Wang1∗ Xiang Bai1 Xingwei Yang2† Wenyu Liu1 Longin Jan Latecki3
-Dept. of Electronics and Information Engineering, Huazhong Univ. of Science and Technology, China
-Image Analytics Lab, GE Research, One Research Circle, Niskayuna, NY 12309, USA
-Dept. of Computer and Information Sciences, Temple Univ., USA"
 2d84c0d96332bb4fbd8acced98e726aabbf15591,Investigating the Role of Saliency for Face Recognition,"UNIVERSITY OF CALIFORNIA
 RIVERSIDE
 Investigating the Role of Saliency for Face Recognition
@@ -62333,12 +52651,6 @@ Xi Zhao, Emmanuel Dellandr´ea, Liming Chen and Dimitris Samaras"
 2d15a7546c16d5821ffa8f769eb7ec18e435e64d,Recognition in Terra Incognita,"Recognition in Terra Incognita
 Sara Beery, Grant Van Horn, and Pietro Perona
 Caltech"
-2d8ffa4a27b3e3b792b2d2516bbcb1a47c114846,Multi-view Laplacian Eigenmaps Based on Bag-of-Neighbors For RGBD Human Emotion Recognition,"JOURNAL OF LATEX CLASS FILES
-Multi-view Laplacian Eigenmaps
-Based on Bag-of-Neighbors
-For RGBD Human Emotion Recognition
-Shenglan Liu, Member, IEEE, Shuai Guo, Hong Qiao, Senior Member, IEEE, Yang Wang, Bin Wang,
-Wenbo Luo, Mingming Zhang, Keye Zhang, and Bixuan Du"
 2d22a60e69ebdb3fde056adcf4f6a08ccdb6106f,Robust Facial Expression Recognition Mr,"IJREAT International Journal of Research in Engineering & Advanced Technology, Volume 2, Issue 2, Apr-May, 2014
 ISSN: 2320 – 8791 (Impact Factor: 1.479)
 www.ijreat.org
@@ -62394,11 +52706,6 @@ Department of Social Psychology, Friedrich Schiller University of Jena, Humboldt
 Michael Stifel Center, Ernst-Abbe-Platz 2, 07743 Jena, Germany
 Keywords:
 Nonverbal emotional communication, Granger causality, maximally coherent intervals"
-2dc62458979dfc00ec195258ea8809077c5de442,Robust Painting Recognition and Registration for Mobile Augmented Reality,"JOURNAL OF LATEX CLASS FILES, VOL. 6, NO. 1, JANUARY 2007
-Robust Painting Recognition and Registration
-for Mobile Augmented Reality
-Niki Martinel*, Student Member, IEEE, Christian Micheloni, Member, IEEE,
-nd Gian Luca Foresti, Senior Member, IEEE"
 ecdf8e5393eead0b63c5bc4fbe426db5a70574eb,Linear Subspace Learning for Facial Expression Analysis,"Linear Subspace Learning for
 Facial Expression Analysis
 Caifeng Shan
@@ -62461,16 +52768,8 @@ tioning may be informative because, although these processes overlap anatomicall
 re compromised in each network are different in ADHD and BD. Adults, aged 18 – 62, with ADHD (n ⫽
 2), BD (n ⫽ 20), and healthy controls (n ⫽ 21) performed an interleaved pro- and antisaccade task"
 ecbb05ad1d5ffc9bad3c33a8cb800d3a6d034159,Generative Sensing: Transforming Unreliable Sensor Data for Reliable Recognition,
-eca9b9dd665556423278b85f79e1d589009a7ea7,Person Re-Identi fi cation by Robust Canonical Correlation Analysis,"IEEE SIGNAL PROCESSING LETTERS, VOL. 22, NO. 8, AUGUST 2015
-Person Re-Identiﬁcation by Robust
-Canonical Correlation Analysis
-Le An, Songfan Yang, Member, IEEE, and Bir Bhanu, Fellow, IEEE"
 ec196dbede1772541bb9df2efeda655d377b291e,Fast Disparity Estimation Using Dense Networks,"Fast Disparity Estimation using Dense Networks*
 Rowel Atienza1"
-ec443db55db1a6721387b2054b94f6df020994ae,Weakly Supervised Visual Dictionary Learning by Harnessing Image Attributes,"Weakly Supervised Visual Dictionary Learning
-y Harnessing Image Attributes
-Yue Gao, Senior Member, IEEE, Rongrong Ji, Senior Member, IEEE, Wei Liu, Member, IEEE,
-Qionghai Dai, Senior Member, IEEE, and Gang Hua, Senior Member, IEEE"
 ec89c5f2f5acce23b0d05736cd9f32d4ca6dc382,Body Actions Change the Appearance of Facial Expressions,"Body Actions Change the Appearance of Facial
 Expressions
 Carlo Fantoni1,2*, Walter Gerbino1
@@ -62509,9 +52808,6 @@ Institute of Computing, University of Campinas (Unicamp), Campinas, Brazil.
 Department of Computing, S˜ao Paulo State University (Unesp), Bauru, Brazil.
 E-mails: {jow,
 Equal contributors."
-ec8eed7fd8549abb269d95a12d1ac1f2898ea2fb,Deep Class-Wise Hashing: Semantics-Preserving Hashing via Class-wise Loss,"Deep Class-Wise Hashing:
-Semantics-Preserving Hashing via Class-wise Loss
-Xuefei Zhe, Shifeng Chen, Member, IEEE, and Hong Yan, Fellow, IEEE"
 ece31d41b4da5457d570c04d22f19fcd026776b6,Learning Deep Disentangled Embeddings with the F-Statistic Loss,"Learning Deep Disentangled Embeddings
 With the F-Statistic Loss
 Karl Ridgeway
@@ -62538,10 +52834,6 @@ Fabio Remondino, Trento
 Markus Gerke, Twente"
 ec7d418ddf95d231b2afc70ed8c94d0764abec61,Knowledge Transfer Using Latent Variable Models,"Copyright
 Ayan Acharya"
-ec2a887e02237e0b221b721eedac14254ec681cf,Deep Feature Aggregation and Image Re-ranking with Heat Diffusion for Image Retrieval,"JOURNAL OF LATEX CLASS FILES, VOL. **, NO. **, AUGUST 2018
-Deep Feature Aggregation and Image Re-ranking
-with Heat Diffusion for Image Retrieval
-Shanmin Pang, Jin Ma, Jianru Xue, Member, IEEE, Jihua Zhu, Member, IEEE, Vicente Ordonez"
 ec0104286c96707f57df26b4f0a4f49b774c486b,An Ensemble CNN2ELM for Age Estimation,"An Ensemble CNN2ELM for Age Estimation
 Mingxing Duan , Kenli Li, Senior Member, IEEE, and Keqin Li, Fellow, IEEE"
 ecd0a2e55f456b69243d1278fee15d8dbfc98c28,Heterogeneous Multicores : When Slower is Faster,"Heterogeneous Multicores: When Slower is Faster
@@ -62549,13 +52841,6 @@ Tomas Hruby
 Herbert Bos
 The Network Institute, VU University Amsterdam
 Andrew S. Tanenbaum"
-ec3621e900cc50afd067584bb1246a8b4e338fa8,Structured Triplet Learning with POS-Tag Guided Attention for Visual Question Answering,"Structured Triplet Learning with POS-tag Guided Attention
-for Visual Question Answering
-Zhe Wang1 Xiaoyi Liu2 Liangjian Chen1 Limin Wang3 Yu Qiao4 Xiaohui Xie1 Charless Fowlkes1
-Dept. of CS, UC Irvine
-Microsoft
-CVL, ETH Zurich
-SIAT, CAS"
 ecf4690ddd3ad26f9cd1749d16ef1aa06d391f92,Does Exposure to Hostile Environments Predict Enhanced Emotion Detection?,"PDF hosted at the Radboud Repository of the Radboud University
 Nijmegen
 The following full text is a publisher's version.
@@ -62587,9 +52872,6 @@ Title
 Bilingualism and Children's Attention to Facial Expressions that Conflict with Lexical
 Content
 Amani Asad"
-37b6d6577541ed991435eaf899a2f82fdd72c790,Vision-based Human Gender Recognition: A Survey,"Vision-based Human Gender Recognition: A Survey
-Choon Boon Ng, Yong Haur Tay, Bok Min Goi
-Universiti Tunku Abdul Rahman, Kuala Lumpur, Malaysia."
 375993fd5f94c7b02169ff0d71a74d1b84262dfc,Parallel Application Library for Object Recognition,"Parallel Application Library for Object Recognition
 Bor-Yiing Su
 Electrical Engineering and Computer Sciences
@@ -62650,26 +52932,6 @@ Senstar Corporation
 Waterloo, Canada
 {Paul.Marchwica, Mike.Jamieson,
 the art"
-37a23e76674e606ce779131d2c93496e8a53bb2f,The discrete cosine transform ( DCT ) plus local normalization : a novel two-stage method for de-illumination in face recognition,"Optica Applicata, Vol. XLI, No. 4, 2011
-The discrete cosine transform (DCT)
-plus local normalization:
-novel two-stage method
-for de-illumination in face recognition
-MINGHUA ZHAO*, YINGHUI WANG, ZHENGHAO SHI, JIULONG ZHANG
-School of Computer Science and Engineering, Xi’an University of Technology, Xi’an710048, China
-*Corresponding author:
-To  deal  with  illumination  variations  in  face  recognition,  a  novel  two-stage  illumination
-normalization method is proposed in this paper. Firstly, a discrete cosine transform (DCT) is used
-on the original images in logarithm domain. DC coefficient is set based on the average pixel value
-of all the within-class training samples and some low frequency AC coefficients are set to zero to
-eliminate illumination variations in large areas. Secondly, local normalization method, which can
-minimize illumination variations in small areas, is used on the inverse DCT images. This makes
-the pixel values on the processed images be close to or equal to that of the normal illumination
-ondition. Experimental results, both on Yale B database and Extended Yale B database, show
-that the proposed method can eliminate effect of illumination variations effectively and improve
-performance  of  face  recognition  methods  significantly.  The  present  method  does  not  demand
-modeling step and can eliminate the effect of illumination variations before face recognition. In
-this way, it can be used as a preprocessing step for any existing face recognition method."
 37c014854655980870122143d16ecf585c7b8980,Crowd-Robot Interaction: Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learning,"Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learning
 Crowd-Robot Interaction:
 Changan Chen, Yuejiang Liu, Sven Kreiss, Alexandre Alahi"
@@ -62696,10 +52958,6 @@ This paper shows how the results returned by an image search engine
 an be used to construct models from Internet images and
 use them for object recognition.
 By Rob Fergus, Li Fei-Fei, Pietro Perona, Member IEEE, and Andrew Zisserman"
-37eb666b7eb225ffdafc6f318639bea7f0ba9a24,"Age , Gender and Race Estimation from Unconstrained Face Images","MSU Technical Report (2014): MSU-CSE-14-5
-Age, Gender and Race Estimation from
-Unconstrained Face Images
-Hu Han, Member, IEEE and Anil K. Jain, Fellow, IEEE"
 377a1be5113f38297716c4bb951ebef7a93f949a,Facial emotion recognition with anisotropic inhibited Gabor energy histograms,"Dear Faculty, IGERT Fellows, IGERT Associates and Students,
 You are cordially invited to attend a Seminar presented by Albert Cruz. Please
 plan to attend.
@@ -62746,9 +53004,6 @@ Faculty of Information Technology,
 IT4Innovations Centre of Excellence
 Bozetechova 1/2, Brno 61266, Czech Republic
 Bozetechova 1/2, Brno 61266, Czech Republic"
-3748a828dabc6b5292b53cec6080cef33d78d3e3,On Clustering and Embedding Manifolds using a Low Rank Neighborhood Approach,"On Clustering and Embedding Manifolds using a
-Low Rank Neighborhood Approach
-Arun M. Saranathan, Student Member, IEEE, and Mario Parente, Member, IEEE"
 372a8bf0ef757c08551d41e40cb7a485527b6cd7,Unsupervised Video Hashing by Exploiting Spatio-Temporal Feature,"Unsupervised Video Hashing by Exploiting
 Spatio-Temporal Feature
 Chao Ma, Yun Gu, Wei Liu, and Jie Yang(cid:63)
@@ -62811,23 +53066,6 @@ Baltimore, Maryland
 January, 2009
 (cid:176) Gagan Bansal 2009
 All rights reserved"
-375e478acf62eede1cc69693c54d81aa718df9e7,DFT domain Feature Extraction using Edge-based Scale Normalization for Enhanced Face Recognition,"Journal of Advanced Computer Science and Technology, 1 (3) (2012) 134-166
-(cid:13)Science Publishing Corporation
-www.sciencepubco.com/index.php/JACST
-DFT domain Feature Extraction using
-Edge-based Scale Normalization for
-Enhanced Face Recognition
-K Manikantan1,∗, S Ramachandran2,†
-Department of Electronics and Communication Engineering,
-M S Ramaiah Institute of Technology, Bangalore, Karnataka, India 560054
-Department of Electronics and Communication Engineering,
-S J B Institute of Technology, Bangalore, Karnataka, India 560060"
-370e0d9b89518a6b317a9f54f18d5398895a7046,Cross-pollination of normalisation techniques from speaker to face authentication using Gaussian mixture models,"IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, VOL. X, NO. X, XXXXXXX 20XX
-Cross-pollination of normalisation techniques
-from speaker to face authentication
-using Gaussian mixture models
-Roy Wallace, Member, IEEE, Mitchell McLaren, Member, IEEE, Christopher McCool, Member, IEEE,
-nd S´ebastien Marcel, Member, IEEE"
 3726b82007512a15a530fd1adad57af58a9abb62,Teaching Compositionality to CNNs,"Teaching Compositionality to CNNs∗
 Austin Stone
 Yi Liu
@@ -62869,26 +53107,6 @@ context-based approach for pedestrian detection
 Cristiano Premebida and Urbano Nunes
 The ﬁnal version is available at: http://ijr.sagepub.com/content/32/3.toc
 This is a pre-print version."
-3762bde6d3f21e8abc549d70709984c36b6bf3b6,Domain Adaptation for Pedestrian Detection Based on Prediction Consistency,"Hindawi Publishing Corporation
-e Scientiﬁc World Journal
-Volume 2014, Article ID 280382, 7 pages
-http://dx.doi.org/10.1155/2014/280382
-Research Article
-Domain Adaptation for Pedestrian Detection Based on
-Prediction Consistency
-Yu Li-ping,1,2 Tang Huan-ling,2 and An Zhi-yong1
-Key Laboratory of Intelligent Information Processing, Universities of Shandong (Shandong Institute of Business and Technology),
-Yantai 264005, China
-School of Computer Science and Technology, Shandong Institute of Business and Technology, Yantai 264005, China
-Correspondence should be addressed to An Zhi-yong;
-Received 25 March 2014; Revised 20 May 2014; Accepted 21 May 2014; Published 10 June 2014
-Academic Editor: Liang Lin
-Copyright © 2014 Yu Li-ping et al. This is an open access article distributed under the Creative Commons Attribution License,
-which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
-Pedestrian detection is an active area of research in computer vision. It remains a quite challenging problem in many applications
-where many factors cause a mismatch between source dataset used to train the pedestrian detector and samples in the target
-scene. In this paper, we propose a novel domain adaptation model for merging plentiful source domain samples with scared target
-domain samples to create a scene-specific pedestrian detector that performs as well as rich target domain simples are present."
 37992120053b50b2f92eaa1949273bf828a54b50,Face Recognition Techniques-An evaluation Study,"Int. J. Advanced Networking and Applications
 Volume: 6 Issue: 4 Pages: 2393-2397       (2015) ISSN: 0975-0290
 Face Recognition Techniques - An evaluation
@@ -62909,17 +53127,6 @@ Stephens, R. G., Semmler, C., & Sauer, J. D. (2017, August 14). The Effect of th
 Mismatching Trials and Task Orientation on the Confidence–Accuracy Relationship in Unfamiliar
 Face Matching. Journal of Experimental Psychology: Applied. Advance online publication.
 http://dx.doi.org/10.1037/xap0000130"
-37b0357d2db89bc4560d4201c3c2478988c87640,Face Recognition Based on Curvelet Transform and LS-SVM,"ISBN 978-952-5726-02-2 (Print), 978-952-5726-03-9 (CD-ROM)
-Proceedings  of  the  2009  International  Symposium  on  Information  Processing  (ISIP’09)
-Huangshan, P. R. China, August 21-23, 2009, pp. 140-143
-Face Recognition Based on Curvelet Transform
-nd LS-SVM
-School of Electronics, Jiangxi University of Finance and Economics, Nanchang, China
-Jianhong Xie
-long
-reduce
-singularities
-urves.  To"
 f9f08511f77c29ff948e146434dfb23608d3deb5,Question Answering Using Match-LSTM and Answer Pointer,"Question Answering Using Match-LSTM and Answer Pointer
 Annie Hu, Cindy Wang, and Brandon Yang
 {anniehu, ciwang,
@@ -62940,26 +53147,6 @@ encoding and decoding layers, and calculating attention as our interaction layer
 Dataset
 The dataset used is the recently released Stanford Question Answering Dataset (SQuAD)[1].
 The context paragraphs are extracted from Wikipedia, while questions and answers are human-"
-f93606d362fcbe62550d0bf1b3edeb7be684b000,Nearest Neighbor Classifier Based on Nearest Feature Decisions,"The Computer Journal Advance Access published February 1, 2012
-© The Author 2012. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved.
-For Permissions, please email:
-doi:10.1093/comjnl/bxs001
-Nearest Neighbor Classiﬁer Based
-on Nearest Feature Decisions
-Alex Pappachen James1,∗ and Sima Dimitrijev2
-Machine Intelligence Group, School of Computer Science, Indian Institute of Information Technology and
-Queensland Micro- and Nanotechnology Centre and Grifﬁth School of Engineering, Grifﬁth University,
-Management, Kerala, India
-Nathan, Australia
-Corresponding author:
-High feature dimensionality of realistic datasets adversely affects the recognition accuracy of nearest
-neighbor (NN) classiﬁers. To address this issue, we introduce a nearest feature classiﬁer that shifts
-the NN concept from the global-decision level to the level of individual features. Performance
-omparisons with 12 instance-based classiﬁers on 13 benchmark University of California Irvine
-lassiﬁcation datasets show average improvements of 6 and 3.5% in recognition accuracy and
-rea under curve performance measures, respectively. The statistical signiﬁcance of the observed
-performance improvements is veriﬁed by the Friedman test and by the post hoc Bonferroni–Dunn
-test. In addition, the application of the classiﬁer is demonstrated on face recognition databases, a"
 f9028b47a4755a7349108b1dc281f13add5c6c12,Atypical gaze patterns in children and adults with autism spectrum disorders dissociated from developmental changes in gaze behaviour,"Downloaded from
 http://rspb.royalsocietypublishing.org/
 on June 9, 2017
@@ -63032,11 +53219,6 @@ Marian Moise, Xue Dong Yang and Richard Dosselmann
 Department of Computer Science, University of Regina, 3737 Wascana Parkway, Regina, Saskatchewan, Canada
 Keywords:
 Face Recognition, Generalized Hough Transform, Image Descriptors."
-f921e6f5085f1ebbd8289081e499240a89bf6c43,Three-Dimensional Face Recognition in the Presence of Facial Expressions: An Annotated Deformable Model Approach,"Three-Dimensional Face Recognition
-in the Presence of Facial Expressions:
-An Annotated Deformable Model Approach
-Ioannis A. Kakadiaris, Member, IEEE, Georgios Passalis, George Toderici,
-Mohammed N. Murtuza, Yunliang Lu, Nikos Karampatziakis, and Theoharis Theoharis"
 f9784db8ff805439f0a6b6e15aeaf892dba47ca0,"Comparing the performance of Emotion-Recognition Implementations in OpenCV , Cognitive Services , and Google Vision APIs","Comparing the performance of Emotion-Recognition Implementations
 in OpenCV, Cognitive Services, and Google Vision APIs
 LUIS ANTONIO BELTRÁN PRIETO, ZUZANA KOMÍNKOVÁ OPLATKOVÁ
@@ -63051,9 +53233,6 @@ Bhargava Urala Kota
 Venu Govindaraju
 University at Buffalo, SUNY
 {rpandey, yingbozh, buralako,"
-f9129b3858c14b5f6cca1fcbf31c4816d94a5038,A Robust 3D-2D Interactive Tool for Scene Segmentation and Annotation,"A Robust 3D-2D Interactive Tool for Scene
-Segmentation and Annotation
-Duc Thanh Nguyen, Binh-Son Hua∗, Lap-Fai Yu, Member, IEEE, and Sai-Kit Yeung, Member, IEEE"
 f98a975642972ce24e42e6957f63be556c11dd31,Dynamic Obstacle Detection of Road Scenes using Equi-Height Mosaicking Image,"Electronic Letters on Computer Vision and Image Analysis 13(2):13-14, 2014
 Dynamic Obstacle Detection of Road Scenes
 using Equi-Height Mosaicking Image
@@ -63102,10 +53281,6 @@ Silvia Santano Guill´en, Luigi Lo Iacono, Christian Meder"
 f98cbf32989387733529fa4fc943f0a7e97b5c07,To Know and To Learn - About the Integration of Knowledge Representation and Deep Learning for Fine-Grained Visual Categorization,
 f92ceb6875f614bbccb25e4b11ca55353773890f,Saliency Detection via Boundary Prior and Center Prior,"International Robotics & Automation Journal
 Saliency Detection via Boundary Prior and Center Prior"
-f8a2a6b821a092ac43acd4e7366fe7c1e9285317,Attribute-controlled face photo synthesis from simple line drawing,"ATTRIBUTE-CONTROLLED FACE PHOTO SYNTHESIS FROM SIMPLE LINE DRAWING
-Qi Guo Ce Zhu Zhiqiang Xia Zhengtao Wang Yipeng Liu
-School of Electronic Engineering / Center for Robotics
-University of Electronic Science and Technology of China (UESTC), Chengdu, China"
 f8796b8e8246ce41efb2904c053fe0ea2868e373,A Variational U-Net for Conditional Appearance and Shape Generation,"A Variational U-Net for Conditional Appearance and Shape Generation
 Patrick Esser∗, Ekaterina Sutter∗, Bj¨orn Ommer
 Heidelberg Collaboratory for Image Processing
@@ -63151,18 +53326,6 @@ f89e5a8800b318fa03289b5cc67df54b956875b4,Do GANs actually learn the distribution
 Sanjeev Arora
 Yi Zhang
 July 4, 2017"
-f8c94afd478821681a1565d463fc305337b02779,Design and Implementation of Robust Face Recognition System for Uncontrolled Pose and Illumination Changes,"www.semargroup.org,
-www.ijsetr.com
-ISSN 2319-8885
-Vol.03,Issue.25
-September-2014,
-Pages:5079-5085
-Design and Implementation of Robust Face Recognition System for
-Uncontrolled Pose and Illumination Changes
-VIJAYA BHASKAR TALARI
-, VENKATESWARLU PRATTI
-PG Scholar, Dept of ECE, LITAM, JNTUK, Andhrapradesh, India, Email:
-Assistant Professor, Dept of ECE, LITAM, JNTUK, Andhrapradesh, India, Email:"
 f881d2a04de838c8950a279e1ed8c0f9886452af,Multi-Stage Variational Auto-Encoders for Coarse-to-Fine Image Generation,"Multi-Stage Variational Auto-Encoders for
 Coarse-to-Fine Image Generation
 Lei Cai
@@ -63201,12 +53364,6 @@ ISSN 2229-5518
 Artificial Neural Network Design and Parameter
 Optimization for Facial Expressions Recognition
 Ammar A. Alzaydi"
-f8b37756c5d8b3af3bf78a2f3dae293725074965,CBVR for Face Based Digital Signatures,"IJCST Vol. 3, ISSue 3, July - SepT 2012
-ISSN : 0976-8491 (Online)  |  ISSN : 2229-4333 (Print)
-CBVR for Face Based Digital Signatures
-M. Nagaraju, 2M. Thanoj, 3K. Lakshmi Tejaswini, 4A. Koteswaramma
-,3,4Dept. of IT, Gudlavalleru Engineering College, AP, India
-Dept. of CSE, Andhra Loyola Institute of Engineering and Technology, Vijayawada, AP, India"
 f8e0910d50d7dffe7097b6263c6bb3952b1de336,50 Years of Test (Un)fairness: Lessons for Machine Learning,"50 Years of Test (Un)fairness: Lessons for Machine Learning
 Ben Hutchinson and Margaret Mitchell"
 f8ec92f6d009b588ddfbb47a518dd5e73855547d,Extreme Learning Machine Ensemble Using Bagging for Facial Expression Recognition,"J Inf Process Syst, Vol.10, No.3, pp.443~458, September 2014
@@ -63215,12 +53372,6 @@ ISSN 2092-805X (Electronic)
 Extreme Learning Machine Ensemble Using
 Bagging for Facial Expression Recognition
 Deepak Ghimire* and Joonwhoan Lee*"
-f8cfabecbe587c611de2696a37f96e3f77ac8555,NEMGAN: Noise Engineered Mode-matching GAN,"NEMGAN: Noise Engineered Mode-matching GAN
-Deepak Mishra∗, Prathosh AP∗, Aravind J, Prashant Pandey
-& Santanu Chaudhury
-Department of Electrical Engineering
-Indian Institute of Technology Delhi
-New Delhi, India"
 f8facd9691b9b41392aef606aea5e6bc2e7d489c,Recognition of Facial Expressions by Cortical Multi-scale Line and Edge Coding,"Recognition of facial expressions by cortical
 multi-scale line and edge coding
 R.J.R. de Sousa, J.M.F. Rodrigues and J.M.H. du Buf
@@ -63266,15 +53417,6 @@ Namita Rathore1 Rohit Miri2
 defense
 systems,
 surveillance"
-f842b13bd494be1bbc1161dc6df244340b28a47f,An Improved Face Recognition Technique Based on Modular Multi-directional Two-dimensional Principle Component Analysis Approach,"An Improved Face Recognition Technique Based
-on Modular Multi-directional Two-dimensional
-Principle Component Analysis Approach
-Department of    Physics and Electronic Engineering, Hanshan Normal University, Chaozhou, 521041, China
-Xiaoqing Dong
-Department of    Physics and Electronic Engineering, Hanshan Normal University, Chaozhou, 521041, China
-Email:
-Hongcai Chen
-Email:"
 f8a5bc2bd26790d474a1f6cc246b2ba0bcde9464,"KDEF-PT: Valence, Emotional Intensity, Familiarity and Attractiveness Ratings of Angry, Neutral, and Happy Faces","ORIGINAL RESEARCH
 published: 19 December 2017
 doi: 10.3389/fpsyg.2017.02181
@@ -63330,23 +53472,6 @@ Stefan Becker, Wolfgang H¨ubner, and Michael Arens
 Fraunhofer IOSB
 Fraunhofer Institute for Optronics, System Technologies, and Image Exploitation
 Gutleuthausstr. 1, 76275 Ettlingen, Germany"
-f8ddeb23343cde8e2a9fdd87e877f0ce5461b42b,Illumination and Pose Invariant Face Recognition : A Technical Review,"International Journal of Computer Information Systems and Industrial Management Applications (IJCISIM)
-ISSN: 2150-7988 Vol.2 (2010), pp.029-038
-http://www.mirlabs.org/ijcisim
-Illumination and Pose Invariant Face Recognition: A Technical Review
-Kavita. R. Singh
-Department of Computer
-Technology, YCCE, Nagpur(M.S),
-41 110, India
-Mukesh. A. Zaveri
-Computer Engineering
-Department, S.V.National Institute
-of Technology, Surat(Gujarat),
-29507, India
-Mukesh. M. Raghuwanshi
-NYSS College of Engineering and
-Research, Nagpur(M.S), 441 110,
-India"
 e3e66ee37d08752dc19c3e3b212f869c8ff19f71,Effective Interaction-aware Trajectory Prediction using Temporal Convolutional Neural Networks,"Effective Interaction-aware Trajectory Prediction using
 Temporal Convolutional Neural Networks
 Noha Radwan
@@ -63355,12 +53480,6 @@ e39f9565903a9701657ce3ade94c37d8a12f702e,Audio-Visual Scene Analysis with Self-S
 Self-Supervised Multisensory Features
 Andrew Owens Alexei A. Efros
 UC Berkeley"
-e3582dffe5f3466cc5bc9d736934306c551ab33c,AttGAN: Facial Attribute Editing by Only Changing What You Want,"SUBMITTED MANUSCRIPT TO IEEE TRANSACTIONS ON IMAGE PROCESSING
-AttGAN: Facial Attribute Editing by
-Only Changing What You Want
-Zhenliang He, Wangmeng Zuo, Senior Member, IEEE, Meina Kan, Member, IEEE,
-Shiguang Shan, Senior Member, IEEE, and Xilin Chen, Fellow, IEEE
-i.e.,"
 e3bbdd6efc906f6ae17e5b1d62497420991b977d,Visual Explanation by High-Level Abduction: On Answer-Set Programming Driven Reasoning About Moving Objects,"Visual Explanation by High-Level Abduction
 On Answer-Set Programming Driven Reasoning about Moving Objects
 Jakob Suchan1, Mehul Bhatt1,2, Przemysław Wał˛ega3, and Carl Schultz4
@@ -63451,19 +53570,6 @@ Germany"
 e3c420b29b8590442decd330ef70494c2209f149,Learning a Part-Based Pedestrian Detector in a Virtual World,"Learning a Part-based Pedestrian Detector in Virtual
 World
 Jiaolong Xu, David V´azquez, Antonio M. L´opez Member, IEEE, Javier Mar´ın and Daniel Ponsa"
-e3f0c5a51d6c5085fbcb64d872d7db438da27474,Ubiquitously Supervised Subspace Learning,"Ubiquitously Supervised Subspace Learning
-Jianchao Yang, Student Member, IEEE, Shuicheng Yan, Member, IEEE, and Thomas S. Huang, Life Fellow, IEEE"
-e3b40ffd57a676aef377ef463849fd6b9a3d3b5d,Morphable hundred-core heterogeneous architecture for energy-aware computation,"Received on 16th April 2014
-Revised on 23rd June 2014
-Accepted on 7th August 2014
-doi: 10.1049/iet-cdt.2014.0078
-www.ietdl.org
-ISSN 1751-8601
-Morphable hundred-core heterogeneous architecture
-for energy-aware computation
-Nuno Neves, Henrique Mendes, Ricardo Jorge Chaves, Pedro Tomás, Nuno Roma
-INESC-ID, Instituto Superior Técnico, Universidade de Lisboa, Rua Alves Redol, 9, 1000-029 Lisboa, Portugal
-E-mail:"
 e33b1833b2d0cd7b0450b22b96a567a59c9e4685,Attribute Discovery via Predictable Discriminative Binary Codes,"Attribute Discovery via
 Predictable Discriminative Binary Codes
 Mohammad Rastegari†
@@ -63484,15 +53590,6 @@ Engineering Sciences
 on 3rd Sept 2014"
 e3e44385a71a52fd483c58eb3cdf8d03960c0b70,A Hierarchical Graphical Model for Recognizing Human Actions and Interactions in Video,"Copyright
 Sangho Park"
-e31f24b92a19aeb9a7611a9ca09223c8f5238ae1,Expression Empowered ResiDen Network for Facial Action Unit Detection,"RESIDEN: RESIDUE FLOW IN DENSENET
-Expression Empowered ResiDen Network
-for Facial Action Unit Detection
-Shreyank Jyoti
-Abhinav Dhall
-Learning Affect and Semantic Image
-nalysIs (LASII) Group,
-Indian Institute of Technology Ropar
-Punjab, India"
 e3c5c5623af4b1a1f719cac24850dcaa6a304bd5,Training Effective Node Classifiers for Cascade Classification,"ppearing in Int. J. Comput. Vis.; content may change prior to ﬁnal publication.
 Training Effective Node Classiﬁers for Cascade
 Classiﬁcation
@@ -63512,10 +53609,6 @@ Bo Sun, Siming Cao, Jun He, Lejun Yu, Liandong Li, “Automatic temporal segment
 detection via bilateral long short-term memory recurrent neural networks,” J.
 Electron. Imaging 26(2), 020501 (2017), doi: 10.1117/1.JEI.26.2.020501.
 Downloaded From: http://electronicimaging.spiedigitallibrary.org/ on 03/03/2017 Terms of Use: http://spiedigitallibrary.org/ss/termsofuse.aspx"
-e3f6108163b64ca4aa94d9be77c753b377fcda87,USING COMPETITIVE PROTOTYPES FOR THE VERIFICATION ON UNSPECIFIC PERSON,"State Key Lab of Intelligent Technology and Systems, Tsinghua Univ., Beijing, China
-ON UNSPECIFIC PERSON
-Qiong Yang,   Xiaoqing Ding
-USING COMPETITIVE PROTOTYPES FOR THE VERIFICATION"
 e3b0caa1ff9067665e349a2480b057e2afdbc41f,Interactive Effects of Obvious and Ambiguous Social Categories on Perceptions of Leadership: When Double-Minority Status May Be Beneficial.,"702373 PSPXXX10.1177/0146167217702373Personality and Social Psychology BulletinWilson et al.
 research-article2017
 Article
@@ -63565,19 +53658,6 @@ Toshiba RDC, Kawasaki, Japan,
 http://clementcreusot.com/pedestrian"
 e3f2e337d4470545398cc6753a54c21debf9c37b,Potential Contrast – A New Image Quality Measure,"Potential Contrast – A New Image Quality Measure
 Arie Shaus, Shira Faigenbaum-Golovin, Barak Sober, Eli Turkel, Eli Piasetzky; Tel Aviv University; Tel Aviv, Israel"
-e30b14ad7341a596768bd67f854d1ed4ede2abc8,A Principal Component Analysis Method for Recognition of Human Faces : Eigenfaces Approach,"International Journal of Electronics Communication and Computer Technology (IJECCT)
-Volume 2 Issue 3 (May 2012)
-A Principal Component Analysis Method for
-Recognition of Human Faces: Eigenfaces Approach
-Shemi P M
-Department of Electronics,
-M E S College, Marampally, Aluva,
-Ernakulam, India
-Ali M A
-Department of MCA,
-Government Engineering College,
-Thrissur, India
-is  very  much"
 32103c021e4d52f9915c3236669de5da973fb13f,Affective Image Content Analysis: A Comprehensive Survey,Proceedings of the Twenty-Seventh International Joint Conference on Artiﬁcial Intelligence (IJCAI-18)
 323cd51bc18c700fa88044dd24ae663a7eabaa68,Utilizing student activity patterns to predict performance,"Casey and Azcona International Journal of Educational Technology
 in Higher Education  (2017) 14:4
@@ -63612,11 +53692,6 @@ Full Terms & Conditions of access and use can be found at
 http://www.tandfonline.com/action/journalInformation?journalCode=tgis20
 Download by: [UC Santa Barbara Library]
 Date: 09 January 2017, At: 09:44"
-320e2c950d5b31cb371208a6b752a94585ac6665,Context-Patch Face Hallucination Based on Thresholding Locality-constrained Representation and Reproducing Learning,"Context-Patch Face Hallucination Based on
-Thresholding Locality-constrained Representation
-nd Reproducing Learning
-Junjun Jiang, Member, IEEE, Yi Yu, Suhua Tang, Member, IEEE, Jiayi Ma, Member, IEEE, Akiko Aizawa, and
-Kiyoharu Aizawa, Fellow, IEEE"
 324cf94743359df3ada2f86ee8cd3bb6dccae695,FERA 2015-Second Facial Expression Recognition and Analysis Challenge,"FG 2015
 FG 2015 Submission. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE.
 FG 2015
@@ -63717,11 +53792,6 @@ CVPR 2008 Submission #2670. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE.
 Multi-Image Graph Cut Clothing Segmentation for Recognizing People
 Anonymous CVPR submission
 Paper ID 2670"
-32420c65f8ef0c5bd83b14c8ae662cbce73e6781,Face Recognition with Local Binary Patterns,"Face Recognition with Local Binary Patterns
-Timo Ahonen, Abdenour Hadid, and Matti Pietik¨ainen
-Machine Vision Group, Infotech Oulu
-PO Box 4500, FIN-90014 University of Oulu, Finland,
-http://www.ee.oulu.fi/mvg/"
 32b9be86de4f82c5a43da2a1a0a892515da8910d,Robust False Positive Detection for Real-Time Multi-target Tracking,"Robust False Positive Detection for Real-Time
 Multi-Target Tracking
 Henrik Brauer, Christos Grecos, and Kai von Luck
@@ -63738,35 +53808,6 @@ ETH Zurich"
 322ff387087134ac776a4270cd55e7f3334edeb2,"Image Features Detection , Description and Matching","Image Features Detection, Description
 nd Matching
 M. Hassaballah, Aly Amin Abdelmgeid and Hammam A. Alshazly"
-32732095eae3a33614cd6cef2a82e6189f5a28a9,Locally linear representation for subspace learning and clustering,"Locally linear representation for subspace
-learning and clustering
-Liangli Zhen, Zhang Yi, Xi Peng, Dezhong Peng
-It is a key to construct a similarity graph in graph-oriented subspace
-learning and clustering. In a similarity graph, each vertex denotes
-data point and the edge weight represents the similarity between
-two points. There are two popular schemes to construct a similarity
-graph, i.e., pairwise distance based scheme and linear representation
-ased scheme. Most existing works have only involved one of the
-bove schemes and suffered from some limitations. Speciﬁcally, pairwise
-distance based methods are sensitive to the noises and outliers compared
-with linear representation based methods. On the other hand,
-there
-is the possibility that linear representation based algorithms wrongly
-select inter-subspaces points to represent a point, which will degrade
-the performance. In this paper, we propose an algorithm, called Locally
-Linear Representation (LLR), which integrates pairwise distance with
-linear representation together to address the problems. The proposed
-lgorithm can automatically encode each data point over a set of points
-that not only could denote the objective point with less residual error, but"
-3214ce1c8c86c0c4670e3f8b8f4351d8fa44434d,Deep Semantic Pyramids for Human Attributes and Action Recognition,"Deep Semantic Pyramids for Human Attributes
-nd Action Recognition
-Fahad Shahbaz Khan1(B), Rao Muhammad Anwer2, Joost van de Weijer3,
-Michael Felsberg1, and Jorma Laaksonen2
-Computer Vision Laboratory, Link¨oping University, Link¨oping, Sweden
-Department of Information and Computer Science,
-Aalto University School of Science, Aalto, Finland
-Computer Vision Center, CS Department, Universitat Autonoma de Barcelona,
-Barcelona, Spain"
 325c9f6f848407a22b86e3253cb7f29fac19e40c,Change Detection in Crowded Underwater Scenes - Via an Extended Gaussian Switch Model Combined with a Flux Tensor Pre-segmentation,"Change Detection in Crowded Underwater Scenes
 via an Extended Gaussian Switch Model combined with a Flux Tensor
 Pre-Segmentation
@@ -63809,46 +53850,6 @@ EMOTION RECOGNITION
 Xiang Xiang, Minh Dao, Gregory D. Hager, Trac D. Tran
 Johns Hopkins University, 3400 N. Charles Street, Baltimore, MD 21218, USA
 {xxiang, minh.dao, ghager1,"
-3264df8917ad5e39e9a7f33bbfbce25ac7473a9b,JOURNA Robust and Efficient Approach Based Face Recognition System Using Log Likely,"[Kaphungkui, 2(3): March, 2013
-013]
-ISSN: 2277
-ISSN: 2277-9655
-IJESRT
-INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH
-INTERNATIONAL JOURNA
-ENCES & RESEARCH
-TECHNOLOGY
-Robust and Efficient Approach Based Face Recognition System Using Log Likely
-Robust and Efficient Approach Based Face Recognition System Using Log Likely
-Robust and Efficient Approach Based Face Recognition System Using Log Likely
-Hood Ratio
-V. Karthikeyan*1, V.J.Vijayalakshmi2
-V. Karthikeyan
-*1Department of ECE, SVSCE, J.P. Nagar, Arasampalayam,Coimbatore, Tamilnadu,
-Department of ECE, SVSCE, J.P. Nagar, Arasampalayam,Coimbatore, Tamilnadu,
-Department of ECE, SVSCE, J.P. Nagar, Arasampalayam,Coimbatore, Tamilnadu, India
-Department of EEE, SKCET, B.K Pudur Kovaipudur, Coimbatore, Tamilnadu, India
-Department of EEE, SKCET, B.K Pudur Kovaipudur, Coimbatore, Tamilnadu, India"
-324f39fb5673ec2296d90142cf9a909e595d82cf,Relationship Matrix Nonnegative Decomposition for Clustering,"Hindawi Publishing Corporation
-Mathematical Problems in Engineering
-Volume 2011, Article ID 864540, 15 pages
-doi:10.1155/2011/864540
-Research Article
-Relationship Matrix Nonnegative
-Decomposition for Clustering
-Ji-Yuan Pan and Jiang-She Zhang
-Faculty of Science and State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong
-University, Xi’an Shaanxi Province, Xi’an 710049, China
-Correspondence should be addressed to Ji-Yuan Pan,
-Received 18 January 2011; Revised 28 February 2011; Accepted 9 March 2011
-Academic Editor: Angelo Luongo
-Copyright q 2011 J.-Y. Pan and J.-S. Zhang. This is an open access article distributed under
-the Creative Commons Attribution License, which permits unrestricted use, distribution, and
-reproduction in any medium, provided the original work is properly cited.
-Nonnegative matrix factorization (cid:2)NMF(cid:3) is a popular tool for analyzing the latent structure of non-
-negative data. For a positive pairwise similarity matrix, symmetric NMF (cid:2)SNMF(cid:3) and weighted
-NMF (cid:2)WNMF(cid:3) can be used to cluster the data. However, both of them are not very ef‌f‌icient
-for the ill-structured pairwise similarity matrix. In this paper, a novel model, called relationship"
 326df1b94624b7958cff0f7e3d16e612ea9d7e4d,Similarity rank correlation for face recognition under unenrolled pose,"Similarity Rank Correlation for Face
 Recognition Under Unenrolled Pose
 Marco K. M¨uller, Alexander Heinrichs, Andreas H.J. Tewes,
@@ -63907,13 +53908,6 @@ School of Information and Communication Engineering, Inha University, Incheon, K
 localization at intersections
 supplemental material for “Vision-Based Localization at Intersections using Digital Maps”
 Augusto L. Ballardini, Daniele Cattaneo, and Domenico G. Sorrenti"
-329c06c00c627c0b041d330f3c0142a88b7cb1e5,Bayesian Sparsification of Gated Recurrent Neural Networks,"Bayesian Sparsiﬁcation of Gated Recurrent Neural
-Networks
-Ekaterina Lobacheva1∗, Nadezhda Chirkova1∗, Dmitry Vetrov1,2
-Samsung-HSE Laboratory, National Research University Higher School of Economics
-Samsung AI Center
-Moscow, Russia
-{elobacheva, nchirkova,"
 322c063e97cd26f75191ae908f09a41c534eba90,Improving Image Classification Using Semantic Attributes,"Noname manuscript No.
 (will be inserted by the editor)
 Improving Image Classiﬁcation using Semantic Attributes
@@ -63931,11 +53925,6 @@ Udo Frese, Tim Laue, Oliver Birbach, and Thomas R¨ofer
 Guest Editors: Till Mossakowski, Markus Roggenbach, Lutz Schr¨oder
 Managing Editors: Tiziana Margaria, Julia Padberg, Gabriele Taentzer
 ISSN 1863-2122"
-32c6086b1605698c8b775b6920741981e85b217d,Wearable Computing Designing and Sharing Activity-Recognition Systems Across Platforms,"IEEE RAM - SPECIAL ISSUE TOWARDS A WWW FOR ROBOTS
-Designing and sharing activity recognition systems
-cross platforms: methods from wearable computing
-Daniel Roggen, Member, IEEE, and St´ephane Magnenat, Member, IEEE, and Markus Waibel, Member, IEEE,
-nd Gerhard Tr¨oster, Senior Member, IEEE"
 32a6f6aa50ce2a631bf4de7432f830b29b6b05f2,Through the eyes of a child: preschoolers' identification of emotional expressions from the child affective facial expression (CAFE) set.,"Cognition and Emotion
 ISSN: 0269-9931 (Print) 1464-0600 (Online) Journal homepage: http://www.tandfonline.com/loi/pcem20
 Through the eyes of a child: preschoolers’
@@ -64034,10 +54023,6 @@ K´evin Huguenin
 UNIL–HEC Lausanne
 Italo Dacosta
 Jean-Pierre Hubaux"
-fbb2f81fc00ee0f257d4aa79bbef8cad5000ac59,Reading Hidden Emotions: Spontaneous Micro-expression Spotting and Recognition,"Reading Hidden Emotions: Spontaneous
-Micro-expression Spotting and Recognition
-Xiaobai Li, Student Member, IEEE, Xiaopeng Hong, Member, IEEE, Antti Moilanen, Xiaohua Huang, Student
-Member, IEEE, Tomas Pﬁster, Guoying Zhao, Senior Member, IEEE, and Matti Pietik¨ainen, Fellow, IEEE"
 fbbccf0454c84bea1fd5c5a1dcd9fd7bba301a44,Face detection using gradient vector flow,"Proceedings of  the Second International Conference on Machine Learning and Cybernetics, Wan, 2-5 November 2003
 FACE DETECTION USING GRADIENT VECTOR FLOW
 MAYANK VATSA,  RICHA SINCH, P. GUPTA
@@ -64115,16 +54100,6 @@ teaching and research institutions in France or
 broad, or from public or private research centers.
 L’archive ouverte pluridisciplinaire HAL, est
 destinée au dépôt et à la diffusion de documents"
-fbace36d9161fbd062eefa0c005362bb210c7097,VPGNet: Vanishing Point Guided Network for Lane and Road Marking Detection and Recognition,"VPGNet: Vanishing Point Guided Network for Lane and Road Marking
-Detection and Recognition
-Junsik Kim†
-Jae Shin Yoon†
-Seokju Lee†
-Namil Kim† Tae-Hee Lee‡ Hyun Seok Hong‡ Seung-Hoon Han‡
-Robotics and Computer Vision Lab., KAIST
-Seunghak Shin† Oleksandr Bailo†
-In So Kweon†
-Samsung Electronics DMC R&D Center"
 fb82681ac5d3487bd8e52dbb3d1fa220eeac855e,"Summary of Research on Informant Accuracy in Network Data, 11 and on the Reverse Small World Problem","CONNECTIONS
 VOLUME IV, NUMBER 2
 Summer 1981
@@ -64160,9 +54135,6 @@ Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildo
 (R.A.N.); (N.Q.T.)
 * Correspondence: Tel.: +82-10-3111-7022; Fax: +82-2-2277-8735
 Received: 3 May 2018; Accepted: 22 May 2018; Published: 24 May 2018"
-fb732b15fd5235893228ad3249cf04e1809034c9,CBVMR: Content-Based Video-Music Retrieval Using Soft Intra-Modal Structure Constraint,"Content-Based Video–Music Retrieval
-Using Soft Intra-Modal Structure Constraint
-Sungeun Hong, Student Member, IEEE, Woobin Im, and Hyun S. Yang, Member, IEEE"
 fbd169c0f700fcca26a74c79bb46c5ca2d37648a,FACIAL FEATURE BASED HEAD TRACKING AND POSE ESTIMATION,"FACIAL FEATURE BASED HEAD
 TRACKING AND POSE ESTIMATION
 Jari Hannuksela"
@@ -64453,10 +54425,6 @@ Esam A. S. Alzqhoul 1, 2, Balamurali B. T. Nair 1, 2, Bernard J. Guillemin 1, 2
 Mobile Phone Speech
 Forensic and Biometrics Research Group (FaB), The University of Auckland, New Zealand
 Department of Electrical and Computer Engineering, The University of Auckland, New Zealand"
-9fd5ecc538a9344814dc00b92beb45c54d5dff3e,NIC: A Robust Background Extraction Algorithm for Foreground Detection in Dynamic Scenes,"NIC: A Robust Background Extraction Algorithm
-for Foreground Detection in Dynamic Scenes
-Thien Huynh-The, Student Member, IEEE, Oresti Banos, Member, IEEE, Sungyoung Lee, Member, IEEE,
-Byeong Ho Kang, Eun-Soo Kim, and Thuong Le-Tien, Member, IEEE"
 4f051022de100241e5a4ba8a7514db9167eabf6e,Face Parsing via a Fully-Convolutional Continuous CRF Neural Network,"Face Parsing via a Fully-Convolutional Continuous
 CRF Neural Network
 Lei Zhou, Zhi Liu, Senior Member, IEEE, Xiangjian He, Senior Member, IEEE"
@@ -64608,19 +54576,6 @@ Gwalior"
 4f0aedbd0b5cb5939449da41579c93b98048fcdc,Robust classification using structured sparse representation,"Robust Classiﬁcation using Structured Sparse Representation
 Center for Imaging Science, Johns Hopkins University, Baltimore MD 21218, USA
 Ehsan Elhamifar Ren´e Vidal"
-4fdbe95edb967bfc0b44f0fa291cd86b178fca2e,"Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion Segmentation","Competitive Collaboration: Joint Unsupervised
-Learning of Depth, Camera Motion, Optical
-Flow and Motion Segmentation
-Anurag Ranjan1
-Varun Jampani2
-Kihwan Kim 2
-Deqing Sun 2
-Jonas Wulff 1
-Michael J. Black1
-Max Planck Institute for Intelligent Systems
-NVIDIA Research
-{aranjan, jwulff,
-{vjampani, kihwank,"
 4f10b81f822091ce2142e33f0578940da1e25ad3,"Indoor Mobile Robotics at Grima, PUC","Noname manuscript No.
 (will be inserted by the editor)
 Indoor Mobile Robotics at Grima, PUC
@@ -64794,10 +54749,6 @@ nd speechreading systems in natural conditions
 Philippe Daubias, Paul Del´eglise
 Laboratoire d’Informatique de l’Universit´e du Maine
 Le Mans, France"
-9ef73533507b46278d0d27c41e16af2b8ecf23ef,A comparative assessment of appearance based feature extraction techniques and their susceptibility to image degradations in face recognition systems,"A comparative assessment of appearance based
-feature extraction techniques and their susceptibility
-to image degradations in face recognition systems
-Vitomir ˇStruc and Nikola Paveˇsi´c, Member, IEEE"
 9ed3e04586f311b1e2b5ded9c9c4bfeeecf27f0c,Understanding rapid category detection via multiply degraded images.,"http://journalofvision.org/9/6/19/
 Understanding rapid category detection via multiply
 degraded images
@@ -64899,12 +54850,6 @@ Waghmare Supriya, Wavhal Archana, Patil Nital, Tapkir Yogita, Prof. Yogesh Thora
 9e0285debd4b0ba7769b389181bd3e0fd7a02af6,From Face Images and Attributes to Attributes,"From face images and attributes to attributes
 Robert Torfason, Eirikur Agustsson, Rasmus Rothe, Radu Timofte
 Computer Vision Laboratory, ETH Zurich, Switzerland"
-9e6ecc12794f1d3215f93376a32b350a0492ceb0,Modeling and Predicting Face Recognition System Performance Based on Analysis of Similarity Scores,"Modeling and Predicting Face
-Recognition System Performance
-Based on Analysis of Similarity Scores
-Peng Wang, Member, IEEE,
-Qiang Ji, Sr. Member, IEEE, and
-James L. Wayman, Sr. Member, IEEE"
 9e4b052844d154c3431120ec27e78813b637b4fc,Local gradient pattern-A novel feature representation for facial expression recognition,"Journal of AI and Data Mining
 Vol. 2, No .1, 2014, 33-38.
 Local gradient pattern - A novel feature representation for facial
@@ -65014,36 +54959,6 @@ https://doi.org/10.1109/JSSC.2017.2648820"
 7608953ef5c7a882bd2e7e7053a600e543748233,Robust 3D Face Recognition by Local Shape Difference Boosting,"Robust 3D Face Recognition
 y Local Shape Difference Boosting
 Yueming Wang, Jianzhuang Liu, Senior Member, IEEE, and Xiaoou Tang, Fellow, IEEE"
-766728bac030b169fcbc2fbafe24c6e22a58ef3c,A survey of deep facial landmark detection,"A survey of deep facial landmark detection
-Yongzhe Yan1,2
-Xavier Naturel2
-Christophe Garcia3
-Thierry Chateau1
-Christophe Blanc1
-Stefan Duffner3
-Université Clermont Auvergne, France
-Wisimage, France
-Université de Lyon, CNRS, INSA Lyon, LIRIS, UMR5205, Lyon, France
-Résumé
-La détection de landmarks joue un rôle crucial dans de
-nombreuses applications d’analyse du visage comme la
-reconnaissance de l’identité, des expressions, l’animation
-d’avatar, la reconstruction 3D du visage, ainsi que pour
-les applications de réalité augmentée comme la pose de
-masque ou de maquillage virtuel. L’avènement de l’ap-
-prentissage profond a permis des progrès très importants
-dans ce domaine, y compris sur les corpus non contraints
-(in-the-wild). Nous présentons ici un état de l’art cen-"
-765f01e10ef2df381ad8173d90763d218f4da9e1,A Novel Mechanism of Face Recognition Using Stepwise Linear Discriminant Analysis and Linear Vector Quantization Classifiers,"International Journals of Advanced Research in
-Computer Science and Software Engineering
-ISSN: 2277-128X (Volume-7, Issue-7)
-Research  Article
-A Novel Mechanism of Face Recognition Using Stepwise Linear
-Discriminant Analysis and Linear Vector Quantization Classifiers
-Department of computer Engineering, Yogananda College of Engineering and Technology,
-Abdul Quyoom
-Patoli, Jammu, India
-DOI: 10.23956/ijarcsse/V7I6/0302"
 76bfa74a6311db5d84bad2a7a941f30dd750d01c,Evidence That Emotion Mediates Social Attention in Rhesus Macaques,"Evidence That Emotion Mediates Social Attention in
 Rhesus Macaques
 Emily J. Bethell1*, Amanda Holmes2, Ann MacLarnon1, Stuart Semple1
@@ -65076,11 +54991,6 @@ geboren op 3 september 1978 te Stafsinge, Zweden"
 76cb2ecc96f02b1d8a7a0d1681fbb55367a4b765,Learning Object States from Videos,"Learning Object States from Videos
 Liang-Kang Huang
 Katerina Fragkiadaki"
-765b2cb322646c52e20417c3b44b81f89860ff71,PoseShop: Human Image Database Construction and Personalized Content Synthesis,"PoseShop: Human Image Database
-Construction and Personalized
-Content Synthesis
-Tao Chen, Ping Tan, Member, IEEE, Li-Qian Ma, Ming-Ming Cheng, Member, IEEE,
-Ariel Shamir, and Shi-Min Hu, Member, IEEE"
 768cb0e32de3f1b5aebe04448aaec4c25586680c,Boosting Image Captioning with Attributes,"Under review as a conference paper at ICLR 2017
 BOOSTING IMAGE CAPTIONING WITH ATTRIBUTES
 Ting Yao, Yingwei Pan, Yehao Li, Zhaofan Qiu, Tao Mei
@@ -65191,10 +55101,6 @@ ESTIMATION
 AISHWARYA.S1 , RATHNAPRIYA.K1, SUKANYA SARGUNAR.V2
 U. G STUDENTS, DEPT OF CSE, ALPHA COLLEGE OF ENGINEERING, CHENNAI,
 ASST PROF.DEPARTMENT OF CSE, ALPHA COLLEGE OF ENGINEERING, CHENNAI"
-76673de6d81bedd6b6be68953858c5f1aa467e61,Discovering a Lexicon of Parts and Attributes,"Discovering a Lexicon of Parts and Attributes
-Subhransu Maji
-Toyota Technological Institute at Chicago,
-Chicago, IL 60637, USA"
 76f3450e50c20fca00dd6319df38503c5d7ebad0,Sujet de la thèse : Alignement élastique d ’ images pour la reconnaissance d ’ objet — Non-rigid image alignment for object recognition,"THÈSEDEDOCTORATprésentéeparOLIVIERDUCHENNEpourobtenirlegradedeDOCTEURDEL’ÉCOLENORMALESUPÉRIEUREDomaine:MATHÉMATIQUESAPPLIQUÉESSujetdelathèse:Alignementélastiqued’imagespourlareconnaissanced’objet—Non-rigidimagealignmentforobjectrecognitionThèseprésentéeetsoutenueàl’ENSUlmle29Novembre2012devantlejurycomposéde:JeanPonceProfesseur,DirecteurduDI,ENSUlmDirecteurdethèsePedroFelzenszwalbProfesseur,BrownUniversityRapporteurMartialHebertProfesseur,CarnegieMellonUniversityRapporteurFrancisBachDirecteurderecherche,ENSUlmÉxaminateurJitendraMalikProfesseur,UniversityofBerkeleyÉxaminateurCordeliaSchmidProfesseur,INPGrenobleÉxaminateurAndrewZissermanProfesseur,UniversityofOxfordÉxaminateurThèsepréparéeauseindel’équipeWILLOWdudépartementd’informatiquedel’ÉcoleNormaleSupérieure,Ulm.(INRIA/ENS/CNRSUMR8548)."
 7638cb16631fbcdf621aaf392fec5108e6fa9f47,On Nonrigid Shape Similarity and Correspondence,"Alon Shtern and Ron Kimmel
 November 25, 2013
@@ -65338,14 +55244,6 @@ Kevin H. Wilson
 Government of the
 District of Columbia
 Washington, D.C. 20004"
-06c333fc146d0a87f591c82a1f22925ccef378b1,Emotional Cues during Simultaneous Face and Voice Processing: Electrophysiological Insights,"Emotional Cues during Simultaneous Face and Voice
-Processing: Electrophysiological Insights
-Taosheng Liu1,2, Ana Pinheiro2,3, Zhongxin Zhao4*, Paul G. Nestor2,5, Robert W. McCarley2, Margaret A.
-Niznikiewicz2*
-Department of Psychology, Second Military Medical University, Shanghai, China, 2 Clinical Neuroscience Division, Laboratory of Neuroscience, Department of Psychiatry,
-Boston VA Healthcare System, Brockton Division and Harvard Medical School, Brockton, Massachusetts, United States of America, 3 Neuropsychophysiology Laboratory,
-CiPsi, School of Psychology, University of Minho, Braga, Portugal, 4 Department of Neurology, Neuroscience Research Center of Changzheng Hospital, Second Military
-Medical University, Shanghai, China, 5 University of Massachusetts, Boston, Massachusetts, United States of America"
 06cfc431b70ec6a6783284953a668984600e77e2,A Framework for Human Pose Estimation in Videos,"A Framework for Human Pose Estimation in
 Videos
 Dong Zhang and Mubarak Shah"
@@ -65361,15 +55259,6 @@ saliency from pairwise image comparisons
 Michael Burke1"
 069ebb57ccca31ab68983e07044e65ce1a04174f,4D facial expression recognition,"011 IEEE International Conference on Computer Vision Workshops
 978-1-4673-0063-6/11/$26.00 c(cid:13)2011 IEEE"
-064aaad2a9ac5044b333714e61955631faee87fd,Face Recognition using Radial Curves and Back Propagation Neural Network for frontal faces under various challenges,"International Journal of Computer Applications (0975 – 8887)
-International Conference on Advances in Science and Technology 2015 (ICAST 2015)
-Face Recognition using Radial Curves and Back
-Propagation Neural Network for frontal faces under
-various challenges
-Latasha Keshwani
-Electronics and Telecommunication Department
-Datta Meghe College of Engineering, Airoli, Mumbai
-University, (MS), India"
 06da0e4ae21835f0d33cfbf66c8b73b58625c57b,Facial Keypoints Detection,"Facial Keypoints Detection
 Shenghao Shi"
 06cb0939ed5fb2b3398d54a7fcdb865fe53f414a,Bag-of-Words Image Representation: Key Ideas and Further Insight,"Chapter 2
@@ -65379,15 +55268,6 @@ Marc T. Law, Nicolas Thome and Matthieu Cord"
 06262d6beeccf2784e4e36a995d5ee2ff73c8d11,Recognize Actions by Disentangling Components of Dynamics,"Recognize Actions by Disentangling Components of Dynamics
 Yue Zhao1, Yuanjun Xiong1,2, and Dahua Lin1
 CUHK - SenseTime Joint Lab, The Chinese University of Hong Kong 2Amazon Rekognition"
-06560d5721ecc487a4d70905a485e22c9542a522,Deep Facial Attribute Detection in the Wild: From General to Specific,"SUN, YU: DEEP FACIAL ATTRIBUTE DETECTION IN THE WILD
-Deep Facial Attribute Detection in the Wild:
-From General to Speciﬁc
-Yuechuan Sun
-Jun Yu
-Department of Automation
-University of Science and Technology
-of China
-Hefei, China"
 0602e312a532f9af85cfd0190a2f69f07f44b4fe,The influence of self and similarity on immediate affective impressions of people Ruys,"UvA-DARE (Digital Academic Repository)
 The influence of self and similarity on immediate affective impressions of people
 Ruys, K.I.
@@ -65414,13 +55294,6 @@ Mark Sandler Andrew Howard Menglong Zhu Andrey Zhmoginov Liang-Chieh Chen
 Google Inc."
 061acf48912fe058ba7084dbbdbddc407f01263b,Detection and Orientation Estimation for Cyclists by Max Pooled Features,"Detection and Orientation Estimation for Cyclists
 y Max Pooled Features"
-067e2b673e75a25c47cb0a5528dad41c02402251,Interactive Retrieval in Facial Image Database Using Self-Organizing Maps,"Interactive Retrieval in Facial Image Database
-Using Self-Organizing Maps
-Zhirong Yang and Jorma Laaksonen
-Laboratory of Computer and Information Science
-Helsinki University of Technology
-P.O. Box 5400, FI-02015 HUT, Espoo, Finland
-{zhirong.yang,"
 068a7c7849cb6480def2e124ac5a45564e094b2a,Multi-Scale Learning for Low-Resolution Person Re-Identification,"Multi-scale learning for low-resolution person re-identification
 Li, X; Zheng, WS; Wang, X; Xiang, T; Gong, S
 © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be
@@ -65442,13 +55315,6 @@ on Asymmetric Multi-Cores
 Anuj Pathania, Santiago Pagani, Muhammad Shaﬁque, J¨org Henkel
 Chair for Embedded Systems (CES), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
 Corresponding Author:"
-06aab105d55c88bd2baa058dc51fa54580746424,Image Set-Based Collaborative Representation for Face Recognition,"Image Set based Collaborative Representation for
-Face Recognition
-Pengfei Zhu, Student Member, IEEE, Wangmeng Zuo, Member, IEEE, Lei Zhang, Member, IEEE, Simon C.K. Shiu,
-Member, IEEE, David Zhang, Fellow, IEEE"
-06a23ffbd9752ce204197df59812b2ebd1a097ff,Feedforward semantic segmentation with zoom-out features,"Feedforward semantic segmentation with zoom-out features
-Mohammadreza Mostajabi, Payman Yadollahpour and Gregory Shakhnarovich
-Toyota Technological Institute at Chicago"
 066000d44d6691d27202896691f08b27117918b9,Vision-Based Analysis of Small Groups in Pedestrian Crowds,"Vision-based Analysis of Small Groups in
 Pedestrian Crowds
 Weina Ge, Robert T. Collins, Senior Member, IEEE, and R. Barry Ruback
@@ -65479,9 +55345,6 @@ Grégoire Mesnil · Antoine Bordes · Jason Weston ·
 Gal Chechik · Yoshua Bengio
 Received: 24 May 2012 / Accepted: 26 February 2013
 © The Author(s) 2013"
-06dfc1c6f62bffd5f8b8619d8c51db1ec4d25f3f,Fusing Local Patterns of Gabor Magnitude and Phase for Face Recognition,"Fusing Local Patterns of Gabor Magnitude
-nd Phase for Face Recognition
-Shufu Xie, Shiguang Shan, Member, IEEE, Xilin Chen, Senior Member, IEEE, and Jie Chen, Member, IEEE"
 060820f110a72cbf02c14a6d1085bd6e1d994f6a,Fine-grained classification of pedestrians in video: Benchmark and state of the art,"Fine-Grained Classiﬁcation of Pedestrians in Video: Benchmark and State of the Art
 David Hall and Pietro Perona
 California Institute of Technology.
@@ -65547,13 +55410,6 @@ Faculty of Computing and
 Information Technology King
 Abdulaziz University
 Lamiaa F. Ibrahim"
-06e9149b7ef8bff3a4b5a18fe01da9a522f91891,SRLSP: A Face Image Super-Resolution Algorithm Using Smooth Regression With Local Structure Prior,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TMM.2016.2601020, IEEE
-Transactions on Multimedia
-SRLSP: A Face Image Super-Resolution Algorithm
-Using Smooth Regression with Local Structure Prior
-Junjun Jiang, Member, IEEE, Chen Chen, Jiayi Ma, Member, IEEE, Zheng Wang, Zhongyuan
-Wang, Member, IEEE, and Ruimin Hu, Senior Member, IEEE
-traditional"
 06e15d0d6f92a11bb5b46b5a3e0250cccc452c92,Diagnostic Features of Emotional Expressions Are Processed Preferentially,"Diagnostic Features of Emotional Expressions Are
 Processed Preferentially
 Elisa Scheller1, Christian Bu¨ chel2, Matthias Gamer2*
@@ -65646,13 +55502,6 @@ Computer Vision Center, Universitat Autonoma de Barcelona. Ediﬁci O, Campus UA
 Barcelona, Spain. E-mail:"
 06f251cceff93dac123e8568773295f2d0d702da,Player Tracking and Analysis of Basketball Plays,"Player Tracking and Analysis of Basketball Plays
 Evan Cheshire, Cibele Halasz, and Jose Krause Perin"
-06d4379308d2716a866fc2ca583e4f2a33fa9f4c,WBMMSC: Supervised Classification Procedure of Textures Image Extraction,"International Journal of Computer Trends and Technology (IJCTT) – Volume 47 Number 2 - May 2017
-WBMMSC: Supervised Classification
-Procedure of Textures Image Extraction
-Dr. Pratik Gite1, Udit Gupta2, Aditya Acharya3
-Assistant Professor (IES IPS, Indore)1
-Student (IES IPS, Indore), 5/1 Holani Sadan, Mahesh Nagar, Indore, (MP), India2
-Student (IES IPS, Indore), 191 MIG, Meghdoot Nagar, Mandsaur, (MP), India3"
 06928aef986877d04e9ce642a3ac71b6f061c638,Monocular Simultaneous Localisation and Mapping for Road Vehicles,"Monocular Simultaneous Localisation
 nd Mapping for Road Vehicles
 Master’s thesis in Systems, Control and Mechatronics
@@ -65823,10 +55672,6 @@ Erjin Zhou
 Megvii Inc.
 Zhimin Cao
 Megvii Inc."
-4b0111182ace7443f060a64754ca23b2fc7e1d77,Face Recognition by Super-Resolved 3D Models From Consumer Depth Cameras,"Face Recognition by Super-Resolved 3D Models
-From Consumer Depth Cameras
-Stefano Berretti, Pietro Pala, Senior Member, IEEE, and Alberto del Bimbo, Member, IEEE
-the impact of"
 4b9b39bbdac95e24773789f1bb543149116cdc37,Region-Of-Interest Retrieval in Brain MR Images,"Technical Note PR-TN 2008/00905
 Issued: 12/2008
 Region-Of-Interest Retrieval in Brain MR
@@ -65844,11 +55689,6 @@ Plzeˇn, Czech Republic
 NTIS - New Technologies for the Information Society
 University of West Bohemia
 Plzeˇn, Czech Republic"
-4b8762d7637868b6ba0c97c95b2d4949d103ecdc,The OU-ISIR Gait Database Comprising the Large Population Dataset and Performance Evaluation of Gait Recognition,"The OU-ISIR Gait Database Comprising the Large
-Population Dataset and Performance Evaluation of
-Gait Recognition
-Haruyuki Iwama, Mayu Okumura, Yasushi Makihara, and Yasushi Yagi, Member, IEEE
-the world’s"
 4be03fd3a76b07125cd39777a6875ee59d9889bd,Content-based analysis for accessing audiovisual archives: Alternatives for concept-based indexing and search,"CONTENT-BASED ANALYSIS FOR ACCESSING AUDIOVISUAL ARCHIVES:
 ALTERNATIVES FOR CONCEPT-BASED INDEXING AND SEARCH
 Tinne Tuytelaars
@@ -65895,23 +55735,6 @@ Cristianne R. S. Dutra, Matheus Castro Rocha, and William Robson Schwartz
 Department of Computer Science, Universidade Federal de Minas Gerais
 Belo Horizonte, Minas Gerais, Brazil, 31270-901
 rocha"
-4b48e912a17c79ac95d6a60afed8238c9ab9e553,Minimum Margin Loss for Deep Face Recognition,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015
-Minimum Margin Loss for Deep Face Recognition
-Xin Wei, Student Member, IEEE, Hui Wang, Member, IEEE, Bryan Scotney, and Huan Wan"
-4bfe7037b2d92215aeb5e116988ade7e6733a6b9,Frontal contributions to face processing differences in autism: evidence from fMRI of inverted face processing.,"Journal of the International Neuropsychological Society (2008), 14, 922–932.
-Copyright © 2008 INS. Published by Cambridge University Press. Printed in the USA.
-doi:10.10170S135561770808140X
-SYMPOSIUM
-Frontal contributions to face processing differences
-in autism: Evidence from fMRI of inverted
-face processing
-SUSAN Y. BOOKHEIMER,1,2 A. TING WANG,3 ASHLEY SCOTT,1 MARIAN SIGMAN,1,2
-nd MIRELLA DAPRETTO 1
-Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles,
-Los Angeles, California
-Department of Psychology, University of California Los Angeles, Los Angeles, California
-Department of Psychiatry, Mount Sinai School of Medicine, New York, New York
-(Received January 8, 2008; Final Revision August 9, 2008; Accepted August 11, 2008)"
 4b04247c7f22410681b6aab053d9655cf7f3f888,Robust Face Recognition by Constrained Part-based Alignment,"Robust Face Recognition by Constrained Part-based
 Alignment
 Yuting Zhang, Kui Jia, Yueming Wang, Gang Pan, Tsung-Han Chan, Yi Ma"
@@ -65939,14 +55762,6 @@ Institution1 address"
 Learning in Remote Sensing Imagery
 Gencer Sumbul, Ramazan Gokberk Cinbis, and Selim Aksoy, Senior Member, IEEE
 learning (ZSL)"
-4b1fc77a54e9daece9f11ec881a2ec40919337b7,Fusion of LBP and HOG using multiple kernel learning for infrared face recognition,"Fusion of LBP and HOG Using Multiple Kernel
-Learning for Infrared Face Recognition
-Zhihua Xie, Peng Jiang, Shuai Zhang
-Key Lab of Optic-Electronic and Communication
-Jiangxi Sciences and Technology Normal University
-Nanchang, Jiangxi Province, China
-limitation
-(LBP)  has"
 4b4a174f46ce03caf1ffa4addd074aaa70539f35,BlazeIt: Fast Exploratory Video Queries using Neural Networks.,"Fast Exploratory Video Queries using Neural Networks
 BlazeIt:
 Daniel Kang, Peter Bailis, Matei Zaharia
@@ -66007,13 +55822,6 @@ Martin Antenreiter, Ronald Ortner, and Peter Auer
 University of Leoben, A-8700 Leoben, Austria"
 4b0893bf71e4e13529cefb286c78b166a9491552,Estimating orientation in tracking individuals of flying swarms,"978-1-4799-9988-0/16/$31.00 ©2016 IEEE
 ICASSP 2016"
-4b0081d655e1a4df8988908045780938f1c18630,Human Identification Using Gait,"Turk J Elec Engin, VOL.14, NO.2 2006, c(cid:13) T ¨UB_ITAK
-Human Identi(cid:12)cation Using Gait
-Dept. of Computer Engineering
-Karadeniz Technical University, Trabzon, TURKEY
-Murat EK_INC_I
-Computer Vision Lab.
-e-mail:"
 4b1cdb96a39cf23139a21915ba9e3e0692de8563,Bridging the Gap Between Computational Photography and Visual Recognition,"Bridging the Gap Between Computational
 Photography and Visual Recognition
 Rosaura G. VidalMata*, Sreya Banerjee*, Brandon RichardWebster, Michael Albright, Pedro Davalos,
@@ -66035,15 +55843,6 @@ Xuhong LI 1 Yves GRANDVALET 1 Franck DAVOINE 1"
 Junting Pan and Xavier Gir´o-i-Nieto
 Universitat Politecnica de Catalunya (UPC)
 Barcelona, Catalonia/Spain"
-4b5158bdc12b3704fdd5d199f83ace8505be2945,Histograms of Gabor Ordinal Measures for face representation and recognition,"Histograms of Gabor Ordinal Measures for
-Face Representation and Recognition
-National Laboratory of Pattern Recognition, Institute of Automation,
-Chinese Academy of Science, P.O. Box 2728, Beijing, 100080, P.R. China
-Zhenhua Chai, Ran He, Zhenan Sun, Tieniu Tan
-Center for Biometrics and Security Research
-Heydi M´endez-V´azquez
-Advanced Technologies Application Center, CENATAV.
-7a # 21812 b/ 218 and 222, Playa, P.C. 12200, Havana, Cuba"
 4ba503d8f173880d8e8402808f54b78b653e5d20,Accelerating Stochastic Gradient Descent via Online Learning to Sample,"Accelerating Stochastic Gradient Descent via Online
 Learning to Sample
 Guillaume Bouchard
@@ -66150,10 +55949,6 @@ The content must not be changed in any way or sold commercially in any format or
 medium without the formal permission of the author.
 When referring to this work, full bibliographic details including the author, title,
 warding institution and date of the thesis must be given."
-8160b3b5f07deaa104769a2abb7017e9c031f1c1,Exploiting discriminant information in nonnegative matrix factorization with application to frontal face verification,"Exploiting Discriminant Information in Nonnegative
-Matrix Factorization With Application
-to Frontal Face Veriﬁcation
-Stefanos Zafeiriou, Anastasios Tefas, Member, IEEE, Ioan Buciu, and Ioannis Pitas, Senior Member, IEEE"
 810eafc9e854ea9b1d7a9e9f755f8102310d5db6,Dynamic Multimodal Instance Segmentation Guided by Natural Language Queries,"Dynamic Multimodal Instance Segmentation
 Guided by Natural Language Queries
 Edgar Margffoy-Tuay, Juan C. P´erez, Emilio Botero, and Pablo Arbel´aez
@@ -66170,26 +55965,8 @@ Neural Networks
 Bachelor's thesis (6 ECST)
 Supervisor: Tambet Matiisen
 Tartu 2016"
-81ede08b36f3abd423424804da8ff240606b3a5d,Top-Down Deep Appearance Attention for Action Recognition,"Top-Down Deep Appearance Attention for
-Action Recognition
-Rao Muhammad Anwer1, Fahad Shahbaz Khan2, Joost van de Weijer3, Jorma
-Laaksonen1
-Department of Computer Science, Aalto University School of Science, Finland
-Computer Vision Laboratory, Link¨oping University, Sweden
-Computer Vision Center, CS Dept. Universitat Autonoma de Barcelona, Spain"
-81eecb00eeadb5fe36cd840b687439bfdca7ff30,Kernelized Saliency-Based Person Re-Identification Through Multiple Metric Learning,"JOURNAL OF LATEX CLASS FILES, VOL. 11, NO. 4, DECEMBER 2012
-Kernelized Saliency-based Person Re-Identiﬁcation
-through Multiple Metric Learning
-Niki Martinel* Student Member, IEEE, Christian Micheloni, Member, IEEE, and Gian Luca Foresti, Senior
-Member, IEEE"
 81a142c751bf0b23315fb6717bc467aa4fdfbc92,Pairwise Trajectory Representation for Action Recognition,"978-1-5090-4117-6/17/$31.00 ©2017 IEEE
 ICASSP 2017"
-813e9f76fb9e3f007f0bc819eab66b0b5fbd8204,Towards Building Large Scale Multimodal Domain-Aware Conversation Systems,"Towards Building Large Scale Multimodal Domain-Aware Conversation Systems
-Amrita Saha1,2
-Mitesh M. Khapra2
-Karthik Sankaranarayanan1
-IBM Research AI
-I.I.T. Madras, India"
 81b337f2006cd6c8d5fd148a56cab3e5a662d40d,Improving Data Association by Joint Modeling of Pedestrian Trajectories and Groupings,"Improving Data Association by Joint Modeling
 of Pedestrian Trajectories and Groupings
 Stefano Pellegrini 1, Andreas Ess 1, and Luc Van Gool 1,2
@@ -66226,12 +56003,6 @@ College of Computers and Information Systems, Umm Al-Qura University, Makkah, KS
 Visual Affordance and Function Understanding:
 A Survey
 Mohammed Hassanin, Salman Khan, Murat Tahtali"
-819a321975c736e006870e76446d581e195cad2e,Deep Canonical Time Warping for Simultaneous Alignment and Representation Learning of Sequences,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015
-Deep Canonical Time Warping
-for simultaneous alignment and representation
-learning of sequences
-George Trigeorgis, Mihalis A. Nicolaou, Member, IEEE, Bj¨orn W. Schuller, Senior member, IEEE
-Stefanos Zafeiriou, Member, IEEE"
 81cb69e401b3b51e49ec378dba4bc0c8e33448e1,Applying Domain Randomization to Synthetic Data for Object Category Detection,"Applying Domain Randomization to Synthetic
 Data for Object Category Detection
 Jo˜ao Borrego(cid:63), Atabak Dehban(cid:63), Rui Figueiredo, Plinio Moreno, Alexandre
@@ -66286,9 +56057,6 @@ MultiQ: single sensor-based multi-quality
 multi-modal large-scale biometric score
 database and its performance evaluation
 Md. Zasim Uddin*, Daigo Muramatsu, Takuhiro Kimura, Yasushi Makihara and Yasushi Yagi"
-8147ee02ec5ff3a585dddcd000974896cb2edc53,Angular Embedding: A Robust Quadratic Criterion,"Angular Embedding:
-A Robust Quadratic Criterion
-Stella X. Yu, Member,"
 812d3f6975f4cb87e9905ef18696c5c779227634,A novel comparative deep learning framework for facial age estimation,"Abousaleh et al. EURASIP Journal on Image and Video
 Processing  (2016) 2016:47
 DOI 10.1186/s13640-016-0151-4
@@ -66324,16 +56092,6 @@ Dushyant Mehta*, Helge Rhodin*, Dan Casass, Oleksandr Sotnychenko*, Weipeng Xu*,
 Theobalt*
 *Max Planck Institute For Informatics, Saarland Informatics Campus, Germany
 sUniversidad Rey Juan Carlos, Spain"
-8120a64a73b89294990b3c1e4567b503869b8979,Stories in the Eye: Contextual Visual Interactions for Efficient Video to Language Translation,"Under review as a conference paper at ICLR 2016
-STORIES IN THE EYE: CONTEXTUAL VISUAL IN-
-TERACTIONS FOR EFFICIENT VIDEO TO LANGUAGE
-TRANSLATION
-Anirudh Goyal
-Center for Visual Information Technology
-International Institute of Information and Technolgy, Hyderabad
-Marius Leordeanu
-Institute of Mathematics of the Romanian Academy
-1 Calea Grivitei, Bucharest, Romania"
 815069f591122aa7b388615f944c17c7fa1eff14,Constrained Overcomplete Analysis Operator Learning for Cosparse Signal Modelling,"Constrained Overcomplete Analysis Operator
 Learning for Cosparse Signal Modelling
 Mehrdad Yaghoobi, Sangnam Nam, R´emi Gribonval and Mike E. Davies"
@@ -66443,27 +56201,8 @@ vorgelegt von
 Mohamed Farouk Abdel Hady
 us Kairo, ¨Agypten
 Ulm, Deutschland"
-818dcb3bac6342c02eebd896cd0a46bcf2192b64,Unified Structured Learning for Simultaneous Human Pose Estimation and Garment Attribute Classification,"Uniﬁed Structured Learning for Simultaneous
-Human Pose Estimation and Garment Attribute
-Classiﬁcation
-Jie Shen, Guangcan Liu, Member, IEEE, Jia Chen, Yuqiang Fang, Jianbin Xie, Member, IEEE, Yong Yu,
-nd Shuicheng Yan, Senior Member, IEEE"
 81006fe4c4947d225b9fa17e6b98b8acb36a7692,A Dataset for Grasping and Manipulation using ROS,"A Dataset for Grasping and Manipulation using ROS
 Matei Ciocarlie†, Gary Bradski†, Kaijen Hsiao† and Peter Brook†∗"
-81706277ed180a92d2eeb94ac0560f7dc591ee13,Emotion based Contextual Semantic Relevance Feedback in Multimedia Information Retrieval,"International Journal of Computer Applications (0975 – 8887)
-Volume 55– No.15, October 2012
-Emotion based Contextual Semantic Relevance
-Feedback in Multimedia Information Retrieval
-Karm Veer Singh
-Department of Computer Engineering, Indian
-Institute of Technology, Banaras Hindu
-University,Varanasi, 221005, India
-Anil K. Tripathi
-Department of Computer Engineering, Indian
-Institute of Technology, Banaras Hindu
-University,Varanasi, 221005, India
-find  some
-issued  by  a  user"
 8134b052a9aedd573dd16649a611f68b48e30cb2,InverseFaceNet: Deep Monocular Inverse Face Rendering,"InverseFaceNet: Deep Single-Shot Inverse Face Rendering From A Single Image
 Hyeongwoo Kim1
 Justus Thies2
@@ -66487,13 +56226,6 @@ Introduction
 Empirical Comparison of MLDA variants on Face Recognition
 Appendix: Multilinear decompositions
 References"
-81d91eb9fa3fec5d198b4522d5c373e55c0ddffb,Face Recognition using DCT based Energy Discriminant Mask,"International Journal of Computer Applications (0975 – 8887)
-Volume 170 – No.5, July 2017
-Face Recognition using DCT based Energy
-Discriminant Mask
-Vikas Maheshkar
-Division of Information technology
-New Delhi, India"
 c03c16668426d8b069e75cb440686e12a9adbcd7,Deep Unsupervised Similarity Learning Using Partially Ordered Sets,"Deep Unsupervised Similarity Learning using Partially Ordered Sets
 Miguel A. Bautista∗ , Artsiom Sanakoyeu∗ , Bj¨orn Ommer
 Heidelberg Collaboratory for Image Processing
@@ -66512,12 +56244,6 @@ Azad Mashari University of Toronto, Toronto,
 nd Jie Zhou The Johns Hopkins University, Baltimore
 Workshop 
 October , 
-c03f48e211ac81c3867c0e787bea3192fcfe323e,Mahalanobis Metric Scoring Learned from Weighted Pairwise Constraints in I-Vector Speaker Recognition System,"INTERSPEECH 2016
-September 8–12, 2016, San Francisco, USA
-Mahalanobis Metric Scoring Learned from Weighted Pairwise Constraints in
-I-vector Speaker Recognition System
-Zhenchun Lei1, Yanhong Wan1, Jian Luo1, Yingen Yang1
-School of Computer Information Engineering, Jiangxi Normal University, Nanchang, China"
 c0014e048a5d15ddfeffa075a1b819bcb93dd351,Simple and Efficient Visual Gaze Estimation,"Simple and Efﬁcient Visual Gaze Estimation
 Roberto Valenti
 Nicu Sebe
@@ -66543,10 +56269,6 @@ extract highly discriminative, informative, and
 privacy-protective binary representation
 Meng-Hui Lim and Andrew Beng Jin Teoh*"
 c0e9d06383442d89426808d723ca04586db91747,Cascaded SR-GAN for Scale-Adaptive Low Resolution Person Re-identification,Proceedings of the Twenty-Seventh International Joint Conference on Artiﬁcial Intelligence (IJCAI-18)
-c0e5a471179d2d8c7025febe77a90c3a99c7c9fa,Learning With ℓ1-Graph for Image Analysis,"IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 19, NO. 4, APRIL 2010
-Learning With `1-Graph for Image Analysis
-Bin Cheng, Jianchao Yang, Student Member, IEEE, Shuicheng Yan, Senior Member, IEEE, Yun Fu, Member, IEEE,
-nd Thomas S. Huang, Life Fellow, IEEE"
 c05a7c72e679745deab9c9d7d481f7b5b9b36bdd,"Naval Postgraduate School Monterey, California Approved for Public Release; Distribution Is Unlimited Biometric Challenges for Future Deployments: a Study of the Impact of Geography, Climate, Culture, and Social Conditions on the Effective Collection of Biometrics","NPS-CS-11-005
 NAVAL
 POSTGRADUATE
@@ -66671,26 +56393,6 @@ Viale del Risorgimento 2, Bologna
 c0f17f99c44807762f2a386ac6579c364330e082,A Review on Deep Learning Techniques Applied to Semantic Segmentation,"A Review on Deep Learning Techniques
 Applied to Semantic Segmentation
 A. Garcia-Garcia, S. Orts-Escolano, S.O. Oprea, V. Villena-Martinez, and J. Garcia-Rodriguez"
-c0de99c5f15898e2d28f9946436fec2b831d4eae,ClothCap: seamless 4D clothing capture and retargeting,"ClothCap: Seamless 4D Clothing Capture and Retargeting
-GERARD PONS-MOLL∗, Max Planck Institute for Intelligent Systems, Tübingen, Germany
-SERGI PUJADES∗, Max Planck Institute for Intelligent Systems, Tübingen, Germany
-SONNY HU, Body Labs, New York, NY, USA
-MICHAEL J. BLACK, Max Planck Institute for Intelligent Systems, Tübingen, Germany
-Fig. 1. ClothCap. From left to right: (1) An example 3D textured scan that is part of a 4D sequence. (2) Our multi-part aligned mesh model, layered over the
-ody. (3) The estimated minimally clothed shape (MCS) under the clothing. (4) The body made fatter and dressed in the same clothing. Note that the clothing
-dapts in a natural way to the new body shape. (5) This new body shape posed in a new, never seen, pose. This illustrates how ClothCap supports a range of
-pplications related to clothing capture, modeling, retargeting, reposing, and try-on.
-Dressing virtual avatars and animating them with high quality, visu-
-lly plausible, results is a challenging task. Highly realistic physical
-simulation of clothing on human bodies in motion is complex: cloth-
-ing models are laborious to construct, patterns must be graded so
-that they can be sized to different characters, and the physical param-
-eters of the cloth must be known. Instead, we propose a data-driven
-lothing capture (ClothCap) approach; we capture dynamic clothing
-on humans from 4D scans and transform it to more easily dress
-virtual avatars.
-INTRODUCTION
-Designing and simulating realistic clothing is challenging. Previous methods"
 c038beaa228aeec174e5bd52460f0de75e9cccbe,Temporal Segment Networks for Action Recognition in Videos,"Temporal Segment Networks for Action
 Recognition in Videos
 Limin Wang, Yuanjun Xiong, Zhe Wang, Yu Qiao, Dahua Lin, Xiaoou Tang, and Luc Van Gool"
@@ -66702,12 +56404,6 @@ Peng Wang†
 Sergio Guadarrama∗
 Kevin P. Murphy∗
 Hyun Oh Song∗"
-c082afd5928165ccaf6d419aff5d0456d8ef78f3,Face recognition by fusing binary edge feature and second-order mutual information,"Face Recognition by Fusing Binary Edge Feature and
-Second-order Mutual Information
-Jiatao Song, Beijing Chen, Wei Wang, Xiaobo Ren
-School of Electronic and Information Engineering,
-Ningbo University of Technology
-Ningbo, China"
 c038186138b76a625500ff84c9dadb18aae29f1c,Learning Implicit Transfer for Person Re-identification,"Learning Implicit Transfer
 for Person Re-identi(cid:12)cation
 Tamar Avraham, Ilya Gurvich, Michael Lindenbaum, and Shaul Markovitch
@@ -66746,16 +56442,6 @@ Dataset
 Jingchun Cheng2(cid:63) Han-Kai Hsu1∗ Fang Chen3 Hailin Jin3 Shengjin Wang2‡
 Ming-Hsuan Yang1
 University of California, Merced 2Tsinghua University 3Adobe Research"
-ac968bf321f1dfa2d216dccc22fa5315de63d7bd,Face Template Protection using Deep Convolutional Neural Network,"Face Template Protection using Deep Convolutional Neural Network
-Arun Kumar Jindal, Srinivas Chalamala, Santosh Kumar Jami
-TCS Research, Tata Consultancy Services, India
-{jindal.arun, chalamala.srao,"
-ac4c19e52a58aea27593b99f0ebe5316339b9646,A Probabilistic Approach for Image Retrieval Using Descriptive Textual Queries,"A Probabilistic Approach for Image Retrieval Using
-Descriptive Textual Queries
-Yashaswi Verma
-CVIT, IIIT Hyderabad, India
-C. V. Jawahar
-CVIT, IIIT Hyderabad, India"
 ac7f898ff5789914d423526c392ee61b979fdd8e,"Target Tracking with Kalman Filtering , KNN and LSTMs Dan Iter","Target Tracking with Kalman Filtering, KNN and LSTMs
 Dan Iter
 Jonathan Kuck
@@ -66791,8 +56477,6 @@ Certiﬁed by:
 Accepted by:
 William T. Freeman
 Professor of Electrical Engineering and Computer Science"
-ac88405d34b7b6fa701e25d9fbdb56126cc9a8c3,On the Diversity of Realistic Image Synthesis,"On the Diversity of Realistic Image Synthesis
-Zichen Yang, Haifeng Liu, Member, IEEE and Deng Cai, Member, IEEE"
 ac83b9ad20ecf63c7818ff1e43a99b4c626fac12,Accuracy and Security Evaluation of Multi-Factor Biometric Authentication,"Accuracy and Security Evaluation of Multi-Factor Biometric Authentication
 Hisham Al-Assam, Harin Sellahewa, Sabah Jassim
 Department of Applied Computing
@@ -66923,26 +56607,6 @@ Graduate School of Engineering, Tokyo University of Agriculture and Technology,
 Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, Kitakyushu, Japan
 *Corresponding author:
 Received January 09, 2015; Revised January 19, 2015; Accepted January 22, 2015"
-accbd6cd5dd649137a7c57ad6ef99232759f7544,Facial Expression Recognition with Local Binary Patterns and Linear Programming,"FACIAL EXPRESSION RECOGNITION WITH LOCAL BINARY PATTERNS
-AND LINEAR PROGRAMMING
-Xiaoyi Feng1, 2, Matti Pietikäinen1, Abdenour Hadid1
-Machine Vision Group, Infotech Oulu and Dept. of Electrical and Information Engineering
-P. O. Box 4500 Fin-90014 University of Oulu, Finland
-2 College of Electronics and Information, Northwestern Polytechnic University
-710072 Xi’an, China
-In  this  work,  we  propose  a  novel  approach  to  recognize  facial  expressions  from  static
-images. First, the Local Binary Patterns (LBP) are used to efficiently represent the facial
-images and then the Linear Programming (LP) technique is adopted to classify the seven
-facial  expressions  anger,  disgust,  fear,  happiness,  sadness,  surprise  and  neutral.
-Experimental results demonstrate an average recognition accuracy of 93.8% on the JAFFE
-database, which outperforms the rates of all other reported methods on the same database.
-Introduction
-Facial  expression  recognition  from  static
-images  is  a  more  challenging  problem
-than  from  image  sequences  because  less
-information  for  expression  actions
-vailable.  However,  information  in  a
-single  image  is  sometimes  enough  for"
 ac2e3a889fc46ca72f9a2cdedbdd6f3d4e9e2627,Age detection from a single image using multitask neural networks : An overview and design proposal,"Research School of Engineering
 ANU College of Engineering and Computer Science
 ASSIGNMENT COVER SHEET
@@ -66966,11 +56630,6 @@ ac6a9f80d850b544a2cbfdde7002ad5e25c05ac6,Privacy-Protected Facial Biometric Veri
 Using Fuzzy Forest Learning
 Richard Jiang, Ahmed Bouridane, Senior Member, IEEE, Danny Crookes, Senior Member, IEEE,
 M. Emre Celebi, Senior Member, IEEE, and Hua-Liang Wei"
-acc5318592303852feba755a1202fb3c683b3b53,Correction of AI systems by linear discriminants: Probabilistic foundations,"Correction of AI systems by linear discriminants: Probabilistic foundations
-A.N. Gorbana,b,∗, A. Golubkovc, B. Grechuka, E.M. Mirkesa,b, I.Y. Tyukina,b
-Department of Mathematics, University of Leicester, Leicester, LE1 7RH, UK
-Lobachevsky University, Nizhni Novgorod, Russia
-Saint-Petersburg State Electrotechnical University, Saint-Petersburg, Russia"
 ac12ba5bf81de83991210b4cd95b4ad048317681,Combining Deep Facial and Ambient Features for First Impression Estimation,"Combining Deep Facial and Ambient Features
 for First Impression Estimation
 Furkan G¨urpınar1, Heysem Kaya2, Albert Ali Salah3
@@ -67016,15 +56675,6 @@ Based Semantic Segmentation
 Max-Heinrich Laves · Jens Bicker · Lüder
 A. Kahrs · Tobias Ortmaier
 Received: date / Accepted: date"
-6a1da83440c7685f5a03e7bda17be9025e0892e3,Semantic Match Consistency for Long-Term Visual Localization,"Semantic Match Consistency for Long-Term
-Visual Localization
-Carl Toft1, Erik Stenborg1, Lars Hammarstrand1, Lucas Brynte1, Marc
-Pollefeys2,3, Torsten Sattler2, Fredrik Kahl1
-Department of Electrical Engineering, Chalmers University of Technology, Sweden
-Department of Computer Science, ETH Z¨urich, Switzerland
-Microsoft, Switzerland"
-6ac1dc59e823d924e797afaf5c4a960ed7106f2a,Deep Facial Expression Recognition: A Survey,"Deep Facial Expression Recognition: A Survey
-Shan Li and Weihong Deng∗, Member, IEEE"
 6aa21d78af359853ee07288cfc8d047e914ce458,Facial Expression Recognition using Log-Euclidean Statistical Shape Models,"FACIAL EXPRESSION RECOGNITION USING
 LOG-EUCLIDEAN STATISTICAL SHAPE MODELS
 Bartlomiej W. Papiez, Bogdan J. Matuszewski, Lik-Kwan Shark and Wei Quan
@@ -67039,16 +56689,6 @@ Facebook Research
 Facebook Research
 Hacker Way
 Hacker Way"
-6a7e464464f70afea78552c8386f4d2763ea1d9c,Facial Landmark Localization – A Literature Survey,"Review Article
-International Journal of Current Engineering and Technology
-E-ISSN 2277 – 4106, P-ISSN 2347 - 5161
-©2014 INPRESSCO
-, All Rights Reserved
-Available at http://inpressco.com/category/ijcet
-Facial Landmark Localization – A Literature Survey
-Dhananjay RathodȦ*, Vinay A, Shylaja SSȦ and S NatarajanȦ
-ȦDepartment of Information Science and Engineering, PES Institute of Technology, Bangalore, Karnataka, India
-Accepted 25 May 2014, Available online 01 June2014, Vol.4, No.3 (June 2014)"
 6a7ec333ccabd41b9d20f05c145b3377f6045f43,"C 2010 Zihan Zhou Face Recognition under Varying Illumination, Pose and Contiguous Occlusion",(cid:13) 2010 Zihan Zhou
 6a41ba9db0affa701ea125e09a2fe7eb583e3ac9,Frontal imgelerden otomatik yüz tan ı ma Automatic face recognition from frontal images,"Frontal imgelerden otomatik yüz tanıma
 Automatic face recognition from frontal images
@@ -67140,15 +56780,6 @@ Beijing Etrol Technologies Co., Ltd.
 Centre for OPTical Imagery Analysis and Learning, Northwestern Polytechnical University.
 School of Automation, Northwestern Polytechnical University.
 5School of Electrical and Data Engineering, University of Technology Sydney."
-6a1fd51107770edbdd832a1934ff5461e891f2e1,A Robust and Dominant Local Binary Pattern and Its Application,"IJSRD - International Journal for Scientific Research & Development| Vol. 2, Issue 10, 2014 | ISSN (online): 2321-0613
-A Robust and Dominant Local Binary Pattern and Its Application
-Keerthana A.V1 Ashwin M2
-Student of M.E 2Associate Professor
-,2Department of Computer Science & Engineering
-,2Adhiyamaan College of Engineering, Krishnagiri, Tamilnadu, India
-Local
-ternary
-Pattern,  modified"
 6af98f9843ba629ae1b0347e8b8d81a263f8d7f2,Does this recession make me look black? The effect of resource scarcity on the categorization of biracial faces.,"Short Report
 Does This Recession Make Me Look Black?
 The Effect of Resource Scarcity on the
@@ -67173,14 +56804,6 @@ ompetition between groups (e.g., Kurzban & Neuberg, 2005;"
 Relative Pairwise Relationship Constrained
 Non-negative Matrix Factorisation
 Shuai Jiang, Kan Li, and Richard Yida Xu"
-6ade1e0d4744d2eb5bf7bab97289ffd7eeb5a661,SIMULATED+UNSUPERVISED LEARNING WITH ADAPTIVE DATA GENERATION AND BIDIRECTIONAL MAPPINGS,"Published as a conference paper at ICLR 2018
-SIMULATED+UNSUPERVISED LEARNING WITH
-ADAPTIVE DATA GENERATION AND
-BIDIRECTIONAL MAPPINGS
-Kangwook Lee∗, Hoon Kim∗& Changho Suh
-School of Electrical Engineering
-KAIST
-Daejeon, South Korea"
 6a3cbe2bb27b2a7d32c358e0be4ed268f7d4455c,"Modeling Shape, Appearance and Self-Occlusions for Articulated Object Tracking","Modeling Shape, Appearance and Self-Occlusions
 for Articulated Object Tracking
 Yanchao Yang and Ganesh Sundaramoorthi"
@@ -67235,26 +56858,6 @@ purposes or for creating new collective works for resale or
 redistribution to servers or lists, or to reuse any copyrighted
 omponent of this work in other works must be obtained from
 the IEEE.; This work is licensed under a Creative Commons"
-6ad5a38df8dd4cdddd74f31996ce096d41219f72,Multi-cue onboard pedestrian detection,"Objectives
-Implementation details
-Experiments on TUD-Brussels
-Conclusion
-{wojek, walk,
-Multi-Cue Onboard Pedestrian Detection
-Christian Wojek, Stefan Walk, Bernt Schiele
-Computer Science Department, TU Darmstadt, Germany
-Detect pedestrians from a moving platform
-• Exploit motion information
-• Leverage complementarity of features
-• Evaluate different classiﬁers
-• New datasets with image pairs
-Features
-• HOG [1]
-8× 8 pixel cells, 2× 2 blocks
-9-bin histograms, unsigned gradients
-• Haar wavelets [2]
-2 and 16 pixel masks
-horizontal, vertical and diagonal re-"
 6a8a3b27a78c78bc80984fca29554de3269d34d3,Speeding-Up Object Detection Training for Robotics with FALKON,"Speeding-up Object Detection Training for Robotics with FALKON
 Elisa Maiettini1,2,3, Giulia Pasquale1,2, Lorenzo Rosasco2,3 and Lorenzo Natale1"
 6a27ffd788a0db64fef74e673786763c82902a26,Discriminative deep transfer metric learning for cross-scenario person re-identification,"Downloaded From: https://www.spiedigitallibrary.org/journals/Journal-of-Electronic-Imaging on 9/13/2018
@@ -67435,11 +57038,6 @@ Smartphones
 Affiliation
 City, Country
 e-mail address"
-63c71e317168d5b55dccaf5515ad96c9e87f7d9e,"Part-Based RDF for Direction Classification of Pedestrians, and a Benchmark","Part-based RDF for Direction Classiﬁcation
-of Pedestrians, and a Benchmark
-Junli Tao and Reinhard Klette
-The .enpeda.. Project, Tamaki Campus
-The University of Auckland, Auckland, New Zealand"
 637648198f9e91654ce27eaaa40512f2dc870fc1,Survey of Visual Question Answering: Datasets and Techniques,"Survey of Visual Question Answering: Datasets and Techniques
 Akshay Kumar Gupta
 Indian Institute of Technology Delhi"
@@ -67492,15 +57090,6 @@ P. Quelhasy, F. Monayy, J.-M. Odobezy, D. Gatica-Perezy, T. Tuytelaarsz, and L.
 yIDIAP Research Institute, Martigny, Switzerland
 zKatholieke Universiteit, Leuven, Belgium
 fquelhas, monay, odobez, ftinne.tuytelaars,"
-638b98ce5fddd0bd6d9ca22fb4c48220e6f3109c,Facial Feature Extraction in Colour Images Based on Local Binary Pattern,"International Journal of Science and Research (IJSR)
-ISSN (Online): 2319-7064
-Facial Feature Extraction in Colour Images Based
-on Local Binary Pattern
-Lakshmy. R1, Asha A. S2
-PG Scholar, Department of Electronics and Communication Engineering
-TKM Institute of Technology, Kollam, Kerala, India
-Assistant Professor, Department of Electronics and Communication Engineering
-TKM Institute of Technology, Kollam, Kerala, India"
 63c109946ffd401ee1195ed28f2fb87c2159e63d,Robust Facial Feature Localization Using Improved Active Shape Model and Gabor Filter,"MVA2011 IAPR Conference on Machine Vision Applications, June 13-15, 2011, Nara, JAPAN
 Robust Facial Feature Localization using Improved Active Shape
 Model and Gabor Filter
@@ -67541,17 +57130,6 @@ DAVIDE MALTONI
 Relatore
 MASSIMO TISTARELLI
 Esame finale anno 2014"
-63db312ec494988e1af0c1db5f9d9ca40ef89237,Vision Based Gesture Recognition : a Comprehensive Study,"REGULAR ISSUE
-ARTICLE
-VISION BASED GESTURE RECOGNITION: A COMPREHENSIVE
-STUDY
-A Balasundaram1*, C Chellappan 2
-Research Scholar, Department of CSE, G.K.M. College of Engineering and Technology, Chennai, INDIA
-Principal, G.K.M. College of Engineering and Technology, Chennai, INDIA"
-63cdf4aa1492c5c8fb109a1bf03af4844982e265,Reconstructing High-Resolution Face Models From Kinect Depth Sequences,"Reconstructing High-Resolution Face Models
-From Kinect Depth Sequences
-Enrico Bondi, Pietro Pala, Senior Member, IEEE, Stefano Berretti, Member, IEEE,
-nd Alberto Del Bimbo, Senior Member, IEEE"
 6358b95b1c97df4f10f57a90913f672e44d2094b,Opponent colors for human detection,"Opponent Colors for Human Detection
 Rao Muhammad Anwer, David V´azquez, and Antonio M. L´opez
 Computer Vision Center and Computer Science Dpt.,
@@ -67683,9 +57261,6 @@ the requirements for the degree of
 Master of Science
 Graduate Program in Computer Engineering
 Bo˘gazi¸ci University"
-628b7dbf216aba008b9ef74a411b87a99e7a3106,A review of speech-based bimodal recognition,"IEEE TRANSACTIONS ON MULTIMEDIA, VOL. 4, NO. 1, MARCH 2002
-A Review of Speech-Based Bimodal Recognition
-Claude C. Chibelushi, Farzin Deravi, Member, IEEE, and John S. D. Mason"
 62b90583723174220b26c92bd67f6c422ad75570,DNA-GAN: LEARNING DISENTANGLED REPRESEN-,"Under review as a conference paper at ICLR 2018
 DNA-GAN: LEARNING DISENTANGLED REPRESEN-
 TATIONS FROM MULTI-ATTRIBUTE IMAGES
@@ -67780,9 +57355,6 @@ genehmigte
 Dissertation
 Gerard Pons Moll
 geboren am 25. Oktober 1984 in Barcelona."
-6268ad4bc516a41a30db566e2207079fc483212e,LBP-Based Edge-Texture Features for Object Recognition,"LBP-Based Edge-Texture Features for
-Object Recognition
-Amit Satpathy, Member, IEEE, Xudong Jiang, Senior Member, IEEE, and How-Lung Eng, Member, IEEE"
 621ea1f1e364262348135c803557e7b3454a804e,Generative spatiotemporal modeling of neutrophil behavior,"Accepted to 2018 IEEE International Symposium on Biomedical Imaging
 Copyright ©2018 IEEE
 Generative Spatiotemporal Modeling Of Neutrophil Behavior
@@ -67795,26 +57367,6 @@ University of Georgia"
 6236962ce0d627fc23774f0680e77069b9667803,Fitting a Morphable Model to Pose and Shape of a Point Cloud,"Fitting a Morphable Model to Pose and Shape of a Point Cloud
 David C. Schneider, Peter Eisert
 Fraunhofer Heinrich Hertz Institute, Einsteinufer 37, 10587 Berlin, Germany"
-62c425be3e07e076d1339d1f2fe2ed319a859f02,Face Recognition & Gender Determination Using LIPS .,"International Journal of Advance Foundation and Research in Computer (IJAFRC)
-Volume 2, Special Issue (NCRTIT 2015), January 2015. ISSN 2348 - 4853
-Face Recognition & Gender Determination Using LIPS.
-Rutuja G. Shelke*,Prof. S. A. Annadate.
-JNEC, Aurangabad, Maharashtra, India
-A B S T R A C T
-This  paper  presents  a  novel  face  detection  and  gender  determination  strategy  in  color  images
-under non uniform background. This is done by detecting the human skin regions in image given
-nd  detecting  facial  features  based  on  the  measurements  in  pixels.  The  proposed  converts  the
-RGB image into the YCbCr color space to detect the skin regions in the facial image. But in order to
-detect facial features the color image is converted in to gray scale image. This method locates the
-lip  region  and  the  mouth  region.  Here  feature  extraction  is  carried  out  by  using  Principal
-omponent analysis (PCA) and Gabor wavelet. The gender classification method classifies almost
-ll  the  images  with  different  image  sizes.  The  best  classification  rate  is  achieved  by  using  the
-method  given  in  this  work  i.e.  Minimum  distance  classifier method.  The  whole  idea  is  offering  a
-simple, reliable and robust method for extracting features of lips for face recognition and gender
-identification. For recognition experiments we used face images of persons from different sets of
-the  FERET  and  AR  databases.  The  results  using  a  training  database  of  15  male  and  15  female
-images show an average performance of 88.6% correct gender determination on images from test
-Index  Terms  :  Face  recognition,  Gender  determination,  YCbCr,  Principal  Component  Analysis,"
 626c12d6ccb1405c97beca496a3456edbf351643,Conditional Variance Penalties and Domain Shift Robustness,"Conditional Variance Penalties and Domain Shift Robustness
 Christina Heinze-Deml & Nicolai Meinshausen
 Seminar for Statistics
@@ -67839,14 +57391,6 @@ School of Electrical Engineering
 Korea Advanced Institute of Science
 nd Technology (KAIST),
 South Korea"
-62e2c431d375bbafd988d53c4d39f240c8b7977b,A Game-Theoretic Probabilistic Approach for Detecting Conversational Groups,"A Game-Theoretic Probabilistic Approach
-for Detecting Conversational Groups
-Sebastiano Vascon1, Eyasu Zemene Mequanint2, Marco Cristani1,3, Hayley Hung4 (cid:63),
-Marcello Pelillo2, and Vittorio Murino1,3
-Dept. of Pattern Analysis & Computer Vision (PAVIS), Istituto Italiano di Tecnologia, Genova, Italy
-Dept. of Environmental Sciences, Informatics and Statistics, University Ca’ Foscari of Venice, Italy
-Dept. of Computer Science, University of Verona, Italy
-Faculty of Electrical Engineering, Mathematics and Computer Science, Technical University of Delft, Netherlands"
 623da0faea1f98f238936e34f361518829edfdf4,Digital geometry image analysis for medical diagnosis,"Digital Geometry Image Analysis for Medical Diagnosis
 Jiandong Fang    Shiaofen Fang     Jeffrey Huang     Mihran Tuceryan
 Department of Computer and Information Science
@@ -67874,9 +57418,6 @@ presented.
 Correspondingauthor:I.Pitas
 DRAFT
 September
-62da5876fbc5b6abe467891fc71b68173e6ad061,Heterogeneous Face Recognition Using Kernel Prototype Similarities,"Heterogeneous Face Recognition Using
-Kernel Prototype Similarities
-Brendan F. Klare, Member, IEEE, and Anil K. Jain, Fellow, IEEE"
 62c435bc714f13a373926e3b1914786592ed1fef,Classification Signboard Detection Face Detection Animal Detection Texture Detection GPS + IMU Depth Localization Module Central Control Speech,"MAVI: An Embedded Device to Assist Mobility of
 Visually Impaired
 Rajesh Kedia∗, Yoosuf K K∗, Pappireddy Dedeepya∗, Munib Fazal∗, Chetan Arora†, and M. Balakrishnan∗
@@ -67937,18 +57478,6 @@ Magnitude-Orientation Stream Network
 Carlos Caetano, Victor H. C. de Melo, Jefersson A. dos Santos, William Robson Schwartz
 Smart Surveillance Interest Group, Department of Computer Science
 Universidade Federal de Minas Gerais, Belo Horizonte, Brazil"
-62d5c16760018b08e301a940434c3fc2e862c385,Approach For Palm Vein Blood Vessel Detection Based On Fuzzy Logic,"International Journal of Electronics Engineering Research.
-ISSN 0975-6450 Volume 9, Number 4 (2017) pp. 613-619
-© Research India Publications
-http://www.ripublication.com
-Approach For Palm Vein Blood Vessel Detection
-Based On Fuzzy Logic
-Praveen Kaundal
-Department of E.C.E, PEC, University of Technology
-Chandigarh-160012, India
-Dr. Sukhwinder Singh
-Department of E.C.E, PEC, University of Technology
-Chandigarh-160012, India"
 62007c30f148334fb4d8975f80afe76e5aef8c7f,Eye In-Painting with Exemplar Generative Adversarial Networks,"Eye In-Painting with Exemplar Generative Adversarial Networks
 Brian Dolhansky, Cristian Canton Ferrer
 Facebook Inc.
@@ -67974,26 +57503,6 @@ Tabasco, Mexico // // // //
 for Mathematics
 Huerta-Pacheco1
 *Corresponding author"
-629722342f719ee413e9bb07072a2fc2b4f09a26,Gender Classification by Information Fusion of Hair and Face,"Gender Classification by Information Fusion
-of Hair and Face
-Zheng Ji, Xiao-Chen Lian and Bao-Liang Lu
-Department of Computer Science and Engineering, Shanghai
-Jiao Tong University 800 Dong Chuan Road,
-Shanghai 200240, China
-. Introduction
-Various gender classification methods have been reported in the literature. These existing
-methods fall into two categories. The first kind of method is the appearance-based approach.
-Golomb et al. [1] used a two-layer neural network with 30 × 30 inputs and directly fed the
-scaled  image  pixels  to  the  network  without  dimensionality  reduction.  Their  database
-ontains only 90 images with half male and half female facial images. Gutta et al. [2] used the
-mixture of experts combining the ensembles of radial basis functions (RBF) networks and a
-decision tree. Xu et al. [3] applied Adaboost to gender classification problem with the feature
-pools  composed  of  a  set  of  linear  projections  utilizing  statistical  moments  up  to  second
-order. Wu et al. [4] also adopted Adaboost. Instead of using threshold weak classifiers, they
-used  looking-up  table  weak  classifiers,  which  are  more  general  and  better  than  simple
-threshold  ones  due  to  stronger  ability  to  model  complex  distribution  of  training  samples.
-Moghaddam and Yang [5] demonstrated that support vector machines (SVMs) work better
-than other classifiers such as ensemble of radial basis function (RBF) networks, classical RBF"
 62306db738cfddd39e1f12e22bce0f7615ce58b8,Face detection with colour segmentation and fuzzy template matching,"Proceedings of the 17th World Congress
 The International Federation of Automatic Control
 Seoul, Korea, July 6-11, 2008
@@ -68018,38 +57527,12 @@ Guilhem Ch´eron · Anton Osokin · Ivan Laptev · Cordelia Schmid"
 14761b89152aa1fc280a33ea4d77b723df4e3864,Zero-Shot Learning via Visual Abstraction,
 14a5feadd4209d21fa308e7a942967ea7c13b7b6,Content-based vehicle retrieval using 3D model and part information,"978-1-4673-0046-9/12/$26.00 ©2012 IEEE
 ICASSP 2012"
-14f964d152337e963e4a4fd3619f6030aa75deb1,Person Re-identification by Discriminatively Selecting Parts and Features,"Person re-identiﬁcation by discriminatively
-selecting parts and features
-Amran Bhuiyan, Alessandro Perina and Vittorio Murino
-Pattern Analysis and Computer Vision (PAVIS)
-Istituto Italiano di Tecnologia
-Genova, Italy"
 1414d4880e368414cbbbbd215e8b0471f185aa03,Face Detection in Low-Resolution Color Images,"Face Detection in Low-resolution Color Images
 Jun Zheng, Geovany A. Ramirez, and Olac Fuentes,
 Computer Science Department,
 University of Texas at El Paso,
 El Paso, Texas, 79968, U.S.A.
 No Institute Given"
-14f0283c703e450e5f17cbe94878896de865ce30,Robust Visual Tracking for Multiple Targets with Data Association and Track Management,"Volume 3, Issue 2 (2015) 383-385
-ISSN 2347 - 3258
-International Journal of Advance Research and Innovation
-Robust Visual Tracking for Multiple Targets with Data Association and
-Track Management
-N. Mahalakshmi, S. R. Saranya
-Department of Computer Science Engineering, Dhanalakshmi Srinivasan Engineering College, Perambalur, Tamil
-Nadu, India
-Article Info
-Article history:
-Received 5 April 2015
-Received in revised form
-0 April 2015
-Accepted 20 May 2015
-Available online 15 June 2015
-Keywords
-Online Multi-Object Tracking,
-Tracking-By Detection,
-Data Association,
-Track Management,"
 14c988aa9086207b337dcc5611aad08422129b42,Human Relative Position Detection Based on Mutual Occlusion,"Human Relative Position Detection
 Based on Mutual Occlusion
 V´ıctor Borjas, Michal Drozdzal, Petia Radeva, and Jordi Vitri`a
@@ -68086,14 +57569,6 @@ DETECTOR:
 FEWER CLICKS – LESS FRUSTRATION1
 Peter M. Roth2, Helmut Grabner2, Christian Leistner2,
 Martin Winter2, and Horst Bischof2"
-14902cf0b07eae6561184b12aef07e945936ed26,Road side video surveillance in traffic scenes using mapreduce framework for accident analysis,"Biomedical Research 2016; Special Issue: : S257-S266
-ISSN 0970-938X
-www.biomedres.info
-Road side video surveillance in traffic scenes using map-reduce framework
-for accident analysis.
-Maha Vishnu VC*, Rajalakshmi M
-Department of Computer Science and Engineering and Information Technology, Coimbatore Institute of Technology,
-Coimbatore, India"
 14bf85bacf15241c500db72c145b0490a14addaa,Generalization in Holistic versus Analytic Processing of Faces,"Generalization in Holistic versus Analytic Processing of Faces
 M. Bicego∗
 A.A. Salah
@@ -68239,13 +57714,6 @@ SeMarket, S.A. Barcelona, Spain"
 1450296fb936d666f2f11454cc8f0108e2306741,Learning to Discover Cross-Domain Relations with Generative Adversarial Networks,"Learning to Discover Cross-Domain Relations
 with Generative Adversarial Networks
 Taeksoo Kim 1 Moonsu Cha 1 Hyunsoo Kim 1 Jung Kwon Lee 1 Jiwon Kim 1"
-14a022a3eb8cc9681b1ab075650d462788de1fa0,GANs for Biological Image Synthesis,"GANs for Biological Image Synthesis
-INRIA/ENS∗, France
-Anton Osokin
-HSE†, Russia
-Anatole Chessel
-´Ecole Polytechnique‡,
-France"
 142dcfc3c62b1f30a13f1f49c608be3e62033042,Adaptive region pooling for object detection,"Adaptive Region Pooling for Object Detection
 Yi-Hsuan Tsai
 UC Merced
@@ -68348,9 +57816,6 @@ Ruslan Salakhutdinov
 Richard S. Zemel
 Yoshua Bengio"
 14e9eaa6ac23996e9a62060c8da90bdb7116ee37,Localization Recall Precision (LRP): A New Performance Metric for Object Detection,[cs.CV]  5 Jul 2018
-1471c0b72e4a88b39e59362bf169bb35915966a9,Extended Coding and Pooling in the HMAX Model,"Extended coding and pooling in the HMAX model
-Christian Th´eriault, Nicolas Thome, Member, IEEE, and Matthieu Cord, Member, IEEE
-Universit´e Pierre et Marie Curie, UPMC-Sorbonne Universities, LIP6, 4 place Jussieu, 75005, Paris, France"
 14373c9fd08dee8f7195a88430121c69bbebbe1b,Head Pose Estimation Using Covariance of Oriented Gradients,"978-1-4244-4296-6/10/$25.00 ©2010 IEEE
 ICASSP 2010"
 1456f147381bf7c385225d854c2fb48c19eca285,LCAV-31: a dataset for light field object recognition,"Computational Imaging XII, edited by Charles A. Bouman, Ken D. Sauer, Proc. of SPIE-IS&T Electronic Imaging,
@@ -68359,16 +57824,6 @@ Proc. of SPIE-IS&T/ Vol. 9020  902014-1"
 1459d4d16088379c3748322ab0835f50300d9a38,Cross-Domain Visual Matching via Generalized Similarity Measure and Feature Learning,"Cross-Domain Visual Matching via Generalized
 Similarity Measure and Feature Learning
 Liang Lin, Guangrun Wang, Wangmeng Zuo, Xiangchu Feng, and Lei Zhang"
-c5c379a807e02cab2e57de45699ababe8d13fb6d,Facial Expression Recognition Using Sparse Representation,"Facial Expression Recognition Using Sparse Representation
-SHIQING ZHANG 1, XIAOMING ZHAO 2, BICHENG LEI 1
-School of Physics and Electronic Engineering
-Taizhou University
-Taizhou 318000
-CHINA
-2Department of Computer Science
-Taizhou University
-Taizhou 318000
-CHINA"
 c5844de3fdf5e0069d08e235514863c8ef900eb7,A Study on Similarity Computations in Template Matching Technique for Identity Verification,"Lam S K et al. / (IJCSE) International Journal on Computer Science and Engineering
 Vol. 02, No. 08, 2010, 2659-2665
 A Study on Similarity Computations in Template
@@ -68400,25 +57855,6 @@ for the degree of Doctor of Philosophy
 The University of Leeds
 School of Computing
 September 2016"
-c5697c28272dc7e81c451a63495f229c740d597b,Intra-class retrieval of non-rigid 3 D objects : Application to Face Recognition,"Intra-class retrieval of non-rigid 3D objects:
-Application to Face Recognition
-Georgios Passalis†‡, Ioannis A. Kakadiaris†, Member, IEEE, and Theoharis Theoharis†‡"
-c55dcc587a53ff82cf3f79d84e7df67f4c8f77ed,TabletGaze: A Dataset and Baseline Algorithms for Unconstrained Appearance-based Gaze Estimation in Mobile Tablets,"TabletGaze: A Dataset and Baseline Algorithms
-for Unconstrained Appearance-based Gaze
-Estimation in Mobile Tablets
-Qiong Huang, Student Member, IEEE, Ashok Veeraraghavan, Member, IEEE,
-nd Ashutosh Sabharwal, Fellow, IEEE"
-c51e244be1728fd1abbd4b4bc58d2e555643ea50,Towards Autonomous Vehicles with Advanced Sensor Solutions,"World Journal of Engineering and Technology, 2015, 3, 6-17
-Published Online October 2015 in SciRes. http://www.scirp.org/journal/wjet
-http://dx.doi.org/10.4236/wjet.2015.33C002
-Towards Autonomous Vehicles with
-Advanced Sensor Solutions
-Matti Kutila1, Pasi Pyykönen1, Aarno Lybeck2, Pirita Niemi2, Erik Nordin3
-VTT Technical Research Centre Ltd., P.O. Box 1300, FI-33101 Tampere, Finland
-TTS, P.O. Box 5, FI-05200 Rajamäki, FINLAND
-Volvo Group Trucks Technology (GTT), BF40562 M1.6, SE-405 08 Göteborg, Sweden
-Email:
-Received 29 May 2015; accepted 15 October 2015; published 22 October 2015"
 c50e498ede6f5216cffd0645e747ce67fae2096a,Low-Resolution Face Recognition in the Wild via Selective Knowledge Distillation,"Low-resolution Face Recognition in the Wild
 via Selective Knowledge Distillation
 Shiming Ge, Senior Member, IEEE, Shengwei Zhao, Chenyu Li and Jia Li, Senior Member, IEEE"
@@ -68487,19 +57923,6 @@ for advertising or promotional purposes, creating new collective works, for resa
 servers or lists, or reuse of any copyrighted component of this work in other works.
 Downloaded from
 http://hdl.handle.net/10072/54416"
-c53a512b4d7dee0d8d0f3e5bf2c6ace7a00cbbae,"Content-Based Video Indexing and Retrieval using Key frames Texture , Edge and Motion Features","International Journal of Current Engineering and Technology
-©2016 INPRESSCO®, All Rights Reserved
-Research Article
-Content-Based Video Indexing and Retrieval using Key frames Texture,
-Edge and Motion Features
-M.Ravinder†* and T.Venugopal‡
-E-ISSN 2277 – 4106, P-ISSN 2347 – 5161
-Available at http://inpressco.com/category/ijcet
-(R.Hamid et al., 2007; G. Lavee et al., 2009; J. Tang et al.,
-009; X. Chen et al., 2009).
-JNTUK, Kakinada, Andhra Pradesh, India
-Department of CSE, JNTUHCES, Sultanpur, Medak, Telangana, India
-Accepted 25 April 2016, Available online 30 April 2016, Vol.6, No.2 (April 2016)"
 c5318c79bc1b880e8356211b837b684f1ee6e5c4,Acquiring Common Sense Spatial Knowledge Through Implicit Spatial Templates,"Acquiring Common Sense Spatial Knowledge through Implicit Spatial Templates
 Department of Computer Science
 Computer Vision Laboratory
@@ -68510,13 +57933,6 @@ ETH Zurich
 Marie-Francine Moens
 Department of Computer Science
 KU Leuven"
-c5decf0a3906c85b6540e96c9c7003957c6d395b,Optimizing the Trade-off between Single-Stage and Two-Stage Object Detectors using Image Difficulty Prediction,"Optimizing the Trade-off between
-Single-Stage and Two-Stage Deep Object Detectors
-using Image Difﬁculty Prediction
-Petru Soviany, Radu Tudor Ionescu
-Department of Computer Science
-University of Bucharest, Romania
-E-mails:"
 c52aa6b9c7b89782f2316ce8ef2156fa06a3696d,Learning Semantic Part-Based Models from Google Images,"Learning Semantic Part-Based Models
 from Google Images
 Davide Modolo and Vittorio Ferrari"
@@ -68528,13 +57944,6 @@ Online First Publication, May 11, 2017. http://dx.doi.org/10.1037/emo0000328
 CITATION
 Deska, J. C., Lloyd, E. P., & Hugenberg, K. (2017, May 11). The Face of Fear and Anger: Facial
 online publication. http://dx.doi.org/10.1037/emo0000328"
-c5c0cda46a77a7ea8c1f6d4d762b189ef424ffa4,Semantic 3 D Reconstruction of Heads,"Semantic 3D Reconstruction of Heads
-Fabio Maninchedda1, Christian H¨ane2,(cid:63), Bastien Jacquet3,(cid:63),
-Ama¨el Delaunoy(cid:63), Marc Pollefeys1,4
-ETH Zurich
-UC Berkeley
-Kitware SAS
-Microsoft"
 c588c89a72f89eed29d42f34bfa5d4cffa530732,Attributes2Classname: A Discriminative Model for Attribute-Based Unsupervised Zero-Shot Learning,"Attributes2Classname: A discriminative model for attribute-based
 unsupervised zero-shot learning
 Berkan Demirel1,3, Ramazan Gokberk Cinbis2, Nazli Ikizler-Cinbis3
@@ -68560,10 +57969,6 @@ Brandon Amos 1 Lei Xu 2 * J. Zico Kolter 1"
 c5b05718963f4edff80456c441796e4199ad8d41,Sampling and Ontologically Pooling Web Images for Visual Concept Learning,"Sampling and Ontologically Pooling Web Images for
 Visual Concept Learning
 Shiai Zhu, Chong-Wah Ngo, and Yu-Gang Jiang"
-c5a561c662fc2b195ff80d2655cc5a13a44ffd2d,Using Language to Learn Structured Appearance Models for Image Annotation,"Using Language to Learn Structured Appearance
-Models for Image Annotation
-Michael Jamieson, Student Member, IEEE, Afsaneh Fazly, Suzanne Stevenson, Sven Dickinson, Member, IEEE,
-Sven Wachsmuth, Member, IEEE"
 c590c6c171392e9f66aab1bce337470c43b48f39,Emotion Recognition by Machine Learning Algorithms using Psychophysiological Signals,"Emotion Recognition by Machine Learning Algorithms using
 Psychophysiological Signals
 Eun-Hye Jang, 2Byoung-Jun Park, 3Sang-Hyeob Kim, 4Jin-Hun Sohn
@@ -68577,17 +57982,6 @@ c54e8c7a4f9c2ebd8787aecafa4cfdb35bfd49e0,Effective Use of Bidirectional Language
 Medical Named Entity Recognition
 Devendra Singh Sachan1,*, Pengtao Xie1, and Eric P Xing1
 Petuum Inc, Pittsburgh, 15222, USA"
-c5637543e80f97c9ddab8b54a635cf71941e2786,Self-Calibrating View-Invariant Gait Biometrics,"This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination.
-IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS
-Self-Calibrating View-Invariant Gait Biometrics
-Michela Goffredo, Member, IEEE, Imed Bouchrika, Member, IEEE, John N. Carter, Member, IEEE, and
-Mark S. Nixon, Associate Member, IEEE"
-c5c6ec48ae98d86171360b19e3ec03738c712f53,Infinite Hidden Conditional Random Fields for Human Behavior Analysis,"Inﬁnite Hidden Conditional Random Fields for
-Human Behavior Analysis
-Konstantinos Bousmalis, Student Member, IEEE,
-Stefanos Zafeiriou, Member, IEEE,
-Louis-Philippe Morency, Member, IEEE,
-nd Maja Pantic, Fellow, IEEE"
 1fd54172f7388cd83ed78ff9165519296de5cf20,Changing the Image Memorability: From Basic Photo Editing to GANs,"Changing the Image Memorability: From Basic Photo Editing to GANs
 Oleksii Sidorov
 The Norwegian Colour and Visual Computing Laboratory, NTNU
@@ -68601,9 +57995,6 @@ Pravakar Roy
 Volkan Isler∗"
 1ff057f2fb8258bd5359cded950a3627bd8ee1f4,Low-rank embedding for semisupervised face classification,"Low-Rank Embedding for Semisupervised Face Classiﬁcation
 Gaurav Srivastava, Ming Shao and Yun Fu∗"
-1fbde67e87890e5d45864e66edb86136fbdbe20e,The Action Similarity Labeling Challenge,"The Action Similarity Labeling Challenge
-Orit Kliper-Gross, Tal Hassner, and
-Lior Wolf, Member, IEEE"
 1f7cd3343f4b6b0f936c94e3a45c477c014e2b5c,3D Human Pose Estimation on a Configurable Bed from a Pressure Image,"D Human Pose Estimation on a Conﬁgurable Bed from a Pressure Image
 Henry M. Clever*, Ariel Kapusta, Daehyung Park, Zackory Erickson, Yash Chitalia, Charles C. Kemp"
 1f8d539885f78e1a9d1314e952f3099e71676a5b,Audio-Visual Speaker Diarization Based on Spatiotemporal Bayesian Fusion,"Audio-Visual Speaker Diarization Based on
@@ -68640,10 +58031,6 @@ DEEP NEURAL NETWORKS
 Jesse M. Johns, Jeremiah Rounds & Michael J. Henry
 Paciﬁc Northwest National Laboratory
 Richland, WA 99352, USA"
-1f41a96589c5b5cee4a55fc7c2ce33e1854b09d6,Demographic Estimation from Face Images: Human vs. Machine Performance,"Demographic Estimation from Face Images:
-Human vs. Machine Performance
-Hu Han, Member, IEEE, Charles Otto, Student Member, IEEE, Xiaoming Liu, Member, IEEE
-nd Anil K. Jain, Fellow, IEEE"
 1f06651fc5ce2c10cb1f4ad53dd9c931ceb66448,Eliminating the Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360 ^\circ ∘ Panoramic Imagery,"Eliminating the Blind Spot: Adapting 3D Object
 Detection and Monocular Depth Estimation to
 60◦ Panoramic Imagery
@@ -68684,9 +58071,6 @@ Image Classiﬁcation
 Joshi, A.J.; Porikli, F.; Papanikolopoulos, N.
 TR2012-026
 January 2012"
-1ffe20eb32dbc4fa85ac7844178937bba97f4bf0,Face Clustering: Representation and Pairwise Constraints,"Face Clustering: Representation and Pairwise
-Constraints
-Yichun Shi, Student Member, IEEE, Charles Otto, Member, IEEE, and Anil K. Jain, Fellow, IEEE"
 1fcd7978c6956fd9a0d752ecc9f5ac1a1b2896e9,Impact of Face Registration Errors on Recognition,"Impact of Face Registration Errors on Recognition
 E. Rentzeperis, A. Stergiou, A. Pnevmatikakis and L. Polymenakos
 Athens Information Technology, Autonomic and Grid Computing,
@@ -68720,21 +58104,6 @@ Chen Change Loy (Eds.)
 PERSON RE-IDENTIFICATION
 October 10, 2013
 Springer"
-1fc952fef09d63c61b9b8828f872b7a018eefac1,QUEST: Quadriletral Senary bit Pattern for Facial Expression Recognition,"ACCEPTED IN SMC IEEE CONFERENCE 2018 (PAPER ID: 13628)
-QUEST:Quadriletral Senary bit Pattern for Facial
-Expression Recognition
-Monu Verma1
-Prafulla Saxena2
-S. K. Vipparthi3
-Gridhari Singh4
-Dept. of Computer Science and Engineering, Malaviya national Institute of Technology, Jaipur, India
-improves"
-1f69fa423b076e19dc2ccf6bc9013f09ae39133c,Multimodal Dialogs (MMD): A large-scale dataset for studying multimodal domain-aware conversations,"Towards Building Large Scale Multimodal Domain-Aware Conversation Systems
-Amrita Saha1,2
-Mitesh M. Khapra2
-Karthik Sankaranarayanan1
-IBM Research AI
-I.I.T. Madras, India"
 1fff309330f85146134e49e0022ac61ac60506a9,Data-Driven Sparse Sensor Placement for Reconstruction,"Data-Driven Sparse Sensor Placement for Reconstruction
 Krithika Manohar∗, Bingni W. Brunton, J. Nathan Kutz, and Steven L. Brunton
 Corresponding author:"
@@ -68776,11 +58145,6 @@ Xiang Xu, Ha A. Le, Pengfei Dou, Yuhang Wu, Ioannis A. Kakadiaris
 {xxu18, hale4, pdou, ywu35,
 Computational Biomedicine Lab
 800 Calhoun Rd. Houston, TX, USA"
-1f35f0400d6d112e3b27231d0d9241258efd782d,Learning to Rank Using High-Order Information,"Learning to Rank Using High-Order Information
-Puneet Kumar Dokania1, Aseem Behl2, C.V. Jawahar2, and M. Pawan Kumar1
-Ecole Centrale de Paris
-INRIA Saclay, France
-IIIT Hyderabad, India"
 1fa9c5af78b3ca04476f4ee6910684dc19008f5e,Supplementary Material : Cross-Dataset Adaptation for Visual Question Answering,"Supplementary Material:
 Cross-Dataset Adaptation for Visual Question Answering
 Wei-Lun Chao∗
@@ -68815,10 +58179,6 @@ www.iosrjournals.org
 Face Recognition using Feed Forward Neural Network
 Pooja Rani
 (Department of computer science/ Punjabi university, India)"
-1fe74d637bc5e7d95abcd18b6967e51461fd8cdd,On the Dynamic Selection of Biometric Fusion Algorithms,"On the Dynamic Selection of Biometric Fusion
-Algorithms
-Mayank Vatsa, Member, IEEE, Richa Singh, Member, IEEE, Afzel Noore, Member, IEEE, and
-Arun Ross, Member, IEEE"
 1f0c7b93636f879bd5ef3dd915a02dcd813a053d,Interpreting Deep Visual Representations via Network Dissection,"Interpreting Deep Visual Representations via
 Network Dissection
 Bolei Zhou∗, David Bau∗, Aude Oliva, and Antonio Torralba"
@@ -68872,11 +58232,6 @@ Computer Vision Lab, ETH Zurich, Switzerland"
 1f47a13548317602ec76eafbea44d7b39926c4cd,Stacking-Based Deep Neural Network: Deep Analytic Network for Pattern Classification,"Stacking-Based Deep Neural Network: Deep
 Analytic Network for Pattern Classification
 Cheng-Yaw Low, Jaewoo Park, and, Andrew Beng-Jin Teoh, Senior Member, IEEE"
-1f614a97e16671c091b1bcd1a33e1280822b53db,Tracking People's Hands and Feet Using Mixed Network AND/OR Search,"DRAFT FOR TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
-Tracking people’s hands and feet using mixed
-network AND/OR search
-Vlad I. Morariu, Member, IEEE, David Harwood, Member, IEEE,
-nd Larry S. Davis, Fellow, IEEE"
 1fbb66a9407470e1da332c4ef69cdc34e169a3d7,A Baseline for General Music Object Detection with Deep Learning,"Article
 A Baseline for General Music Object Detection with
 Deep Learning
@@ -68900,16 +58255,6 @@ Cupertino, CA 95014
 Shaoting Zhang
 UNC Charlotte
 Charlotte, NC 28223"
-1f3370e2e6381408efe11e69ab12586bd6f74dc8,Report: Feature Selection Techniques for Classification,"Feature Selection Techniques for Classiﬁcation:
-A widely applicable code library
-Giorgio Roffo
-University of Verona,
-Department of Computer Science"
-1fef45786e707e6b9b8517b0403e596ecbdea6a5,Sketch-based manga retrieval using manga109 dataset,"JOURNAL OF LATEX CLASS FILES, VOL. 11, NO. 4, DECEMBER 2012
-Sketch-based Manga Retrieval
-using Manga109 Dataset
-Yusuke Matsui, Member, IEEE, Kota Ito, Yuji Aramaki, Toshihiko Yamasaki, Member, IEEE,
-nd Kiyoharu Aizawa, Senior Member, IEEE,"
 1f8304f4b51033d2671147b33bb4e51b9a1e16fe,Beyond Trees : MAP Inference in MRFs via OuterPlanar Decomposition,"Noname manuscript No.
 (will be inserted by the editor)
 Beyond Trees:
@@ -68993,11 +58338,6 @@ with Sequential Trajectory Prior
 Min Yang(B), Mingtao Pei, Jiajun Shen, and Yunde Jia
 Beijing Laboratory of Intelligent Information Technology, School of Computer
 Science, Beijing Institute of Technology, Beijing 100081, People’s Republic of China"
-1f53ca209f982500069fed73efe2345358eff79e,Pedestrian Detection with Deep Convolutional Neural Network,"Pedestrian Detection with Deep Convolutional
-Neural Network
-Xiaogang Chen, Pengxu Wei, Wei Ke, Qixiang Ye, Jianbin Jiao
-School of Electronic,Electrical and Communication Engineering, University of
-Chinese Academy of Science, Beijing, China"
 1fd8c71a8859da611a8fde1cbb2bba1c7cf00b4c,EYEDIAP: a database for the development and evaluation of gaze estimation algorithms from RGB and RGB-D cameras,"This paper was presented at the 2014 Symposium on Eye Tracking Research & Applications 2014
 EYEDIAP: A Database for the Development and Evaluation of Gaze Estimation
 Algorithms from RGB and RGB-D Cameras
@@ -69055,9 +58395,6 @@ Universidad de Las Palmas de Gran Canaria, Spain"
 Facial Expression Classification Method Based on Pseudo
 Zernike Moment and Radial Basis Function Network
 Tran Binh Long, Le Hoang Thai, and Tran Hanh"
-4dd72cdafead8a98dbc77a1a74bd66ffb90d3e01,Virtual and Real World Adaptation for Pedestrian Detection,"Virtual and Real World Adaptation for
-Pedestrian Detection
-David V ´azquez, Antonio M. L ´opez, Member, IEEE, Javier Mar´ın, Daniel Ponsa, David Ger ´onimo"
 4dff517b1578dec9155936f29aa9e8ca174e0804,Integrated Object Segmentation and Tracking for 3D LIDAR Data,
 4d5a12fe88e35bb5c4a556a6b2598f7dd5284f46,Sentence transition matrix: An efficient approach that preserves sentence semantics,"Sentence transition matrix: An efficient approach that preserves
 sentence semantics
@@ -69107,23 +58444,11 @@ School of Science, Maefahluang University
 Department of Computer Engineering, Rajabhat Chiangmai University
 02 ChangPuek, Muang Chiangmai 50300, Thailand
 E-mail:"
-4d510bca00b625f86606cb0096299b993090534a,Small Sample Learning in Big Data Era,"Small Sample Learning in Big Data Era
-Jun Shu
-Zongben Xu
-Deyu Meng
-School of Mathematics and Statistics
-Ministry of Education Key Lab of Intelligent Networks and Network Security
-Xi’an Jiaotong University, Xian, China"
 4d2975445007405f8cdcd74b7fd1dd547066f9b8,Image and Video Processing for Affective Applications,"Image and Video Processing
 for Affective Applications
 Maja Pantic and George Caridakis"
 4d7e1eb5d1afecb4e238ba05d4f7f487dff96c11,Largest center-specific margin for dimension reduction,"978-1-5090-4117-6/17/$31.00 ©2017 IEEE
 ICASSP 2017"
-4d9d25e67ebabbfc0acd63798f1a260cb2c8a9bd,Playing for Data: Ground Truth from Computer Games,"Playing for Data: Ground Truth from Computer Games
-Stephan R. Richter∗1 Vibhav Vineet∗2
-Stefan Roth1 Vladlen Koltun2
-TU Darmstadt
-Intel Labs"
 4dd2744a37bd1e666346a41dcd2a271945c74e2f,Human-Robot Teaming : Approaches from Joint Action and Dynamical Systems,"Human Robot Teaming: Approaches from Joint
 Action and Dynamical Systems
 Tariq Iqbal and Laurel D. Riek"
@@ -69257,10 +58582,6 @@ Mideplan, Chile (second and third author). A preliminary partial version of this
 Conference on Artiﬁcial Intelligence (MICAI 2005), pp. 405–414, LNAI Series vol. 3789.
 September 3, 2007
 DRAFT"
-4df34e0194faa27078832cb5078a2af6c9d0ea9b,Saliency Prediction in the Deep Learning Era: An Empirical Investigation,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
-Saliency Prediction in the Deep Learning Era:
-An Empirical Investigation
-Ali Borji, Member, IEEE"
 4d334cfafd11a93394917adcffef6c1d27aa178b,Refined Clustering technique based on boosting and outlier detection,"International Journal of Scientific & Engineering Research, Volume 6, Issue 11, November-2015                                                                                                 472
 ISSN 2229-5518
 Refined Clustering technique based on boosting
@@ -69280,26 +58601,6 @@ Huanhuan Yu, Menglei Hu and Songcan Chen"
 4d47261b2f52c361c09f7ab96fcb3f5c22cafb9f,Deep multi-frame face super-resolution,"Deep multi-frame face super-resolution
 Evgeniya Ustinova, Victor Lempitsky
 October 17, 2017"
-4d4b1aa87af8bfd65ac7bc250bba5951aed40986,A Survey on Model Based Approaches for 2D and 3D Visual Human Pose Recovery,"Sensors 2014, 14, 4189-4210; doi:10.3390/s140304189
-OPEN ACCESS
-sensors
-ISSN 1424-8220
-www.mdpi.com/journal/sensors
-Review
-A Survey on Model Based Approaches for 2D and 3D Visual
-Human Pose Recovery
-Xavier Perez-Sala 1
-,*, Sergio Escalera 2, Cecilio Angulo 3 and Jordi Gonz`alez 4
-Fundaci´o Privada Sant Antoni Abat, Vilanova i la Geltr´u, Universitat Polit`ecnica de Catalunya,
-Vilanova i la Geltr´u 08800, Catalonia, Spain
-Department Mathematics (MAIA), Universitat de Barcelona and Computer Vision Center (CVC),
-Barcelona 08007, Catalonia, Spain; E-Mail:
-Automatic Control Department (ESAII), Universitat Polit`ecnica de Catalunya,
-Vilanova i la Geltr´u 08800, Catalonia, Spain; E-Mail:
-Department Computer Science, Universitat Aut`onoma de Barcelona and Computer Vision Center
-(CVC), Bellaterra 08193, Catalonia, Spain; E-Mail:
-* Author to whom correspondence should be addressed; E-Mail:
-Received: 29 November 2013; in revised form: 30 January 2014 / Accepted: 9 February 2014 /"
 4df3143922bcdf7db78eb91e6b5359d6ada004d2,The Chicago face database: A free stimulus set of faces and norming data.,"Behav Res (2015) 47:1122–1135
 DOI 10.3758/s13428-014-0532-5
 The Chicago face database: A free stimulus set of faces
@@ -69372,10 +58673,6 @@ University of Udine, 33100 Udine, Italy
 University of Massatchussets Lowell, 01852 Lowell, MA, USA
 University of California Riverside, 92507 Riverside, CA, USA"
 1222705b626a33974e85985ddabfcea135e9ddce,k-fold Subsampling based Sequential Backward Feature Elimination,
-129a6daa54a7334930b6413875b6154acef3922a,Data-Driven Synthesis of Cartoon Faces Using Different Styles,"Data-Driven Synthesis of Cartoon
-Faces Using Different Styles
-Yong Zhang, Weiming Dong, Member, IEEE, Chongyang Ma, Xing Mei, Member, IEEE, Ke Li,
-Feiyue Huang, Bao-Gang Hu, Senior Member, IEEE, and Oliver Deussen"
 1267eae42798940c105355a9590363fb6560595b,From Coarse to Fine: Robust Hierarchical Localization at Large Scale,"From Coarse to Fine: Robust Hierarchical Localization at Large Scale
 Paul-Edouard Sarlin1 Cesar Cadena1 Roland Siegwart1 Marcin Dymczyk1,2
 Autonomous Systems Lab, ETH Z¨urich
@@ -69385,9 +58682,6 @@ Utsav Garg 1 Viraj Prabhu 2 Deshraj Yadav 2 Ram Ramrakhya 3 Harsh Agrawal 2 Dhru
 fabrik.cloudcv.org"
 12cd96a419b1bd14cc40942b94d9c4dffe5094d2,Leveraging Captions in the Wild to Improve Object Detection,"Proceedings of the 5th Workshop on Vision and Language, pages 29–38,
 Berlin, Germany, August 12 2016. c(cid:13)2016 Association for Computational Linguistics"
-123bc74a006a75fefcdd9995cbdc1c6c64c8bed6,Socially Constrained Structural Learning for Groups Detection in Crowd,"Socially Constrained Structural Learning for
-Groups Detection in Crowd
-Francesco Solera, Simone Calderara, Member, IEEE, and Rita Cucchiara, Fellow, IEEE"
 12b58a712396bc2fd74cd19a4d758d7b9c104c3f,Cross-Domain Recommendation in the Hotel Sector,"Cross-Domain Recommendation in the Hotel Sector
 Marie Al-Ghossein
 LTCI, T´el´ecom ParisTech
@@ -69410,16 +58704,6 @@ Joint Samsung-HSE lab
 12e80b3a89bc021a6352840fb4552df842a6fe7d,Fast sparse representation with prototypes,"Fast Sparse Representation with Prototypes
 Jia-Bin Huang and Ming-Hsuan Yang
 University of California at Merced"
-120e7a0e9e7bd0eaa248f04cf393a735832a5044,The Analysis of Local Motion and Deformation in Image Sequences Inspired by Physical Electromagnetic Interaction,"XIAODONG ZHUANG1,2 and N. E. MASTORAKIS1,3,4
-. WSEAS Research Department, Agiou Ioannou Theologou 17-23, 15773, Zografou,
-Athens, GREECE
-. Automation Engineering College, Qingdao University, Qingdao, 266071, CHINA
-. Department of Computer Science, Military Institutions of University Education,
-Hellenic Naval Academy, Terma Hatzikyriakou, 18539, Piraeus, GREECE
-http://www.wseas.org/mastorakis
-. Technical University of Sofia, BULGARIA
-The Analysis of Local Motion and Deformation in Image Sequences
-Inspired by Physical Electromagnetic Interaction"
 12ebb51d50f704b5d0a8d821e90dd336175ec8aa,TUHOI: Trento Universal Human Object Interaction Dataset,"Proceedings of the 25th International Conference on Computational Linguistics, pages 17–24,
 Dublin, Ireland, August 23-29 2014."
 1295cbaf3b03de2eb8c79530289f5939d7819e5c,DeepFix: A Fully Convolutional Neural Network for Predicting Human Eye Fixations,"DeepFix: A Fully Convolutional Neural Network
@@ -69455,26 +58739,6 @@ temps réel, au moyen d’une simple webcam. A partir de
 vidéos du challenge AVEC’2014, nous avons entraîné un
 lassiﬁeur neuronal à extraire des prototypes de visages
 selon différentes valeurs du score de dépression de Beck"
-12c548d99fdc59bd702910af2c3daa17ed43e5d7,Performance analysis of different matrix decomposition methods on face recognition,"016 International Conference on Computer Communication and Informatics (ICCCI -2016), Jan. 07 – 09, 2016, Coimbatore, INDIA
-Performance analysis of different Matrix
-decomposition methods on Face Recognition
-Dept. of Electronics and Communication Engineering
-Dept. of Electronics and Communication Engineering
-Suresh Babu K and K B Raja
-UVCE, Bengaluru, India
-the  recognition  accuracy
-image  and  known  stored  images  in  terms  of  dimension
-reduced  images  is  made  to  declare  identity  of  a  person.  It  is
-proved
-improved  by
-onverting the images  with variation in expression to neutral
-images [5] and using image fusion with light field camera for
-image  capturing  [6].  Maintaining  robustness  in  recognition
-ccuracy is elusive for key factors such as pose [7], back view
-illumination  variation  [9]  and  others.  Developing
-illumination invariant image  representation  with textures is a
-difficult  task  and  pre-processing  methods  for  mitigating  the
-illumination  effect  are  discussed  in  future  sections  of  this"
 12ff1c48f5776fda9d156c7b324af3f2674420a9,Are Large Scale Training Images or Discriminative Features Important for Codebook Construction?,
 129ac698f62ca7f9024423671f4128d83a0c3c66,Image Matching Scheme by using Bhattacharyya Coefficient Algorithm,"ISSN(Online): 2320-9801
 ISSN (Print):  2320-9798
@@ -69515,11 +58779,6 @@ April 5, 2007"
 12149fc431d2b3ec4d1f194e92e74c765e51ee67,Concentration in unbounded metric spaces and algorithmic stability,"Concentration in unbounded metric spaces and algorithmic stability
 Aryeh Kontorovich
 Department of Computer Science, Ben-Gurion University, Beer Sheva 84105, ISRAEL"
-12055b8f82d5411f9ad196b60698d76fbd07ac1e,Multiview Facial Landmark Localization in RGB-D Images via Hierarchical Regression With Binary Patterns,"Multiview Facial Landmark Localization in RGB-D
-Images via Hierarchical Regression
-With Binary Patterns
-Zhanpeng Zhang, Student Member, IEEE, Wei Zhang, Member, IEEE, Jianzhuang Liu, Senior Member, IEEE,
-nd Xiaoou Tang, Fellow, IEEE"
 12ebeb2176a5043ad57bc5f3218e48a96254e3e9,Traffic Road Sign Detection and Recognition for Automotive Vehicles,"International Journal of Computer Applications (0975 – 8887)
 Volume 120 – No.24, June 2015
 Traffic Road Sign Detection and Recognition for
@@ -69572,17 +58831,6 @@ Feature Afﬁnity based Pseudo Labeling for
 Semi-supervised Person Re-identiﬁcation
 Guodong Ding, Shanshan Zhang, Salman Khan, Zhenmin Tang, Jian Zhang, Senior Member, IEEE and Fatih
 Porikli, Fellow, IEEE"
-12d0c11d546d91e776a170898ebf3a38c010695c,Semi-Supervised Hashing for Large-Scale Search,"Semi-Supervised Hashing for Large Scale
-Search
-Jun Wang, Member, IEEE, Sanjiv Kumar, Member, IEEE, and Shih-Fu Chang, Fellow, IEEE"
-12727bb8a4a1462553a13a253a97c2569cbcba0a,Study on Different Representation Methods for Subspace Segmentation,"International Journal of Grid Distribution Computing
-Vol.8, No.1 (2015), pp.259-268
-http://dx.doi.org/10.14257/ijgdc.2015.8.1.24
-Study on Different Representation Methods for Subspace
-Segmentation
-Jiangshu Wei, Mantao Wang and Qianqian Wu
-College of Information and Engineering, Sichuan Agricultural University, Ya’an,
-625014, China"
 12fd613bc68101176d8fdf1b28d4d6fb3e3fec6f,Training a Scene-Specific Pedestrian Detector Using Tracklets,"Training a Scene-Speciﬁc Pedestrian Detector Using Tracklets
 Yunxiang Mao
 Zhaozheng Yin
@@ -69595,26 +58843,6 @@ University of California, Berkeley - Berkeley, CA 94720"
 Arvind Agarwal
 Jeff M. Phillips†
 Suresh Venkatasubramanian‡"
-124476c2815bbfb523c77943c74356f94f79b580,Recognition of Faces in Unconstrained Environments: A Comparative Study,"Hindawi Publishing Corporation
-EURASIP Journal on Advances in Signal Processing
-Volume 2009, Article ID 184617, 19 pages
-doi:10.1155/2009/184617
-Research Article
-Recognition of Faces in Unconstrained Environments:
-A Comparative Study
-Javier Ruiz-del-Solar, Rodrigo Verschae, and Mauricio Correa
-Department of Electrical Engineering, Universidad de Chile, Avenida Tupper 2007, 837-0451 Santiago, Chile
-Correspondence should be addressed to Javier Ruiz-del-Solar,
-Received 10 October 2008; Revised 31 January 2009; Accepted 13 March 2009
-Recommended by Kevin Bowyer
-The aim of this work is to carry out a comparative study of face recognition methods that are suitable to work in unconstrained
-environments. The analyzed methods are selected by considering their performance in former comparative studies, in addition to
-e real-time, to require just one image per person, and to be fully online. In the study two local-matching methods, histograms
-of LBP features and Gabor Jet descriptors, one holistic method, generalized PCA, and two image-matching methods, SIFT-
-ased and ERCF-based, are analyzed. The methods are compared using the FERET, LFW, UCHFaceHRI, and FRGC databases,
-which allows evaluating them in real-world conditions that include variations in scale, pose, lighting, focus, resolution, facial
-expression, accessories, makeup, occlusions, background and photographic quality. Main conclusions of this study are: there is
-large dependence of the methods on the amount of face and background information that is included in the face’s images,"
 126be977c03d732fbef2381565a41b957d41a2cc,Discourse-Level Language Understanding with Deep Learning,
 12c262912f4c09e6f34d40de77f68b465d80ac8d,Adaptive Graph Guided Embedding for Multi-label Annotation,"Proceedings of the Twenty-Seventh International Joint Conference on Artiﬁcial Intelligence (IJCAI-18)
 FurOutdoorMentalHumanmadeBrownFur(cid:1850)(cid:3039)(cid:1850)(cid:3048)WaterOutdoorWaterTreesFigure1:Frameworkofourmodel,whereanadaptiveafﬁnitygraphSconnectspair-wiserelationsacrosslabeledandunlabeledsamples.Apre-deﬁnedgraphfullyprovideslocalstructureinformationandacceleratesoptimizationprocess.AprojectionPprojectsdataintoacommonanddistinctivespacewhichalsoeliminatesinterruptionsfromnoiseandoutliers.P,S,andlabelmatrixFaresimultaneouslyupdatedtoachieveaccurateandrobustperformance.performance.Consequently,semi-supervisedlearning[Zhuetal.,2003]especiallygraph-basedapproach[Zhaetal.,2009]hasattractedgreatattention.However,theystillhavelimitationsthatthesemethodshighlydependonthepre-constructedgraphbutrarelyoptimizeitonline.Inaddi-tion,mostmethodsconstructgraphdirectlyonfeaturespace,whichissensitivetonoiseandoutliers.Severalworkuti-lizeadaptivegraphstohandletheproblem[Nieetal.,2012;2016].However,thesemethodsmainlyfocusonsingle-labelclassiﬁcationinsteadofmulti-labelscenario.Tothisend,weproposeanovelAdaptiveGraphGuidedEmbedding(AG2E)formulti-labellearninginsemi-supervisedfashion.Figure1showstheframeworkofAG2E,whosecoreideaislearningasemi-supervisedlabelpropaga-tionandaneffectiveembeddingsimultaneouslytoseekala-tentspace,andthusunlabeledimagescanbewellrecovered.Ourmaincontributionsaresummarizedasfollows:(cid:15)Weseekanadaptivegraphtoautomaticallycapturethelatentstructureofthedata.Moreover,apre-deﬁned"
@@ -69674,26 +58902,6 @@ Dhruv Mahajan
 Yahoo! Labs Bangalore
 S. Sundararajan
 Yahoo! Labs Bangalore"
-120b22e7a47923e42a123b9b68a93ccac5aaea6d,Paper on Ear Biometric Authentication,"Research Article                                                                                                                           Volume 6 Issue No.10
-ISSN XXXX XXXX © 2016 IJESC
-Review Paper on Ear Biometric Authentication
-Shubham Mohurle 1, See ma Khutwad 2, Pratiksha Kunjir3, Anjali Bhosle4
-Assistant Professor4
-KJCOEM R, Pune, India
-Abstrac t:
-In this paper we have studied about ear bio metric  authentication. Powe rful bio metrics likes fingerprint, face  and iris are used while
-omparing  the  new  biometric  technology  that  is  human  ear  recognition.  We  are studied  different  methods  like  2D  ear  reco gnition,
-Pattern extract ion method, robust algorithm, Pixe l based feature extraction.  Genetic algorith m  is the solution to all proble ms faced  by
-these methods. Recognition Rate for t ime series  modeling is 99% obtained.AR  model is used for time series  modeling.  All  methods
-re discussed later.
-Ke ywor ds:  Ear, Recognition Rate, 2D image, AR model
-During crime  investigation, in the absence of (valid) fingerprints
-nd  footprints  ear  ma rks  are   used  for  identification.  Just  like
-fingerprints,  use  of  ear  shapes  recommends  its  use  for  human
-identification.  An  ear  recognition  system  is  simila r  to  face
-recognition  system  and  which  has  five  components:  image
-cquisition, preprocessing, feature extraction,  model training and
-template  matching. Du ring image  gaining, an image of the ear is"
 12c7ecbfd714c160d2a6bb9cf03fa8b88e8da62b,Impaired Recognition of Basic Emotions from Facial Expressions in Young People with Autism Spectrum Disorder: Assessing the Importance of Expression Intensity.,"Griffiths, S. L., Jarrold, C., Penton-Voak, I., Woods, A., Skinner, A., &
 Munafo, M. (2017). Impaired Recognition of Basic Emotions from Facial
 Expressions in Young People with Autism Spectrum Disorder: Assessing the
@@ -69714,17 +58922,6 @@ General rights
 This document is made available in accordance with publisher policies. Please cite only the published
 version using the reference above. Full terms of use are available:
 http://www.bristol.ac.uk/pure/about/ebr-terms.html"
-12d813f14166578dea8aa6aacc945102dddfd05d,Fog Computing in 5 G Networks : An Application Perspective,"“fog˙5g˙full”
-016/5/4
-page 1
-Chapter 1
-Fog Computing in 5G Networks: An Application
-Perspective
-Harshit Gupta1, Sandip Chakraborty1, Soumya K. Ghosh1,
-nd Rajkumar Buyya2
-Department of Computer Science and Engineering, IIT
-CLOUDS Laboratory, University of Melbourne, Australia
-Kharagpur, India"
 1287bfe73e381cc8042ac0cc27868ae086e1ce3b,Computational Mid-Level Vision: From Border Ownership to Categorical Object Recognition,
 12831caca9674e0ab3fe2fc02a447ddb5a372994,Deep Aesthetic Quality Assessment With Semantic Information,"Deep Aesthetic Quality Assessment with Semantic
 Information
@@ -69758,18 +58955,6 @@ Bruna Vieira Frade
 Erickson R. Nascimento
 Universidade Federal de Minas Gerais (UFMG), Brazil
 {brunafrade,"
-280d45fb813e75622b7c584ee7fba70066245871,Visual Tracking with Online Incremental Deep Learning and Particle Filter,"International Journal of Signal Processing, Image Processing and Pattern Recognition
-Vol.8, No.12 (2015), pp.107-120
-http://dx.doi.org/10.14257/ijsip.2015.8.12.12
-Visual Tracking with Online Incremental Deep Learning and
-Particle Filter
-Shuai Cheng 1, Yonggang Cao3,1, Junxi Sun2 and Guangwen Liu1*
-School of Electronic Information Engineering, Changchun University of Science
-School of Computer Science and information Technology, Northeast Normal
-nd Technology, Changchun, China
-Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of
-University, Changchun, China
-Sciences, Changchun, China"
 28103f6c09fd64c90a738076b0681400d4d31c9f,Color Invariants for Person Reidentification,"Color Invariants for Person
 Re-Identiﬁcation
 Igor Kviatkovsky
@@ -69786,30 +58971,7 @@ Departamento de Tecnologia Fotonica
 Campus de Monteganedos/n
 8660 Boadilla del Monte (Spain)
 e-mail: {aruiz,"
-288bddfabe739b32721df62d821632e3dafed06a,Robust multi-image based blind face hallucination,"Robust Multi-Image Based Blind Face Hallucination
-Yonggang Jin, 2Christos-Savvas Bouganis
-University of Bristol. 2Imperial College London.
-1.56 0.73
-3.15 0.80
-3.61 0.82
-3.32 0.80
-3.98 0.83
-3.63 0.82
-PCA-Init
-PCA-Est
-PCA-GT
-MPPCA-Est MPPCA-GT
-Methods
-Blurring
-Trans.
-9.67
-Initial
-9.52
-[1, 5]"
 28d65e4d72638983fbc723b102d78b10587c06aa,Low Resolution Sparse Binary Face Patterns,
-28b5b5f20ad584e560cd9fb4d81b0a22279b2e7b,A New Fuzzy Stacked Generalization Technique and Analysis of its Performance,"A New Fuzzy Stacked Generalization Technique
-nd Analysis of its Performance
-Mete Ozay, Student Member, IEEE, Fatos T. Yarman Vural, Member, IEEE"
 286c1e0b34ee6d40706ca6a02604420a192204e7,An overview of NuDetective Forensic Tool and its usage to combat child pornography in Brazil,"An overview of NuDetective Forensic Tool and its usage
 to combat child pornography in Brazil
 Pedro Monteiro da Silva Eleuterio and Mateus de Castro Polastro
@@ -69846,30 +59008,12 @@ Queensgate, Huddersﬁeld, HD1 3DH, United Kingdom"
 Jiasen Lu, Jianwei Yang, Dhruv Batra, Devi Parikh
 Virginia Tech
 {jiasenlu, jw2yang, dbatra,"
-285faa4cc54ef9b1834128705e0f96ad17b61e0b,SIFT Flow: Dense Correspondence across Scenes and Its Applications,"SIFT Flow: Dense Correspondence across
-Scenes and its Applications
-Ce Liu, Member, IEEE, Jenny Yuen, Student Member, IEEE, and Antonio Torralba, Member, IEEE"
 28e77337bcb88e37d36f5660709a53e71377a2a8,5 Discriminative Cluster Analysis,",250+OPEN ACCESS BOOKS106,000+INTERNATIONALAUTHORS AND EDITORS112+ MILLIONDOWNLOADSBOOKSDELIVERED TO151 COUNTRIESAUTHORS AMONGTOP 1%MOST CITED SCIENTIST12.2%AUTHORS AND EDITORSFROM TOP 500 UNIVERSITIESSelection of our books indexed in theBook Citation Index in Web of Science™Core Collection (BKCI)Chapter from the book Theory and Novel Applications of Machine LearningDownloaded from:http://www.intechopen.com/books/theory_and_novel_applications_of_machine_learningPUBLISHED BYWorld's largest Science,Technology & Medicine Open Access book publisherInterested in publishing with InTechOpen?Contact us at"
 286ea63b1b5df1b8b67718f25b47357ec3168e97,Human parsing using stochastic and-or grammars and rich appearances,"Human Parsing using Stochastic And-Or
 Grammars and Rich Appearances
 Brandon Rothrock and Song-Chun Zhu
 UCLA Dept. of Computer Science
 Thursday, November 17, 11"
-28fe6e785b32afdcd2c366c9240a661091b850cf,Facial Expression Recognition using Patch based Gabor Features,"International Journal of Applied Information Systems (IJAIS) – ISSN : 2249-0868
-Foundation of Computer Science FCS, New York, USA
-Volume 10 – No.7, March 2016 – www.ijais.org
-Facial Expression Recognition using Patch based Gabor
-Features
-Electronics & Telecommunication Engg
-Electronics & Telecommunication Engg
-St. Francis Institute of Technology
-St. Francis Institute of Technology
-Vaqar Ansari
-Department
-Mumbai, India
-Anju Chandran
-Department
-Mumbai, India"
 28f5f8dc2f2f9f2a4e49024fe6aa7e9a63b23ab0,Vision-based bicycle detection and tracking using a deformable part model and an EKF algorithm,"Vision-based Bicycle Detection and Tracking using a Deformable Part
 Model and an EKF Algorithm
 Hyunggi Cho, Paul E. Rybski and Wende Zhang"
@@ -69957,16 +59101,6 @@ Robert Bosch, Computer Vision Lab, Hildesheim, Germany,
 Institute of Photogrammetry and GeoInformation, Leibniz Universit¨at Hannover, Germany
 Commission II
 KEY WORDS: Person Re-Identiﬁcation, PRID, Bifocal Stereo, Multipath Person Re-Identiﬁcation"
-28744ee615d343e7372f3bd5006b7822c66261f6,Imagination Based Sample Construction for Zero-Shot Learning,"Imagination Based Sample Construction for Zero-Shot Learning
-Gang Yang
-Renmin University of China
-Beijing, China
-Jinlu Liu
-Renmin University of China
-Beijing, China
-Xirong Li∗
-Renmin University of China
-Beijing, China"
 2805daf3795e4e153d79dbecfe88b830ddc068d3,Articulated human motion tracking with foreground learning,"ARTICULATED HUMAN MOTION TRACKING WITH FOREGROUND LEARNING
 Aichun Zhu1, Hichem Snoussi1, Abel Cherouat2
 ICD - LM2S - Universit´e de Technologie de Troyes (UTT) - UMR STMR CNRS
@@ -70042,16 +59176,6 @@ Naomi Saphra2
 Sammy Mohamed9
 Iasonas Kokkinos3
 Karen Simonyan1"
-28a3673e57839ab75fe1c05ce2a4c1a00a7efe76,Towards Automatic Report Generation in Spine Radiology Using Weakly Supervised Framework,"Towards Automatic Report Generation in Spine
-Radiology using Weakly Supervised Framework
-Zhongyi Han1,2, Benzheng Wei1,2,∗, Stephanie Leung3,4, Jonathan Chung3,4,
-nd Shuo Li3,4,∗
-College of Science and Technology, Shandong University of Traditional Chinese
-Medicine, Jinan, Shandong, China
-Computational Medicine Lab (CML), Shandong University of Traditional Chinese
-Department of Medical Imaging, Western Univeristy, London, ON, Canada
-Medicine, Jinan, Shandong, China
-Digital Imaging Group (DIG), London, ON, Canada"
 28795f32b324eb3601e9a8c1ce93335691e120f3,CliqueCNN: Deep Unsupervised Exemplar Learning,"CliqueCNN: Deep Unsupervised Exemplar Learning
 Miguel A. Bautista∗, Artsiom Sanakoyeu∗, Ekaterina Sutter, Björn Ommer
 Heidelberg Collaboratory for Image Processing
@@ -70204,33 +59328,9 @@ Chebrolu(V&M),Guntur(Dt),
 Andhra Pradesh - India
 Chebrolu(V&M),Guntur(Dt),
 Andhra Pradesh - India"
-162403e189d1b8463952fa4f18a291241275c354,Action Recognition with Spatio-Temporal Visual Attention on Skeleton Image Sequences,"Action Recognition with Spatio-Temporal
-Visual Attention on Skeleton Image Sequences
-Zhengyuan Yang, Student Member, IEEE, Yuncheng Li, Jianchao Yang, Member, IEEE,
-nd Jiebo Luo, Fellow, IEEE
-With a strong ability of modeling sequential data, Recur-
-rent Neural Networks (RNN) with Long Short-Term Memory
-(LSTM) neurons outperform the previous hand-crafted feature
-ased methods [9], [10]. Each skeleton frame is converted into
-feature vector and the whole sequence is fed into the RNN.
-Despite the strong ability in modeling temporal sequences,
-RNN structures lack the ability to efﬁciently learn the spatial
-relations between the joints. To better use spatial information,
-hierarchical structure is proposed in [11], [12] that feeds
-the joints into the network as several pre-deﬁned body part
-groups. However,
-limit
-the effectiveness of representing spatial relations. A spatio-
-temporal 2D LSTM (ST-LSTM) network [13] is proposed
-to learn the spatial and temporal relations simultaneously.
-Furthermore, a two-stream RNN structure [14] is proposed to"
 161c9ef7114bda7c5a60a29ee4a3161b0a76e676,Low Rank Approximation and Decomposition of Large Matrices Using Error Correcting Codes,"Low rank approximation and decomposition of
 large matrices using error correcting codes
 Shashanka Ubaru, Arya Mazumdar Senior Member, IEEE, and Yousef Saad"
-16d1e29b588fd26f5f0ac8038110f7b8500a1ec9,$L_0$ Regularized Stationary-Time Estimation for Crowd Analysis,"L0 Regularized Stationary-Time Estimation
-for Crowd Analysis
-Shuai Yi, Xiaogang Wang, Member, IEEE, Cewu Lu, Member, IEEE,
-Jiaya Jia, Senior Member, IEEE, and Hongsheng Li"
 166b5bdea1f4f850af5b045a953d6de74bc18d1e,Best of both worlds: Human-machine collaboration for object annotation,"Best of both worlds: human-machine collaboration for object annotation
 Olga Russakovsky1, Li-Jia Li2, Li Fei-Fei1
 Stanford University. 2Snapchat (this work was done while at Yahoo! Labs).
@@ -70258,14 +59358,6 @@ For additional information about this publication click this link.
 http://repository.ubn.ru.nl/handle/2066/126858
 Please be advised that this information was generated on 2018-10-16 and may be subject to
 hange."
-16bd796687ca17ac7ca28d28d856b324186628ba,Face Recognition and Verification Using Photometric Stereo: The Photoface Database and a Comprehensive Evaluation,"Face Recognition and Veriﬁcation Using
-Photometric Stereo: The Photoface Database
-nd a Comprehensive Evaluation
-Stefanos Zafeiriou, Member, IEEE, Gary A. Atkinson, Mark F. Hansen, William A. P. Smith, Member, IEEE,
-Vasileios Argyriou, Member, IEEE, Maria Petrou, Senior Member, IEEE, Melvyn L. Smith, and Lyndon N. Smith"
-166f42f66c5e6dd959548acfb97dc77a36013639,Bilevel Model-Based Discriminative Dictionary Learning for Recognition,"Bilevel Model-Based Discriminative Dictionary
-Learning for Recognition
-Pan Zhou, Chao Zhang, Member, IEEE, and Zhouchen Lin, Senior Member, IEEE"
 1670729d1edc9bc6103ee823f1137d302be41397,Patch-based Object Recognition Using Discriminatively Trained Gaussian Mixtures,"Patch-based Object Recognition Using
 Discriminatively Trained Gaussian Mixtures
 Andre Hegerath, Thomas Deselaers, and Hermann Ney
@@ -70273,18 +59365,6 @@ Human Language Technology and Pattern Recognition Group,
 RWTH Aachen University – D-52056 Aachen, Germany
 {hegerath, deselaers,"
 16597862a1df1a983c439e82e0462424f538bb48,Personalized Saliency and its Prediction,
-16fdc3829dc8322a26eac46e93703000005f3d6d,An occlusion reasoning scheme for monocular pedestrian tracking in dynamic scenes,"An Occlusion Reasoning Scheme for Monocular
-Pedestrian Tracking in Dynamic Scenes
-Sourav Garg and Swagat Kumar
-Innovation Lab
-Tata Consultancy Services
-New Delhi, India 201301
-Email:
-Rajesh Ratnakaram and Prithwijit Guha
-Department of Electronics and Electrical Engineering
-Indian Institute of Technology Guwahati
-Guwahati, Assam, India 781039
-Email:"
 16d9b983796ffcd151bdb8e75fc7eb2e31230809,GazeDirector : Fully Articulated Eye Gaze Redirection in Video,"EUROGRAPHICS 2018 / D. Gutierrez and A. Sheffer
 (Guest Editors)
 Volume 37 (2018), Number 2
@@ -70294,21 +59374,7 @@ ID: paper1004"
 Ankesh Anand1 Eugene Belilovsky1 Kyle Kastner1 Hugo Larochelle2,1 Aaron Courville1,3
 Mila
 Google Brain 3CIFAR Fellow"
-169927e68301d881da6585dd09e1bc9a88adf147,AV@CAR: A Spanish Multichannel Multimodal Corpus for In-Vehicle Automatic Audio-Visual Speech Recognition,"A Spanish Multichannel Multimodal Corpus for In-Vehicle Automatic
-Audio-Visual Speech Recognition
-Alfonso Ortega1, Federico Sukno2, Eduardo Lleida1,
-Alejandro Frangi2, Antonio Miguel1, Luis Buera1, Ernesto Zacur2
-Communication Technologies Group and 2Computer Vision Group
-Aragon Institute of Engineering Research (I3A)
-University of Zaragoza, Spain"
 16e8d439fbcf8311efea7b0baeb1a5340272b396,Stereo and LIDAR Fusion based Detection of Humans and Other Obstacles in Farming Scenarios,
-160ab0e879f4451fa4df88cd567508150894ba9d,Cross Dataset Person Re-identification,"Cross Dataset Person Re-identiﬁcation
-Yang Hu, Dong Yi, Shengcai Liao, Zhen Lei, Stan Z. Li(cid:63)
-Center for Biometrics and Security Research
-National Laboratory of Pattern Recognition
-Institute of Automation, Chinese Academy of Sciences (CASIA)
-95 Zhongguancun East Road, 100190, Beijing, China
-{yhu, dong.yi, scliao, zlei,"
 16c884be18016cc07aec0ef7e914622a1a9fb59d,Exploiting Multimodal Data for Image Understanding. (Données multimodales pour l'analyse d'image),"UNIVERSITÉ DE GRENOBLE
 No attribué par la bibliothèque
 THÈSE
@@ -70398,9 +59464,6 @@ The Institute for Information Transmission Problems RAS (Kharkevich Institute)
 National Research University Higher School of Economics (HSE)"
 16022f7f0cf6492fdc3cf768c9f474791ae3d0ca,Detecting Traffic Lights by Single Shot Detection,"Detecting Trafﬁc Lights by Single Shot Detection
 Julian M¨uller1 and Klaus Dietmayer1"
-16bd481fb66259df9c4c22b54797d8e8adc910fc,Robustifying Descriptor Instability Using Fisher Vectors,"Robustifying Descriptor Instability
-using Fisher Vectors
-Ivo Everts, Jan C. van Gemert, Thomas Mensink, Theo Gevers, Member, IEEE"
 16aec3ee9a97162b85b1d51c3c5ce73a472e74b8,Application of Selective Search to Pose estimation,"Application of Selective Search to Pose estimation
 Ujwal Krothapalli
 Department of Electrical and
@@ -70509,30 +59572,12 @@ A dissertation submitted to the University of Bristol in accordance with the
 requirements for the degree of Doctor of Philosophy in the Faculty of Engineering,
 Department of Computer Science.
 July 2009"
-f79ab9baccd466d86460214c5cee9f3be0af4064,Image Segmentation of Medical Images using Automatic Fuzzy C-Mean Clustering,"IJSRD - International Journal for Scientific Research & Development| Vol. 3, Issue 03, 2015 | ISSN (online): 2321-0613
-Image Segmentation of Medical Images using Automatic Fuzzy C-Mean
-Clustering
-Padmini Umorya1 Rajesh Singh2
-Research Scholar 2Assistant Professor
-,2Department of Computer Science and Engineering
-,2NITM College Gwalior, India"
 f79267b0f4c0110051c93f9faabe436215e4fc28,Selective Feature Connection Mechanism: Concatenating Multi-layer CNN Features with a Feature Selector,"Selective Feature Connection Mechanism:
 Concatenating Multi-layer CNN Features with a Feature Selector
 Chen Du1,2, Chunheng Wang1, Cunzhao Shi1, Baihua Xiao1
 Institute of Automation, Chinese Academy of Sciences(CASIA)
 University of Chinese Academy of Sciences(UCAS)
 {duchen2016, chunheng.wang, cunzhao.shi,"
-f73b15d33b9dcf329cf605815be7493b162b1fab,SLMotion - An extensible sign language oriented video analysis tool,"SLMotion – An extensible sign language oriented video analysis tool
-Matti Karppa∗, Ville Viitaniemi∗, Marcos Luzardo∗, Jorma Laaksonen∗, Tommi Jantunen†
-Department of Information and Computer Science,
-Aalto University School of Science, Espoo, Finland,
-Sign Language Centre, Department of Languages,
-University of Jyv¨askyl¨a, Finland,
-We present a software toolkit called SLMotion which provides a framework for automatic and semiautomatic analysis, feature extraction
-nd annotation of individual sign language videos, and which can easily be adapted to batch processing of entire sign language corpora.
-The program follows a modular design, and exposes a Numpy-compatible Python application programming interface that makes it easy
-nd convenient to extend its functionality through scripting. The program includes support for exporting the annotations in ELAN
-format. The program is released as free software, and is available for GNU/Linux and MacOS platforms."
 f7dcadc5288653ec6764600c7c1e2b49c305dfaa,Interactive Image Search with Attributes by,"Copyright
 Adriana Ivanova Kovashka"
 f724cbf5035e2df0dbe9a4992a0100465f5c6db5,Scalable Multicore k-NN Search via Subspace Clustering for Filtering,"Parallel Graph Partitioning for Complex Networks
@@ -70547,11 +59592,6 @@ Fatemeh Sadat Saleh1,2[0000−0002−3695−9876], Mohammad Sadegh
 Aliakbarian1,2,3[0000−0003−3948−6418], Mathieu Salzmann4[0000−0002−8347−8637],
 Lars Petersson2[0000−0002−0103−1904], and Jose M. Alvarez5[0000−0002−7535−6322]
 ANU, 2 Data61-CSIRO, 3 ACRV, 4 CVLab, EPFL, 5 NVIDIA"
-f755d9b2b7ef66ffdf7504b34167b95d0685c18d,Efficient Online Subspace Learning With an Indefinite Kernel for Visual Tracking and Recognition,"Efﬁcient Online Subspace Learning With
-n Indeﬁnite Kernel for Visual
-Tracking and Recognition
-Stephan Liwicki, Student Member, IEEE, Stefanos Zafeiriou, Member, IEEE,
-Georgios Tzimiropoulos, Member, IEEE, and Maja Pantic, Fellow, IEEE"
 f7ecc9df67e9d33543c68fb150270e9f7af8814a,Joint Epipolar Tracking (JET): Simultaneous Optimization of Epipolar Geometry and Feature Correspondences,"Simultaneous optimization of epipolar geometry and feature correspondences
 Joint Epipolar Tracking (JET):
 Henry Bradler1, Matthias Ochs1, Nolang Fanani1
@@ -70560,22 +59600,6 @@ Goethe University, Frankfurt, Germany
 Rudolf Mester1,2
 Computer Vision Laboratory, ISY
 Link¨oping University, Sweden"
-f7c9bafc66dc8d8002cbb2ea926378bce2b3b251,Emotion Detection Using EEG Signal Analysis ‘ Review ’,"International Journal of Electronics Communication and Computer Technology (IJECCT)
-Volume 5 Issue 2 (March 2015)
-Emotion Detection Using EEG Signal Analysis
-‘Review’
-K.S. Bhagat
-Assistant Professor,
-Dr. P.M. Mahajan
-Assistant Professo,
-Gunjal P. Waghulade
-M.E. IVth Semester,
-J.T. Mahajan College of ngineering,
-J.T. Mahajan College of ngineering,
-J.T. Mahajan College of ngineering,
-Faizpur, India
-Faizpur, India
-Faizpur, India"
 f7186eb3d717694d4ab1730a8d0f662e90c44d6f,A Computational Study on Word Meanings and Their Distributed Representations via Polymodal Embedding,"Proceedings of the The 8th International Joint Conference on Natural Language Processing, pages 214–223,
 Taipei, Taiwan, November 27 – December 1, 2017 c(cid:13)2017 AFNLP"
 f795b4ff67d3ecce0b988ecfc0589cc7e54f5dfa,Grounded Human-Object Interaction Hotspots from Video,"Grounded Human-Object Interaction Hotspots from Video
@@ -70588,25 +59612,6 @@ Facebook AI Research"
 f77c9bf5beec7c975584e8087aae8d679664a1eb,Local Deep Neural Networks for Age and Gender Classification,"Local Deep Neural Networks for Age and Gender Classiﬁcation
 Zukang Liao, Stavros Petridis, Maja Pantic
 March 27, 2017"
-f75852386e563ca580a48b18420e446be45fcf8d,ILLUMINATION INVARIANT FACE RECOGNITION,"ILLUMINATION INVARIANT FACE RECOGNITION
-Raghuraman Gopalan
-ENEE 631: Digital Image and Video Processing
-Instructor: Dr. K. J. Ray Liu
-Term Project - Spring 2006
-INTRODUCTION
-The  performance  of  the  Face  Recognition  algorithms  is  severely  affected  by  two
-important  factors:  the  change  in  Pose  and  Illumination  conditions  of  the  subjects.  The
-hanges in Illumination conditions of the subjects can be so drastic that, the variation in
-lighting will be of the similar order as that of the variation due to the change in subjects
-[1] and this can result in misclassification.
-For example, in the acquisition of the face of a person from a real time video, the
-mbient  conditions  will  cause  different  lighting  variations  on  the  tracked  face.  Some
-examples  of  images  with  different  illumination  conditions  are  shown  in  Fig.  1.  In  this
-project, we study some algorithms that are capable of performing Illumination Invariant
-Face Recognition. The performances of these algorithms were compared on the CMU-
-Illumination dataset [13], by using the entire face as the input to the algorithms. Then, a
-model  of  dividing  the  face  into  four  regions  is  proposed  and  the  performance  of  the
-lgorithms on these new features is analyzed."
 f774f80fa4b5a8760084921f093730da519c6681,Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms,"Development of an Efficient Face Recognition System based on Linear and Nonlinear Algorithms
 {tag}                                                 {/tag}
 International Journal of Computer Applications
@@ -70716,11 +59721,6 @@ Bruce Hwy
 North Rockhampton
 QLD 4701
 Australia"
-f727837e03a039d9bcec6d02cd87256f5a5854a4,"Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning","Deep Convolutional Neural Networks for
-Computer-Aided Detection: CNN Architectures,
-Dataset Characteristics and Transfer Learning
-Hoo-Chang Shin, Member, IEEE, Holger R. Roth, Mingchen Gao, Le Lu, Senior Member, IEEE, Ziyue Xu,
-Isabella Nogues, Jianhua Yao, Daniel Mollura, Ronald M. Summers*"
 64b78b6f13c321da77e3770a748772fa837aa8c8,Parallel Architecture for Face Recognition using MPI,"(IJACSA) International Journal of Advanced Computer Science and Applications,
 Vol. 8, No. 1, 2017
 Parallel Architecture for Face Recognition using MPI
@@ -70814,13 +59814,6 @@ Ramazan Gokberk Cinbis
 Jakob Verbeek Cordelia Schmid
 LEAR, INRIA Grenoble - Rhˆone-Alpes, France
 Laboratoire Jean Kuntzmann"
-6412d8bbcc01f595a2982d6141e4b93e7e982d0f,"Deep Convolutional Neural Network Using Triplets of Faces, Deep Ensemble, and Score-Level Fusion for Face Recognition","Deep Convolutional Neural Network using Triplets of Faces, Deep Ensemble, and
-Score-level Fusion for Face Recognition
-Bong-Nam Kang, Student Member, IEEE1, Yonghyun Kim, Student Member, IEEE2, and
-Daijin Kim, Member, IEEE2
-Department of Creative IT Engineering, POSTECH, Korea
-Department of Computer Science and Engineering, POSTECH, Korea
-{bnkang, gkyh0805,"
 6475c1e95da0a3bd36786a32d00a893d85460e9e,Combined image- and world-space tracking in traffic scenes,"Combined Image- and World-Space Tracking in Trafﬁc Scenes
 Aljoˇsa Oˇsep, Wolfgang Mehner, Markus Mathias, and Bastian Leibe"
 64d1fcc26c2af47c8ed7436fe91546ba5bfc7a1f,Disentangling Multiple Conditional Inputs in GANs,"Disentangling Multiple Conditional Inputs in GANs
@@ -70848,12 +59841,6 @@ Random Variables Observed on a Lattice Graph
 T. Tony Cai∗ and Ming Yuan†
 University of Pennsylvania and Georgia Institute of Technology
 November 3, 2012"
-6403117f9c005ae81f1e8e6d1302f4a045e3d99d,"A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets.","A Systematic Evaluation and Benchmark for
-Person Re-Identiﬁcation: Features, Metrics, and
-Datasets
-Srikrishna Karanam∗, Student Member, IEEE, Mengran Gou∗, Student Member, IEEE,
-Ziyan Wu, Member, IEEE, Angels Rates-Borras, Octavia Camps, Member, IEEE,
-nd Richard J. Radke, Senior Member, IEEE"
 641fd2edcf93fa29181952356e93a83a26012aa2,Following are some examples from CIFAR dataset : Goal : To alter the training criteria to obtain ‘ objectness ’ in the synthesis of images,"Published as a conference paper at ICLR 2017
 IMPROVING GENERATIVE ADVERSARIAL NETWORKS
 WITH DENOISING FEATURE MATCHING
@@ -70962,11 +59949,6 @@ EPFL, Switzerland
 Universidad Rey Juan Carlos, Spain"
 6497eb53fd7d3ff09190566be8099016fb49f801,Biometric Sensor Interoperability: A Case Study in 3D Face Recognition,
 64a336f952ec67f85fe00092847d50dd29e4cddc,Fast Screening Algorithm for Template Matching FAST SCREENING ALGORITHM FOR TEMPLATE MATCHING,Fast Screening Algorithm for Template Matching
-641f9c87356c0829e690272b010848242058b8bc,Object Co-Detection via Efficient Inference in a Fully-Connected CRF,"Object Co-detection via Ef‌f‌icient Inference
-in a Fully-Connected CRF(cid:2)
-Zeeshan Hayder, Mathieu Salzmann, and Xuming He
-Australian National University (ANU)
-NICTA, Canberra, Australia"
 64cac22210861d4e9afb00b781da90cf99f9d19c,Facial Landmark Detection for Manga Images,"Noname manuscript No.
 (will be inserted by the editor)
 Facial Landmark Detection for Manga Images
@@ -71052,10 +60034,6 @@ SyedA.Rizviy
 StateUniversityofNewYorkatBu(cid:11)alo,Amherst,NY
 DepartmentofAppliedSciences
 CollegeofStatenIslandofCityUniversityofNewYork,StatenIsland,NY
-0f112e49240f67a2bd5aaf46f74a924129f03912,Age-Invariant Face Recognition,"Age-Invariant Face Recognition
-Unsang Park, Member, IEEE,
-Yiying Tong, Member, IEEE, and
-Anil K. Jain, Fellow, IEEE"
 0fe5d8acc77f54d60edc56c012f35517d9c861da,Interactive Stereoscopic Video Conversion,"Interactive Stereoscopic Video Conversion
 Zhebin Zhang, Chen Zhou, Yizhou Wang, and Wen Gao, Fellow, IEEE
 erial perspective,"
@@ -71220,13 +60198,6 @@ Pietro Morerio, Lucio Marcenaro, Carlo S. Regazzoni
 Department of Biophysical and Electronic Engineering
 University of Genoa, Genoa, Italy"
 0f41f1a4bd5141184ee3ed3cf8874eeb396d7862,Deep Forest: Towards An Alternative to Deep Neural Networks,Proceedings of the Twenty-Sixth International Joint Conference on Artiﬁcial Intelligence (IJCAI-17)
-0fafbeedc41f5e31f81c91f56eca448cc29e1701,Real-Time Pedestrian Detection System,"International Journal of Science and Research (IJSR)
-ISSN (Online): 2319-7064
-Index Copernicus Value (2013): 6.14 | Impact Factor (2013): 4.438
-Real-Time Pedestrian Detection System
-Tinto Raj R V1, Surya Priya .S2
-P.G scholar, Department of CSE, Sarabhai Institute of Science & technology, Kerala, India
-Assistant Professor, Department of CSE, Sarabhai Institute of Science & technology, Kerala, India"
 0f92e9121e9c0addc35eedbbd25d0a1faf3ab529,MORPH-II : A Proposed Subsetting Scheme,"MORPH-II: A Proposed Subsetting Scheme
 Participants: K. Kempfert, J. Fabish, K. Park, and R. Towner
 Mentors: Y. Wang, C. Chen, and T. Kling
@@ -71234,9 +60205,6 @@ NSF-REU Site at UNC Wilmington, Summer 2017"
 0fd1bffb171699a968c700f206665b2f8837d953,Weakly Supervised Object Localization with Multi-Fold Multiple Instance Learning,"Weakly Supervised Object Localization with
 Multi-fold Multiple Instance Learning
 Ramazan Gokberk Cinbis, Jakob Verbeek, and Cordelia Schmid, Fellow, IEEE"
-0fcda01765c5a0b4cff99b5ed5139a6e1eddb689,Exploiting Long-Term Connectivity and Visual Motion in CRF-Based Multi-Person Tracking,"Exploiting Long-Term Connectivity and Visual
-Motion in CRF-Based Multi-Person Tracking
-Alexandre Heili, Student Member, IEEE, Adolfo López-Méndez, and Jean-Marc Odobez, Member, IEEE"
 0ff23392e1cb62a600d10bb462d7a1f171f579d0,Toward Sparse Coding on Cosine Distance,"Toward	Sparse	Coding	on	Cosine
 Distance
 Jonghyun	Choi,	Hyunjong	Cho,	Jungsuk	Kwak#,
@@ -71275,26 +60243,6 @@ Tayyab Naseer
 Gabriel L. Oliveira
 Thomas Brox
 Wolfram Burgard"
-0f395a49ff6cbc7e796656040dbf446a40e300aa,The Change of Expression Configuration Affects Identity-Dependent Expression Aftereffect but Not Identity-Independent Expression Aftereffect,"ORIGINAL RESEARCH
-published: 22 December 2015
-doi: 10.3389/fpsyg.2015.01937
-The Change of Expression
-Conﬁguration Affects
-Identity-Dependent Expression
-Aftereffect but Not
-Identity-Independent Expression
-Aftereffect
-Miao Song 1, 2*, Keizo Shinomori 2, Qian Qian 3, Jun Yin 1 and Weiming Zeng 1
-College of Information Engineering, Shanghai Maritime University, Shanghai, China, 2 School of Information, Kochi University
-of Technology, Kochi, Japan, 3 Yunnan Key Laboratory of Computer Technology Applications, Kunming University of Science
-nd Technology, Kunming, China
-The present study examined the influence of expression conﬁguration on cross-identity
-expression aftereffect. The expression conﬁguration refers to the spatial arrangement
-of facial features in a face for conveying an emotion, e.g., an open-mouth smile vs.
-closed-mouth smile. In the ﬁrst of two experiments, the expression aftereffect is
-measured using a cross-identity/cross-expression conﬁguration factorial design. The
-facial
-identities of test faces were the same or different from the adaptor, while"
 0ff14ec76e5fe7f17dce102e781ffce2738c8d4b,Real-time pedestrian detection in urban scenarios,"Real-time Pedestrian Detection in Urban Scenarios
 VARGA Robert, VESA Andreea Valeria, JEONG Pangyu, NEDEVSCHI Sergiu
 {robert.varga, pangyu.jeong,
@@ -71374,12 +60322,6 @@ Alberto Sanfeliu, and Juan Andrade-Cetto
 Institut de Rob`otica i Inform`atica Industrial, CSIC-UPC
 Llorens Artigas 4-6, 08028 Barcelona, Spain.
 http://www.iri.upc.edu"
-0f07dcf92588945eb0d70893cdf0fe4a48552763,Detection- and Trajectory-Level Exclusion in Multiple Object Tracking,"Detection- and Trajectory-Level Exclusion in Multiple Object Tracking
-Anton Milan1
-Konrad Schindler2
-Stefan Roth1
-Department of Computer Science, TU Darmstadt
-Photogrammetry and Remote Sensing Group, ETH Z¨urich"
 0fb75f5cb12d1e1a909b9f698b7617bb9603002f,Design of Weight-Learning Efficient Convolutional Modules in Deep Convolutional Neural Networks and its Application to Large-Scale Visual Recognition Tasks,"Data Analysis Project
 Design of Weight-Learning Ef‌f‌icient Convolutional Modules in Deep
 Convolutional Neural Networks and its Application to
@@ -71398,14 +60340,6 @@ Krzysztof Czarnecki∗
 Vahdat Abdelzad∗
 Taylor Denouden†
 Sachin Vernekar†"
-2465fc22e03faf030e5a319479a95ef1dfc46e14,Influence of different feature selection approaches on the performance of emotion recognition methods based on SVM,"______________________________________________________PROCEEDING OF THE 20TH CONFERENCE OF FRUCT ASSOCIATION
-Influence of Different Feature Selection Approaches
-on the Performance of Emotion Recognition
-Methods Based on SVM
-Daniil Belkov, Konstantin Purtov, Vladimir Kublanov
-Ural Federal University (UrFU)
-Yekaterinburg, Russia
-d.d.belkov,"
 24ff832171cb774087a614152c21f54589bf7523,Beat-Event Detection in Action Movie Franchises,"Beat-Event Detection in Action Movie Franchises
 Danila Potapov
 Matthijs Douze
@@ -71564,10 +60498,6 @@ nd Landmarking on 3D Meshes
 Clement Creusot · Nick Pears · Jim Austin
 Received: 14 October 2011 / Accepted: 17 December 2012
 © Springer Science+Business Media New York 2013"
-244377600b1474e1da3b86a08683e629990d1417,Embedded Vision System for Atmospheric Turbulence Mitigation,"Embedded Vision System for Atmospheric Turbulence Mitigation
-Ajinkya Deshmukh1, Gaurav Bhosale, Swarup Medasani2, Karthik Reddy,
-Hemanthakumar P, Chandrasekhar A, Kirankumar P, Vijayasagar K
-Uurmi Systems Pvt. Ltd., Hyderabad, India"
 2491203e3b268235ea0269f41dbebd113d2a1b0a,"Optimal multiplexed sensing: bounds, conditions and a graph theory link.","Optimal multiplexed sensing: bounds,
 onditions and a graph theory link
 Netanel Ratner,1 Yoav Y. Schechner,1,∗
@@ -71591,11 +60521,6 @@ Sydney Cash1,2       Brandon Westover1,3
 Massachusetts General Hospital, 2Harvard Medical School, 3Brigham and Women's Hospital
 University of California – Riverside
 {mueen, eamonn,"
-2485c98aa44131d1a2f7d1355b1e372f2bb148ad,The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations,"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART A: SYSTEMS AND HUMANS, VOL. 38, NO. 1, JANUARY 2008
-The CAS-PEAL Large-Scale Chinese Face
-Database and Baseline Evaluations
-Wen Gao, Senior Member, IEEE, Bo Cao, Shiguang Shan, Member, IEEE,
-Xilin Chen, Member, IEEE, Delong Zhou, Xiaohua Zhang, and Debin Zhao"
 24ff2797234e26bb2ffd4558eb4412df0625687e,Mind Your Language: Abuse and Offense Detection for Code-Switched Languages,"Mind Your Language: Abuse and Offense Detection for Code-Switched Languages
 Raghav Kapoor
 MIDAS Lab, NSIT-Delhi
@@ -71609,13 +60534,6 @@ Ponnurangam Kumaraguru
 IIIT, Delhi
 Roger Zimmermann
 NUS, Singapore"
-2400543ba5a94e2723bc5296e9e5f2a280f0adbd,Face Recogition by Using Gabor Feature Extraction and Neural Networks,"IOSR Journal of Electronics and Communication Engineering (IOSR-JECE)
-e-ISSN: 2278-2834,p- ISSN: 2278-8735.Volume 10, Issue 2, Ver. II (Mar - Apr.2015), PP 68-72
-www.iosrjournals.org
-Face Recogition by Using Gabor Feature Extraction and Neural
-Networks
-B.Gopika, K.Srilaxmi, D.Alekhya, B.Bhaskar Rao, B.Rama Mohan
-,2,3,4,5, (ECE, Lendi Institute of Engineering And Technology, India,"
 2475ad865b2102cef83a87adfe0d2e71d4791e53,A Supervised Clustering Algorithm for the Initialization of RBF Neural Network Classifiers,"A Supervised Clustering Algorithm for the Initialization
 of RBF Neural Network Classifiers
 Hakan Cevikalp, Diane Larlus, Frédéric Jurie
@@ -71649,25 +60567,6 @@ Face Recognition: Effects of Similarity Measure
 Arjun V Mane#1, Ramesh R Manza#2, Karbhari V Kale#3
 #Department of Computer Science & Information Technology,
 Dr. Babasaheb Ambedkar Marathwada University, Aurangabad (MS) India"
-24041477d6e412e4afc441992f4b170831f725c7,International Journal of Advance Research in Computer Science and Management Studies,"Volume 3, Issue 10, October 2015
-International Journal of Advance Research in
-Computer Science and Management Studies
-Research Article / Survey Paper / Case Study
-Available online at: www.ijarcsms.com
-ISSN: 2321-7782 (Online)
-Automatic Face Naming by Using Fused Affinity Matrix
-Kadam Vaibhav Bharat1
-B.E. Computer Science
-Deshpande Supriya Ajay2
-B.E. Computer Science
-Alarm College of Engineering, Pune, India
-Alarm College of Engineering, Pune, India
-Malpure Sagar3
-B.E. Computer Science
-Choudhary Jitendra4
-B.E. Computer Science
-Alarm College of Engineering, Pune, India
-Alarm College of Engineering, Pune, India"
 24e98b70dc6982af2dd3a5bb4e501cc1b61f7d2b,LCR-Net++: Multi-person 2D and 3D Pose Detection in Natural Images,"SUBMITTED TO IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2018
 LCR-Net++: Multi-person 2D and 3D Pose
 Detection in Natural Images
@@ -71678,25 +60577,6 @@ Mohammad Rastegari, Shobeir Fakhraei,
 Jonghyun Choi, David Jacobs, Larry S. Davis
 mrastega,shobeir
 jhchoi,djacobs,lsd"
-244a6d4f5f745f8c2a58a6a70d7ba2b91300c118,RADON Transform and PCA based 3 D Face Recognition using KNN and SVM,"International Journal of Computer Applications (0975 – 8887)
-Recent Advances in Information Technology, 2014
-RADON Transform and PCA based 3D Face Recognition
-using KNN and SVM
-P. S. Hiremath
-Department of Computer Science
-Gulbarga University
-Gulbarga, KA, India
-Manjunatha Hiremath
-Department of Computer Science
-Gulbarga University
-Gulbarga, KA, India
-integral
-researches
-society.Many"
-2475d216fd52994ac69ef922f4daf73e47f9535d,Joint Albedo Estimation and Pose Tracking from Video,"Joint Albedo Estimation and Pose Tracking
-from Video
-Sima Taheri, Student Member, IEEE, Aswin Sankaranarayanan, Member, IEEE,
-nd Rama Chellappa, Fellow, IEEE"
 242ae7b1b1c3e1aafcbe9cef3cb23918c6f94f2c,Performance Evaluation of Biometric Template Update,"Performance Evaluation
 of Biometric Template Update
 Romain Giot and Christophe Rosenberger
@@ -71796,11 +60676,6 @@ http://qmro.qmul.ac.uk/xmlui/handle/123456789/22467
 Information about this research object was correct at the time of download; we occasionally
 make corrections to records, please therefore check the published record when citing. For
 more information contact"
-2484a34597a40d846c084e827fda299fd0927008,Image Matching Algorithm based on Feature-point and DAISY Descriptor,"Image Matching Algorithm based on
-Feature-point and DAISY Descriptor
-School of Business, Sichuan Agricultural University, Sichuan Dujianyan 611830, China
-Li Li
-is  the  research"
 5ecf564bc9eab26c96c17304744ff1029215a109,Single-Sample Face Recognition Based on Intra-Class Differences in a Variation Model,"Sensors 2015, 15, 1071-1087; doi:10.3390/s150101071
 OPEN ACCESS
 sensors
@@ -71819,14 +60694,6 @@ Received: 17 September 2014 / Accepted: 10 December 2014 / Published: 8 January
 5e0832848fab012b7e59580264257e0a3d05c596,The University of Southampton Multi-Biometric Tunnel and introducing a novel 3 D gait dataset Richard,"The University of Southampton Multi-Biometric Tunnel and
 introducing a novel 3D gait dataset
 Richard D. Seely, Sina Samangooei, Lee Middleton, John N. Carter and Mark S. Nixon"
-5e0df06d92176f362d52962de866e2d825185afb,Improving Multi-frame Data Association with Sparse Representations for Robust Near-online Multi-object Tracking,"Improving Multi-Frame Data Association with
-Sparse Representations for Robust Near-Online
-Multi-Object Tracking
-Lo¨ıc Fagot-Bouquet1, Romaric Audigier1, Yoann Dhome1, Fr´ed´eric Lerasle2,3
-CEA, LIST, Vision and Content Engineering Laboratory,
-Point Courrier 173, F-91191 Gif-sur-Yvette, France
-CNRS, LAAS, 7, Avenue du Colonel Roche, F-31400 Toulouse, France
-Universit´e de Toulouse, UPS, LAAS, F-31400 Toulouse, France"
 5ee220b6fb70a3d4d99be9d81d2c0e5de06ab3b9,LoST? Appearance-Invariant Place Recognition for Opposite Viewpoints using Visual Semantics,"Pre-print of article that will appear in Proceedings of Robotics: Science and Systems XIV, 2018.Please cite this paper as:Sourav Garg, Niko Sunderhauf, and Michael Milford. LoST? Appearance-Invariant Place Recognition for Opposite Viewpoints using Visual Semantics. Proceedings of Robotics: Science and Systems XIV,  title={LoST? Appearance-Invariant Place Recognition for Opposite Viewpoints using Visual Semantics},  author={Garg, Sourav and Suenderhauf, Niko and Milford, Michael},  journal={Proceedings of Robotics: Science and Systems XIV},  year={2018}}"
 5e9a6357fd7de7271dac77756c3992dce260eb49,ON THE CONVERGENCE OF AFFECTIVE AND PERSUASIVE TECHNOLOGIES IN COMPUTER-MEDIATED HEALTH-CARE SYSTEMS,"Rebeca I. García-Betances
 Life Supporting Technologies (LifeSTech)
@@ -71882,18 +60749,6 @@ Irene Kotsiay, Stefanos Zafeiriouy, Nikolaos Nikolaidisy and Ioannis Pitasy
 yAristotle University of Thessaloniki, Department of Informatics
 Thessaloniki, Greece
 email: fekotsia, dralbert, nikolaid,"
-5e5e11e143140cc376db466d5b096a54b900c2ba,Face Recognition in Uncontrolled Environment,"(IJACSA) International Journal of Advanced Computer Science and Applications,
-Vol. 7, No. 8, 2016
-Face Recognition in Uncontrolled Environment
-Radhey Shyam and Yogendra Narain Singh
-Department of Computer Science & Engineering
-Institute of Engineering and Technology
-Lucknow - 226 021, India"
-5ebd9457a3a09889fad8cc86a91b274da5986636,oASIS: Adaptive Column Sampling for Kernel Matrix Approximation,"PATEL et al.: OASIS: ADAPTIVE COLUMN SAMPLING FOR KERNEL MATRIX APPROXIMATION
-oASIS: Adaptive Column Sampling
-for Kernel Matrix Approximation
-Raajen Patel*, Student Member, IEEE, Thomas A. Goldstein, Member, IEEE, Eva L. Dyer, Member, IEEE,
-Azalia Mirhoseini, Student Member, IEEE, and Richard G. Baraniuk, Fellow, IEEE"
 5e39deb4bff7b887c8f3a44dfe1352fbcde8a0bd,Supervised COSMOS Autoencoder: Learning Beyond the Euclidean Loss!,"Supervised COSMOS Autoencoder: Learning Beyond the
 Euclidean Loss!
 Maneet Singh, Student Member, IEEE, Shruti Nagpal, Student Member, IEEE, Mayank Vatsa, Senior Member, IEEE,
@@ -71942,13 +60797,6 @@ Screening Guidelines
 Clinical & Research Criteria
 Increased Prevalence of Autism
 It’s not the vaccine"
-5e2b918f2dee17cb79d692e10aa2103ca9129e2c,Rotating your face using multi-task deep neural network,"Rotating Your Face Using Multi-task Deep Neural Network
-Junho Yim1 Heechul Jung1 ByungIn Yoo1;2 Changkyu Choi2 Dusik Park2
-Junmo Kim1
-School of Electrical Engineering, KAIST, South Korea
-Samsung Advanced Institute of Technology
-fjunho.yim, heechul,
-fbyungin.yoo, changkyu choi,"
 5eac16cf7551d2968bc2d73200883dca0b5f7f13,Combining complementary kernels in complex visual categorization,"Combining complementary kernels in complex visual categorization
 Nicolas Thome1, David Picard2 and Matthieu Cord1
 LIP6 UPMC Paris 6
@@ -72350,11 +61198,6 @@ Semantic-Aware Image Smoothing
 Weihao Li1,2, Omid Hosseini Jafari1,2, and Carsten Rother1,2
 Computer Vision Lab, TU Dresden, Germany
 Visual Learning Lab, Heidelberg University, Germany"
-6cacda04a541d251e8221d70ac61fda88fb61a70,One-shot Face Recognition by Promoting Underrepresented Classes,"One-shot Face Recognition by Promoting Underrepresented Classes
-Yandong Guo, Lei Zhang
-Microsoft
-One Microsoft Way, Redmond, Washington, United States
-{yandong.guo,"
 6cad008ad80081dc42752e813ee6924e3c174dc7,Does Facial Resemblance Enhance Cooperation?,"Does Facial Resemblance Enhance Cooperation?
 Trang Giang*, Raoul Bell*, Axel Buchner
 Department of Experimental Psychology, Heinrich Heine University Du¨ sseldorf, Du¨ sseldorf, Germany"
@@ -72379,17 +61222,6 @@ Erster Gutachter:
 Prof. Dr. A. Waibel
 Zweiter Gutachter:
 Prof. Dr. J. Kittler"
-6cd497a9a66daa2d0c867dc07412d958791f3499,Speeding Up Permutation Based Indexing with Indexing,"Speeding Up Permutation Based Indexing with Indexing
-Karina Figueroa
-Facultad de Ciencias F´ısico-Matem´aticas
-Universidad Michoacana
-Mexico
-Kimmo Fredriksson
-Department of Computer Science
-University of Kuopio
-Finland
-Email:
-Email:"
 6cd762e7cb1301abd0ddbb265dd9c7661ffc0458,On optimal low rank Tucker approximation for tensors: the case for an adjustable core size,"On Optimal Low Rank Tucker Approximation for Tensors:
 The Case for an Adjustable Core Size
 Bilian CHEN ∗
@@ -72434,10 +61266,6 @@ Universidad de Las Palmas de Gran Canaria
 Photo Filter Recommendation
 y Category-Aware Aesthetic Learning
 Wei-Tse Sun, Ting-Hsuan Chao, Yin-Hsi Kuo, Winston H. Hsu"
-6c62330cbd60f2cb6cb80b920104d0df3116cb3f,Robust People Tracking Using A Light Coding Depth Sensor,"Robust People Tracking Using A Light Coding Depth Sensor
-Xun Changqing1, Yang Shuqiang2, and Zhang Chunyuan1
-College of Computer, National University of Defence Technology, ChangSha, China
-College of Electronic Science and Engineering, National University of Defence Technology, ChangSha, China"
 6cefb70f4668ee6c0bf0c18ea36fd49dd60e8365,Privacy-Preserving Deep Inference for Rich User Data on The Cloud,"Privacy-Preserving Deep Inference for Rich User
 Data on The Cloud
 Seyed Ali Osia ♯, Ali Shahin Shamsabadi ♯, Ali Taheri ♯, Kleomenis Katevas ⋆,
@@ -72654,12 +61482,6 @@ Jonathan Huang
 Google Inc.
 Kevin Murphy
 Google Inc."
-053ff27aba868c64823dbbe2167a762dd3f33b53,Probabilistic Slow Features for Behavior Analysis,"This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination.
-Probabilistic Slow Features for Behavior Analysis
-Lazaros Zafeiriou, Student Member, IEEE, Mihalis A. Nicolaou, Member, IEEE,
-Stefanos Zafeiriou, Member, IEEE, Symeon Nikitidis,
-nd Maja Pantic, Fellow, IEEE
-feature"
 05ce73c39368aca1d10ab48dbe0dee80ee084bdb,M ULTI-LABEL L EARNING WITH THE RNN S FOR F ASHION S EARCH,"Under review as a conference paper at ICLR 2017
 MULTI-LABEL LEARNING WITH THE RNNS
 FOR FASHION SEARCH
@@ -72689,12 +61511,6 @@ Søren Hauberg, Aasa Feragen, Rafﬁ Enﬁciaud, and Michael J. Black"
 05ad478ca69b935c1bba755ac1a2a90be6679129,Attribute Dominance: What Pops Out?,"Attribute Dominance: What Pops Out?
 Naman Turakhia
 Georgia Tech"
-05469df372a567dcef62b7ba447685fd5a5efb80,DeepSpace: An Online Deep Learning Framework for Mobile Big Data to Understand Human Mobility Patterns,"JOURNAL OF LATEX CLASS FILES, VOL. 13, NO. 9, SEPTEMBER 2014
-DeepSpace: An Online Deep Learning
-Framework for Mobile Big Data to Understand
-Human Mobility Patterns
-Xi Ouyang, Student Member, IEEE, Chaoyun Zhang†, Student Member, IEEE, Pan Zhou, Member, IEEE
-nd Hao Jiang, Member, IEEE"
 050a149051a5d268fcc5539e8b654c2240070c82,Magisterské a doktorské studijnı́ programy,MAGISTERSKÉ A DOKTORSKÉSTUDIJNÍ PROGRAMY31. 5. 2018SBORNÍKSTUDENTSKÁ VĚDECKÁ KONFERENCE
 052880031be0a760a5b606b2ad3d22f237e8af70,Datasets on object manipulation and interaction: a survey,"Datasets on object manipulation and interaction: a survey
 Yongqiang Huang and Yu Sun"
@@ -72779,42 +61595,6 @@ Numbers displayed above are based on latest data collected."
 Reinhard Heckel and Helmut B¨olcskei
 Dept. of IT & EE, ETH Zurich, Switzerland
 July 2013; last revised August 2015"
-0569d7d3d8f96140adc8ec5a6016fdc97e7ef8aa,Random tree walk toward instantaneous 3D human pose estimation,"Random Tree Walk toward Instantaneous 3D Human Pose Estimation
-Ho Yub Jung1, Soochahn Lee2, Yong Seok Heo3, Il Dong Yun1
-Div. of Comp. & Elect. Sys. Eng., Hankuk University of Foreign Studies. 2Dept. of Elect. Eng., Soonchunghyang University. 3Dept. of Elect. & Comp. Eng.,
-Ajou University.
-Figure 1: The red lines represents the random tree walks trained to ﬁnd
-the head position. The random walk starts from the body center in (a). In
-(b), the head position is found with fewer steps by starting from the chest,
-which is much closer than the body center. (c) illustrates the kinematic tree
-implemented along with RTW. The adjacent joint positions can be used as
-the starting positions for new RTW. (d) shows the RTW path examples.
-Figure 2: Example results of the RTW from EVAL db [1]. Proposed ap-
-proach achieves the state-of-the-art accuracy without using the temporal
-prior. 64 RTW steps are taken for each joint to estimate human pose from
-single depth image. The RTW paths are drawn, and the expectations of
-RTW steps are used to ﬁnd the joint positions. The pose estimation from a
-single frame takes less than 1 millisecond.
-The availability of accurate depth cameras have made real-time human
-pose estimation possible; however, there are still demands for faster algo-
-rithms on low power processors. This paper introduces 1000 frames per
-second pose estimation method on a single core 3.20 GHz CPU with no"
-05a6a40c840c069631a825509f3095697592e1c4,IAN: The Individual Aggregation Network for Person Search,"IAN: The Individual Aggregation Network for
-Person Search
-Jimin XIAO, Member, IEEE, Yanchun XIE, Tammam TILLO, Senior Member, IEEE, Kaizhu HUANG, Senior
-Member, IEEE, Yunchao WEI, Member, IEEE, Jiashi FENG"
-057d879fe2d6c40ef79fe901cc62625a3b2ea8ba,EgoSampling: Fast-forward and stereo for egocentric videos,"EgoSampling: Fast-Forward and Stereo for Egocentric Videos
-Yair Poleg
-Tavi Halperin
-The Hebrew University
-The Hebrew University
-Jerusalem, Israel
-Jerusalem, Israel
-Chetan Arora
-Delhi, India
-Shmuel Peleg
-The Hebrew University
-Jerusalem, Israel"
 050fdbd2e1aa8b1a09ed42b2e5cc24d4fe8c7371,Spatio-Temporal Scale Selection in Video Data,"Contents
 Scale Space and PDE Methods
 Spatio-Temporal Scale Selection in Video Data . . . . . . . . . . . . . . . . . . . . .
@@ -72836,15 +61616,6 @@ Combining Contrast Invariant L1 Data Fidelities with Nonlinear
 Spectral Image Decomposition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
 Leonie Zeune, Stephan A. van Gils, Leon W.M.M. Terstappen,"
 05e658fed4a1ce877199a4ce1a8f8cf6f449a890,Domain Transfer Learning for Object and Action Recognition,
-053c2f592a7f153e5f3746aa5ab58b62f2cf1d21,PERFORMANCE EVALUATION OF ILLUMINATION NORMALIZATION TECHNIQUES FOR FACE RECOGNITION,"International Journal of Research in
-Engineering & Technology (IJRET)
-ISSN 2321-8843
-Vol. 1, Issue 2, July 2013, 11-20
-© Impact Journals
-PERFORMANCE EVALUATION OF ILLUMINATION NORMALIZATION TECHNIQUES
-FOR FACE RECOGNITION
-A. P. C. SARATHA DEVI & V. MAHESH
-Department of Information Technology, PSG College of Technology, Coimbatore, Tamil Nadu, India"
 05ea7930ae26165e7e51ff11b91c7aa8d7722002,Learning And-Or Model to Represent Context and Occlusion for Car Detection and Viewpoint Estimation,"Learning And-Or Model to Represent Context and
 Occlusion for Car Detection and Viewpoint Estimation
 Tianfu Wu∗, Bo Li∗ and Song-Chun Zhu"
@@ -73010,22 +61781,6 @@ Doctor of Philosophy
 Department of Computer Science
 University of Shefﬁeld
 November 2013"
-edd28097745ade85c3acd1d8bcba0b17cccb682e,Title Multi-Object Classification and Unsupervised Scene Understanding Using Deep Learning Features and Latent Tree Probabilistic Models Permalink,"UC Irvine
-UC Irvine Previously Published Works
-Title
-Multi-Object Classification and Unsupervised Scene Understanding Using
-Deep Learning Features and Latent Tree Probabilistic Models
-Permalink
-https://escholarship.org/uc/item/21x3r1x0
-Authors
-Nimmagadda, T
-Anandkumar, A
-Publication Date
-017-03-02
-Peer reviewed
-eScholarship.org
-Powered by the California Digital Library
-University of California"
 eda20a2f33d0f6db44a2e7d060efad3caa6621e0,"Classification with Global, Local and Shared Features","Classiﬁcation with Global, Local and Shared
 Features
 Hakan Bilen1, Vinay P. Namboodiri2, Luc J. Van Gool1,3
@@ -73045,21 +61800,6 @@ Supervisor:
 Prof. Andrea Prati
 The Chair of the Doctoral Program:
 Prof. Fabio Peron"
-de48bb3a9974f6f1ed2aa36d066150015f9f8647,Ultrasound Image Despeckling using Local Binary Pattern Weighted Linear Filtering,"I.J. Information Technology and Computer Science, 2013, 06, 1-9
-Published Online May 2013 in MECS (http://www.mecs-press.org/)
-DOI: 10.5815/ijitcs.2013.06.01
-Ultrasound Image Despeckling using Local
-Binary Pattern Weighted Linear Filtering
-Digital Image Processing Lab, Dept. of Computer Applications, Cochin University of Science and Technology, Kerala,
-Simily Joseph, Kannan Balakrishnan
-E-mail: {simily.joseph,
-India
-M.R. Balachandran Nair
-Ernakulam Scan Center, Kerala, India
-E-mail:
-Reji Rajan Varghese
-Dept. of Biomedical Engineering, Co operative Medical College, Kerala, India
-E-mail:"
 de0eb358b890d92e8f67592c6e23f0e3b2ba3f66,Inference-Based Similarity Search in Randomized Montgomery Domains for Privacy-Preserving Biometric Identification,"ACCEPTED BY IEEE TRANS. PATTERN ANAL. AND MACH. INTELL.
 Inference-Based Similarity Search in
 Randomized Montgomery Domains for
@@ -73081,9 +61821,6 @@ Inffeldgasse 16/II, 8010 Graz, Austria
 Trˇzaˇska 25, SI-1001 Slovenia
 e-mail: {pmroth,
 {danijel.skocaj,"
-de398bd8b7b57a3362c0c677ba8bf9f1d8ade583,Hierarchical Bayesian Theme Models for Multipose Facial Expression Recognition,"Hierarchical Bayesian Theme Models for
-Multi-pose Facial Expression Recognition
-Qirong Mao, Member, IEEE, Qiyu Rao, Yongbin Yu, and Ming Dong*, Member, IEEE"
 de287480b9ab8dfab1c49e24e5517b0a3c55203b,A Tempt to Unify Heterogeneous Driving Databases using Traffic Primitives,"A Tempt to Unify Heterogeneous Driving Databases
 using Trafﬁc Primitives
 Jiacheng Zhu1,Wenshuo Wang1, Ding Zhao1,∗"
@@ -73096,26 +61833,6 @@ de55bfc96b027b3e2bd44baed656a3f563ff6e71,"Deep Feature Consistent Deep Image Tra
 Transformations: Downscaling, Decolorization and
 HDR Tone Mapping
 Xianxu Hou, Jiang Duan, and Guoping Qiu"
-de95fa1dd69a2d0d2b76539357062062f8b1e7b8,Face to Age,"Face to Age
-Project 1
-CS395T - Deep Learning Seminar
-Aishwarya Padmakumar, Ashish Bora, Amir Gholaminejad
-October 9, 2016
-A Century of Portraits is a dataset that contains frontal-facing American high school year-book photos
-with labels to indicate the years those photos were taken [2].
-In this project we train classiﬁers to
-predict the label, given the image. We used several Deep Neural Network architectures for this task,
-ll of which were ﬁnetuned with ImageNet pretraining. With VGGNet architecture, we demonstrate
-signiﬁcant improvements in classiﬁcation accuracy reporting test set accuracy of 67.59% and mean L1
-error, as compared to 11.31 % achieved by Ginosar et al. [2]. Further, we show some visualizations of
-the trained model to gain insights into the learned model. The code for this project can be found at
-https://github.com/AshishBora/face2year.
-Introduction
-Deep Neural networks have been central to large improvements in several visual learning tasks. Feature
-representations learned by deep convolutional neural networks for image classiﬁcation on large datasets
-such as ImageNet [1] have been repeatedly demonstrated to be useful for other tasks [6]. Several down-
-stream applications have also greatly beneﬁted from these representations, either when used directly
-[9, 10] or with appropriate ﬁnetuning [3, 5]."
 def3b2254caea169c5cbc4b771c44f1773c004fd,Matching Adversarial Networks,"Matching Adversarial Networks
 Gell´ert M´attyus and Raquel Urtasun
 Uber Advanced Technologies Group and University of Toronto"
@@ -73307,12 +62024,6 @@ vi	a
 66c792b7e9946f8cb92fac185267d03371437451,Adaptive Affinity Fields for Semantic Segmentation,"Adaptive Afﬁnity Fields for Semantic Segmentation
 Tsung-Wei Ke*, Jyh-Jing Hwang*, Ziwei Liu, and Stella X. Yu
 UC Berkeley / ICSI"
-66810438bfb52367e3f6f62c24f5bc127cf92e56,Face Recognition of Illumination Tolerance in 2 D Subspace Based on the Optimum Correlation Filter,"Face Recognition of Illumination Tolerance in 2D
-Subspace Based on the Optimum Correlation
-Filter
-Xu Yi
-Department of Information Engineering, Hunan Industry Polytechnic, Changsha, China
-images  will  be  tested  to  project"
 66a9935e958a779a3a2267c85ecb69fbbb75b8dc,Fast and Robust Fixed-Rank Matrix Recovery,"FAST AND ROBUST FIXED-RANK MATRIX RECOVERY
 Fast and Robust Fixed-Rank Matrix
 Recovery
@@ -73418,10 +62129,6 @@ ISSN(Online)  2093-7423
 Nearest-Neighbors Based Weighted Method for the BOVW Applied to
 Image Classification
 Mengxi Xu*,**, Quansen Sun†, Yingshu Lu*** and Chenming Shen**"
-661c16658db873efeee3621603fe6bd53eaffac1,LLE Score: A New Filter-Based Unsupervised Feature Selection Method Based on Nonlinear Manifold Embedding and Its Application to Image Recognition,"LLE score: a new ﬁlter-based unsupervised feature
-selection method based on nonlinear manifold
-embedding and its application to image recognition
-Chao Yao, Ya-Feng Liu, Member, IEEE, Bo Jiang, Jungong Han, and Junwei Han, Senior Member, IEEE."
 660c8a9fa166c1d81e65192e011eacfec208ec00,Discrimination of visual pedestrians data by combining projection and prediction learning,"Discrimination of visual pedestrians data by combining
 projection and prediction learning
 Mathieu Lefort, Alexander Gepperth
@@ -73501,9 +62208,6 @@ Web: www.gkmm.tu-darmstadt.de/rescue"
 Reconﬁgurable Inference With
 Bundle Representations
 Liang Lin, Yongyi Lu, Chenglong Li, Hui Cheng, and Wangmeng Zuo, Senior Member, IEEE"
-66dcc6771e35068a1ea2f6e6f4cdb9a40a4df450,A Linear Approximation to the chi^2 Kernel with Geometric Convergence,"A Linear Approximation to the χ2 Kernel with
-Geometric Convergence
-Fuxin Li, Member, IEEE, Guy Lebanon, Member, IEEE, and Cristian Sminchisescu, Member, IEEE"
 664ccdcc614a8ecfbfedadc7b42b9537fe43d3f1,Probabilistic integration of sparse audio-visual cues for identity tracking,"Probabilistic Integration of Sparse Audio-Visual Cues for
 Identity Tracking
 Keni Bernardin
@@ -73518,26 +62222,6 @@ Alex Waibel
 Universität Karlsruhe, ITI
 Am Fasanengarten 5
 76131, Karlsruhe, Germany"
-661da40b838806a7effcb42d63a9624fcd684976,An Illumination Invariant Accurate Face Recognition with Down Scaling of DCT Coefficients,"An Illumination Invariant Accurate
-Face Recognition with Down Scaling
-of DCT Coefﬁcients
-Virendra P. Vishwakarma, Sujata Pandey and M. N. Gupta
-Department of Computer Science and Engineering, Amity School of Engineering and Technology, New Delhi, India
-In this paper, a novel approach for illumination normal-
-ization under varying lighting conditions is presented.
-Our approach utilizes the fact that discrete cosine trans-
-form (DCT) low-frequency coefficients correspond to
-illumination variations in a digital image. Under varying
-illuminations, the images captured may have low con-
-trast; initially we apply histogram equalization on these
-for contrast stretching. Then the low-frequency DCT
-oefficients are scaled down to compensate the illumi-
-nation variations. The value of scaling down factor and
-the number of low-frequency DCT coefficients, which
-re to be rescaled, are obtained experimentally. The
-lassification is done using k−nearest neighbor classi-
-fication and nearest mean classification on the images
-obtained by inverse DCT on the processed coefficients."
 66837b29270f3e03df64941a081d70c687c7955c,ActionXPose: A Novel 2D Multi-view Pose-based Algorithm for Real-time Human Action Recognition,"ActionXPose: A Novel 2D Multi-view Pose-based
 Algorithm for Real-time Human Action Recognition
 Federico Angelini, Student Member, IEEE, Zeyu Fu, Student Member, IEEE, Yang Long, Senior Member, IEEE,
@@ -73550,10 +62234,6 @@ Genevieve Patterson · Chen Xu · Hang Su ·
 James Hays
 Received: 27 February 2013 / Accepted: 28 December 2013 / Published online: 18 January 2014
 © Springer Science+Business Media New York 2014"
-66719918aa6562d14ea53286bf248d6f1a7d6b14,Perceive Your Users in Depth: Learning Universal User Representations from Multiple E-commerce Tasks,"Perceive Your Users in Depth: Learning Universal User
-Representations from Multiple E-commerce Tasks
-Yabo Ni∗, Dan Ou∗, Shichen Liu, Xiang Li, Wenwu Ou, Anxiang Zeng, Luo Si
-Search Algorithm Team, Alibaba Group, Seattle & Hangzhou, China"
 660c6a47ea29de2b4f40ac942ba682954118722f,SUPER-RESOLUTION : LIMITS AND BEYOND,"Chapter 1
 SUPER-RESOLUTION: LIMITS AND BEYOND
 Simon Baker
@@ -73852,16 +62532,6 @@ Andrew Rabinovich
 MagicLeap Inc.
 Alexander C. Berg
 UNC Chapel Hill"
-1ae19084d2cd53c70d7e44d419df32560e417fb9,The Canadian experience using the expanded criteria donor classification for allocating deceased donor kidneys for transplantation,"Young et al. Canadian Journal of Kidney Health and Disease  (2016) 3:15
-DOI 10.1186/s40697-016-0106-9
-Open Access
-O R I G I N AL R ES EA R C H AR TI C L E
-The Canadian experience using the
-expanded criteria donor classification for
-llocating deceased donor kidneys for
-transplantation
-Ann Young1, Stephanie N. Dixon2, Greg A. Knoll2,3, Amit X. Garg2,4, Charmaine E. Lok1,2,6, Ngan N. Lam5
-nd S. Joseph Kim1,2,6*"
 1a54a8b0c7b3fc5a21c6d33656690585c46ca08b,Fast Feature Pyramids for Object Detection,"Fast Feature Pyramids for Object Detection
 Piotr Doll´ar, Ron Appel, Serge Belongie, and Pietro Perona"
 1afbca9f7011ec659db9cb3692cbab5b5e38499b,"A mixed bag of emotions: Model, predict, and transfer emotion distributions","Motivation
@@ -73904,16 +62574,6 @@ The version in the Kent Academic Repository may differ from the final published
 Users are advised to check http://kar.kent.ac.uk for the status of the paper. Users should always cite the
 published version of record.
 Enquiries"
-1a6d748365dbf3b17f2db371a30469478ee7b142,DeepID-Net: Object Detection with Deformable Part Based Convolutional Neural Networks,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TPAMI.2016.2587642, IEEE
-Transactions on Pattern Analysis and Machine Intelligence
-IEEE TRANSACTIONS PATTERN ANALYSIS AND MACHINE INTELLIGENCE
-DeepID-Net: Object Detection with Deformable
-Part Based Convolutional Neural Networks
-Wanli Ouyang*, Member, IEEE, Xingyu Zeng*, Student Member, IEEE,
-Xiaogang Wang, Member, IEEE,Shi Qiu Member, IEEE, Ping Luo, Member, IEEE,
-Yonglong Tian Student Member, IEEE, Hongsheng Li, Member, IEEE, Shuo Yang Student Member, IEEE,
-Zhe Wang, Student Member, IEEE, Hongyang Li, Kun Wang, Junjie Yan,
-Chen-Change Loy, Member, IEEE, Xiaoou Tang, Fellow, IEEE"
 1a219e7bcd8f30f886a1f24a8c05bc26bef83ff9,Crowd Counting with Density Adaption Networks,"Crowd Counting with Density Adaption Networks
 Li Wang, Weiyuan Shao, Yao Lu, Hao Ye, Jian Pu, Yingbin Zheng"
 1ad97cce5fa8e9c2e001f53f6f3202bddcefba22,Grassmann Averages for Scalable Robust PCA,"Grassmann Averages for Scalable Robust PCA
@@ -73945,16 +62605,6 @@ television services such as TV-Anytime andAlliance for Telecommunications Indust
 Interoperability Forum."
 1afe5d933b58b4dd982a559cc6ec1d17959239de,Enhanced canonical correlation analysis with local density for cross-domain visual classification,"978-1-5090-4117-6/17/$31.00 ©2017 IEEE
 ICASSP 2017"
-1a6c3c37c2e62b21ebc0f3533686dde4d0103b3f,Implementation of Partial Face Recognition using Directional Binary Code,"International Journal of Linguistics and Computational Applications (IJLCA)                          ISSN 2394-6385 (Print)
-Volume 4, Issue 1, January – March 2017                                                                                   ISSN 2394-6393 (Online)
-Implementation of Partial Face Recognition
-using Directional Binary Code
-N.Pavithra #1, A.Sivapriya*2, K.Hemalatha*3 , D.Lakshmi*4
-,2,3Final Year, Department of Computer Science and Engineering, PanimalarInstitute of Technology,
-Assistant Professor, Department of Computer Science and Engineering, PanimalarInstitute of Technology, Tamilnadu, India,
-faith
-is  proposed.  It
-face  alignment  and"
 1a7e385d2aa041ca8931784fb7664e9905194565,Chapter 2 Sentiment Analysis Using Social Multimedia,"Chapter 2
 Sentiment Analysis Using Social
 Multimedia
@@ -73981,9 +62631,6 @@ Yonghyun Kim1[0000−0003−0038−7850], Bong-Nam Kang2[0000−0002−6818−75
 nd Daijin Kim1[0000−0002−8046−8521]
 Department of Computer Science and Engineering, POSTECH, Korea
 Department of Creative IT Engineering, POSTECH, Korea"
-1a45ddaf43bcd49d261abb4a27977a952b5fff12,LDOP: Local Directional Order Pattern for Robust Face Retrieval,"LDOP: Local Directional Order Pattern for Robust
-Face Retrieval
-Shiv Ram Dubey, Member, IEEE, and Snehasis Mukherjee, Member, IEEE"
 1a41831a3d7b0e0df688fb6d4f861176cef97136,A Biological Model of Object Recognition with Feature Learning,"massachusetts institute of technology — artificial intelligence laboratory
 A Biological Model of Object
 Recognition with Feature Learning
@@ -74066,13 +62713,6 @@ Matthieu Cord
 LIP6, UPMC - Sorbonne University, Paris, France
 {Marc.Law, Nicolas.Thome,"
 0033e0ce8720f913761f9edb9a6c378eed8366a8,Interactive Object Retrieval using Interpretable Visual Models,"UNIVERSIT´EPARIS-SUD11Facult´edessciencesd’OrsayN◦Ordre:2011PA112054PHDTHESISInteractiveObjectRetrievalusingInterpretableVisualModelsSubmittedforthedegreeof“docteurensciences”oftheUniversityParis-Sud11Speciality:ComputerScienceByAhmedRebaiMay2011INRIAParis-Rocquencourt,ImediaTeamThesiscommittee:Reviewers:FredStentiford-Prof.atUniversityCollegeLondon(UK)SylviePhilipp-Foliguet-Prof.atUniversit´eCergy/Pontoise(FR)Director:NozhaBoujemaa-DirectoroftheINRIA-SaclayCenter(FR)Advisor:AlexisJoly-ResearcheratINRIA-Rocquencourt(FR)Examinator:MichelCrucianu-Prof.atCNAM(FR)President:Fran¸coisYvon-Prof.atUniversit´eParis-Sud11(FR)Copyrightc(cid:13)2011AhmedRebaiAllrightsreserved."
-00f1cccba86736cb6b6f39759ca6749f819252f0,Transfer Metric Learning for Kinship Verification with Locality-Constrained Sparse Features,"Transfer Metric Learning for Kinship
-Veriﬁcation with Locality-Constrained
-Sparse Features
-Yanli Zhang, Bo Ma(B), Lianghua Huang, and Hongwei Hu
-Beijing Laboratory of Intelligent Information Technology,
-School of Computer Science and Technology, Beijing Institute of Technology,
-Beijing, China"
 00d8f67ac0ea0bb2c9827b60e1f47c300346cd7a,Face recognition using color local binary pattern from mutually independent color channels,"Anbarjafari EURASIP Journal on Image and Video Processing 2013, 2013:6
 http://jivp.eurasipjournals.com/content/2013/1/6
 R ES EAR CH
@@ -74089,26 +62729,9 @@ Li-Jia Li2∗
 {zhou.ren, xiaoyu.wang, ning.zhang,
 Snap Inc.
 Google Inc."
-003afe78ec7989371f648fd8957a6ce79083cf11,SeaCLEF 2016: Object Proposal Classification for Fish Detection in Underwater Videos,"SeaCLEF 2016: Object proposal classiﬁcation for
-ﬁsh detection in underwater videos
-Jonas J¨ager1,2, Erik Rodner2, Joachim Denzler2, Viviane Wolff1, and Klaus
-Fricke-Neuderth1
-Department of Electrical Engineering and Information Technology,
-Fulda University of Applied Sciences, Germany
-Computer Vision Group, Friedrich Schiller University Jena, Germany"
 00d9d88bb1bdca35663946a76d807fff3dc1c15f,Subjects and Their Objects: Localizing Interactees for a Person-Centric View of Importance,"Subjects and Their Objects: Localizing Interactees for a
 Person-Centric View of Importance
 Chao-Yeh Chen · Kristen Grauman"
-00091891790ee77816ebd785d25900254e6986bd,Discriminative Robust Local Binary Pattern based Edge Texture Features for Object Recognition,"International Journal of Scientific Engineering and Research (IJSER)
-ISSN (Online): 2347-3878, Impact Factor (2014): 3.05
-www.ijser.in
-Discriminative Robust Local Binary Pattern based
-Edge Texture Features for Object Recognition
-Rasika Raikar1, Shivani Pandita2
-Dhole Patil College of Engineering, Wagholi, Pune, India
-Professor, Dhole Patil College of Engineering, Wagholi, Pune, India
-round
-each  point.  Various"
 0079d56c8e183ef36f876b84327b97ee9454825b,Scene Parsing by Weakly Supervised Learning with Image Descriptions,"Hierarchical Scene Parsing by Weakly
 Supervised Learning with Image Descriptions
 Ruimao Zhang, Liang Lin, Guangrun Wang, Meng Wang, and Wangmeng Zuo"
@@ -74121,13 +62744,6 @@ Xiaojun Chang, Feiping Nie, Zhigang Ma, and Yi Yang"
 0077cd8f97cafd2b389783858a6e4ab7887b0b6b,Face Image Reconstruction from Deep Templates,"MAI et al.: ON THE RECONSTRUCTION OF DEEP FACE TEMPLATES
 On the Reconstruction of Deep Face Templates
 Guangcan Mai, Kai Cao, Pong C. Yuen, Senior Member, IEEE, and Anil K. Jain, Life Fellow, IEEE"
-005c996a9059af96454c3d6f83338068d3608585,On Detection of Multiple Object Instances Using Hough Transforms,"On Detection of Multiple Object Instances using Hough Transforms
-Olga Barinova
-Moscow State University∗
-Victor Lempitsky
-University of Oxford∗
-Pushmeet Kohli
-Microsoft Research Cambridge"
 0089a590154694e0de340f357a022f6a38d60946,Speeding-up Object Detection Training for Robotics with FALKON,"Speeding-up Object Detection Training for Robotics with FALKON
 Elisa Maiettini1,2,3, Giulia Pasquale1,2, Lorenzo Rosasco2,3 and Lorenzo Natale1"
 0052de4885916cf6949a6904d02336e59d98544c,Generalized low rank approximations of matrices,"Machine Learning, 61, 167–191, 2005
@@ -74488,14 +63104,6 @@ o-state propagation,” in Proc. Int. Joint Conf. Neural Networks
 ility criteria for uncertain neutral systems with mixed delays,” Syst.
 Contr. Lett., vol. 51, no. 1, pp. 57–65, 2004.
 [29] ——, “Parameter-dependent Lyapunov functional for stability of time-"
-af9d41c598fc5ae57b20948cf664273da4664931,A comparison of crowd commotion measures from generative models,"A Comparison of Crowd Commotion Measures from Generative Models
-Sadegh Mohammadi
-Hamed Kiani
-Alessandro Perina
-Vittorio Murino
-Pattern Analysis and Computer Vision Department (PAVIS)
-Istituto Italiano di Tecnologia
-Genova, Italy"
 afb51f0e173cd9ab1d41075862945ae6bc593cde,Large databases of real and synthetic images for feature evaluation and prediction,"Large databases of real and synthetic images for
 feature evaluation and prediction
 Biliana K. Kaneva
@@ -74520,10 +63128,6 @@ afaa607aa9ad0e9dad0ce2fe5b031eb4e525cbd8,Towards an automatic face indexing syst
 Towards an Automatic Face Indexing System for Actor-based
 Video Services in an IPTV Environment
 Jae Young Choi, Wesley De Neve, and Yong Man Ro, Senior Member, IEEE"
-af95ba2c08cf3317291dad554488dd951cd6ff80,Decoupled Classification Refinement: Hard False Positive Suppression for Object Detection,"Decoupled Classiﬁcation Reﬁnement: Hard
-False Positive Suppression for Object Detection
-Bowen Cheng, Yunchao Wei, Honghui Shi, Member, IEEE, Rogerio Schmidt Feris, Senior Member, IEEE,
-Jinjun Xiong, Member, IEEE, and Thomas Huang, Life Fellow, IEEE"
 af34388e69800a168876f7446a621f68ca2215c0,Low-cost scene modeling using a density function improves segmentation performance,"Low-Cost Scene Modeling using a Density Function Improves Segmentation
 Performance
 Vivek Sharma(cid:5)(cid:63), S¸ule Yildirim-Yayilgan(cid:63), and Luc Van Gool(cid:5)∓"
@@ -74601,25 +63205,6 @@ Lingxiao He1
 CRIPAC & NLPR, CASIA 2 University of Chinese Academy of Sciences, Beijing, P.R. China
 Center for Excellence in Brain Science and Intelligence Technology, CAS
 {lingxiao.he, hqli, qi.zhang,"
-af6e351d58dba0962d6eb1baf4c9a776eb73533f,How to Train Your Deep Neural Network with Dictionary Learning,"How to Train Your Deep Neural Network with
-Dictionary Learning
-Vanika Singhal*, Shikha Singh+ and Angshul Majumdar#
-*IIIT Delhi
-Okhla Phase 3
-Delhi, 110020, India
-+IIIT Delhi
-Okhla Phase 3
-#IIIT Delhi
-Okhla Phase 3
-Delhi, 110020, India
-Delhi, 110020, India"
-af9a830f62478c3638880d9a870f0b10535b3f92,Hausdorff distance-based multiresolution maps applied to image similarity measure,"Hausdorff distance-based multiresolution maps
-pplied to image similarity measure
-E. Baudrier*a, G. Millonb, F. Nicolierb, R. Seulinc and S. Ruanb
-LMA – University of La Rochelle, Avenue Cre´peau, 17000 La Rochelle, France
-CReSTIC – URCA, IUT, 9, rue de Que´bec, 10026 Troyes Cedex, France
-Le2i – CNRS UMR 5158, University of Burgundy – IUT, 12, rue de la fonderie, 71200 Le Creusot,
-France"
 af97b793a61ba6e2b02d0d29503b73b5bdc2150d,Wavelet-Local binary pattern based face recognition Azad,"I S S N   2 2 7 7 - 3 0 6 1
 V o l u m e   1 6   N u m b e r   1
 I N T E R N A T I O N A L   J O U R N A L   O F   C O M P U T E R S   &   T E C H N O L O G Y
@@ -74669,11 +63254,6 @@ scientifiques de niveau recherche, publiés ou non,
 émanant des établissements d’enseignement et de
 recherche français ou étrangers, des laboratoires
 publics ou privés."
-af283064e5af079a4a49a8641a2e4cc08e583a59,Monocular Depth Estimation using Multi-Scale Continuous CRFs as Sequential Deep Networks,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015
-Monocular Depth Estimation using Multi-Scale
-Continuous CRFs as Sequential Deep Networks
-Dan Xu, Student Member, IEEE, Elisa Ricci, Member, IEEE, Wanli Ouyang, Senior Member, IEEE,
-Xiaogang Wang, Senior Member, IEEE, Nicu Sebe, Senior Member, IEEE"
 39df6ca15f41e5a674ed8cd1654e699dbc8b8c11,Human tracking over camera networks: a review,"Hou et al. EURASIP Journal on Advances in Signal Processing  (2017) 2017:43
 DOI 10.1186/s13634-017-0482-z
 EURASIP Journal on Advances
@@ -74760,9 +63340,6 @@ Autonomous Vehicle
 Michael Teti1†, William Edward Hahn1, Shawn Martin2, Christopher Teti3, and Elan Barenholtz1
 such tasks, or an attempt
 largely due to recent developments"
-397400dd7c31e47f8dec20a742695abed297a150,An integrated vision-based architecture for home security system,"An Integrated Vision-based Architecture for Home
-Security System
-John See, Student Member, IEEE, and Sze-Wei Lee, Member, IEEE"
 397085122a5cade71ef6c19f657c609f0a4f7473,Using Segmentation to Predict the Absence of Occluded Parts,"GHIASI, FOWLKES: USING SEGMENTATION TO DETECT OCCLUSION
 Using Segmentation to Predict the Absence
 of Occluded Parts
@@ -74797,23 +63374,6 @@ April 23, 2007
 Tiny images
 Antonio Torralba, Rob Fergus, and William T. Freeman
 m a s s a c h u s e t t s   i n s t i t u t e   o f   t e c h n o l o g y,   c a m b r i d g e ,   m a   0 213 9   u s a   —   w w w. c s a i l . m i t . e d u"
-3958db5769c927cfc2a9e4d1ee33ecfba86fe054,Describable Visual Attributes for Face Verification and Image Search,"Describable Visual Attributes for
-Face Veriﬁcation and Image Search
-Neeraj Kumar, Student Member, IEEE, Alexander C. Berg, Member, IEEE,
-Peter N. Belhumeur, and Shree K. Nayar, Member, IEEE"
-39675124e4fe1be08f42bdd2e1e237e5a87839ba,"Adversarial Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion Segmentation","Adversarial Collaboration: Joint Unsupervised
-Learning of Depth, Camera Motion, Optical
-Flow and Motion Segmentation
-Anurag Ranjan1
-Varun Jampani2
-Kihwan Kim 2
-Deqing Sun 2
-Jonas Wulff 1
-Michael J. Black1
-Max Planck Institute for Intelligent Systems
-NVIDIA Research
-{aranjan, jwulff,
-{vjampani, kihwank,"
 3918dcfddf2da218a615dd8f008f6fce436e06f7,Learning Sight from Sound: Ambient Sound Provides Supervision for Visual Learning,"Int J Comput Vis manuscript No.
 (will be inserted by the editor)
 Learning Sight from Sound:
@@ -74860,17 +63420,6 @@ Activities
 •  Bangpeng Yao
 •  Li Fei-Fei
 Presented by Sahil Shah"
-399f973a59493280db9686ebd9e7e218ce74a5bd,Face Recognition System – A Survey,"International Journal of Science and Research (IJSR)
-ISSN (Online): 2319-7064
-Index Copernicus Value (2013): 6.14 | Impact Factor (2013): 4.438
-Face Recognition System – A Survey
-Richa1, Jagroop Kaur Josan2
-M.Tech Scholar, Department of Computer Engineering, Punjabi University, Patiala, Punjab, India
-Assistant Professor, Department of Computer Engineering, Punjabi University, Patiala, Punjab, India"
-390f3d7cdf1ce127ecca65afa2e24c563e9db93b,Learning and Transferring Multi-task Deep Representation for Face Alignment,"SUBMITTED TO IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
-Learning Deep Representation for Face
-Alignment with Auxiliary Attributes
-Zhanpeng Zhang, Ping Luo, Chen Change Loy, Member, IEEE and Xiaoou Tang, Fellow, IEEE"
 397c395aed9d96aef064b9ceb9f0eae9421eb00a,An Evaluation of the Pedestrian Classification in a Multi-Domain Multi-Modality Setup,"Sensors 2015, 15, 13851-13873; doi:10.3390/s150613851
 OPEN ACCESS
 sensors
@@ -75094,26 +63643,6 @@ der Ruhr-Universit¨at Bochum
 vorgelegt von
 Alexander Rainer Tassilo Gepperth
 m 19.April 2006"
-a2dd13729206a7434ef1f0cd016275c0d6f3bb6d,SFV: Reinforcement Learning of Physical Skills from Videos,"SFV: Reinforcement Learning of Physical Skills from Videos
-XUE BIN PENG, University of California, Berkeley
-ANGJOO KANAZAWA, University of California, Berkeley
-JITENDRA MALIK, University of California, Berkeley
-PIETER ABBEEL, University of California, Berkeley
-SERGEY LEVINE, University of California, Berkeley
-Fig. 1. Simulated characters performing highly dynamic skills learned by imitating video clips of human demonstrations. Left: Humanoid performing
-artwheel B on irregular terrain. Right: Backflip A retargeted to a simulated Atlas robot.
-Data-driven character animation based on motion capture can produce
-highly naturalistic behaviors and, when combined with physics simula-
-tion, can provide for natural procedural responses to physical perturbations,
-environmental changes, and morphological discrepancies. Motion capture
-remains the most popular source of motion data, but collecting mocap data
-typically requires heavily instrumented environments and actors. In this
-paper, we propose a method that enables physically simulated characters
-to learn skills from videos (SFV). Our approach, based on deep pose esti-
-mation and deep reinforcement learning, allows data-driven animation to
-leverage the abundance of publicly available video clips from the web, such
-s those from YouTube. This has the potential to enable fast and easy de-
-sign of character controllers simply by querying for video recordings of the"
 a237e3d89c460e1b2e3f12c5d4275bd0c6eb47a8,Domain Adaptation on Graphs by Learning Aligned Graph Bases,"Domain Adaptation on Graphs by Learning
 Aligned Graph Bases
 Mehmet Pilancı and Elif Vural"
@@ -75192,17 +63721,6 @@ September 2011
 Department of Information and Computing Sciences
 Utrecht University, Utrecht, The Netherlands
 www.cs.uu.nl"
-a2fbaa0b849ecc74f34ebb36d1442d63212b29d2,An Efficient Approach to Face Recognition of Surgically Altered Images,"Volume 5, Issue 6, June 2015                                           ISSN: 2277 128X
-International Journal of Advanced Research in
-Computer Science and Software Engineering
-Research Paper
-Available online at: www.ijarcsse.com
-An Efficient Approach to Face Recognition of Surgically
-Altered Images
-Er. Supriya, Er. Sukhpreet Kaur
-Department of computer science and engineering
-SUS college of Engineering and Technology,
-Tangori, District, Mohali, Punjab, India"
 a2fce1c551a3c3b1cac16a96f86a59cd7fbd4c80,Attachment and Children’s Biased Attentional Processing: Evidence for the Exclusion of Attachment-Related Information,"Attachment and Children’s Biased Attentional
 Processing: Evidence for the Exclusion of Attachment-
 Related Information
@@ -75336,14 +63854,6 @@ Bilderatlas
 Leonardo Impett, Sabine S¨usstrunk
 School of Computer and Communication Sciences,
 ´Ecole F´ed´erale Polytechnique de Lausanne, Switzerland"
-f3b24cdbd1e7fd94d7ad1fa077dfa051bcc8aa38,AUTOMATIC IMAGE ANNOTATION MODEL USING LSTM APPROACH,"Signal & Image Processing : An International Journal (SIPIJ) Vol.8, No.4, August 2017
-AUTOMATIC IMAGE ANNOTATION MODEL
-USING LSTM APPROACH
-Sonu Pratap Singh Gurjar1,  Shivam Gupta1 and Rajeev Srivastava2
-Student, Department of Computer Science and Engineering,
-IIT-BHU, Varanasi, Uttar Pradesh, India
-Professor, Department of Computer Science and Engineering,
-IIT-BHU, Varanasi, Uttar Pradesh, India"
 f3161b75de1e37b0591f250068b676ea72d1ba22,"Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement Learning","Motion Planning Among Dynamic, Decision-Making Agents
 with Deep Reinforcement Learning
 Michael Everett‡, Yu Fan Chen†, and Jonathan P. How‡"
@@ -75366,24 +63876,8 @@ methodology for head pose estimation in the wild
 Fl´avio H. B. Zavan, Antonio C. P. Nascimento, Olga R. P. Bellon and Luciano Silva
 IMAGO Research Group - Universidade Federal do Paran´a"
 f33c427dc152c20537d2857bee1dda2287e85860,Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks,
-f34a6c1bc9a7872c8dc4c35b678f87bb966ab0ab,"PHOG-derived aesthetic measures applied to color photographs of artworks, natural scenes and objects","PHOG-Derived Aesthetic Measures Applied
-to Color Photographs of Artworks,
-Natural Scenes and Objects
-Christoph Redies2, Seyed Ali Amirshahi1,2,
-Michael Koch1,2, and Joachim Denzler1
-Computer Vision Group, Friedrich Schiller University Jena, Germany
-http://www.inf-cv.uni-jena.de
-Institute of Anatomy I, Friedrich Schiller University,
-Jena University Hospital, Germany
-http://www.anatomie1.uniklinikum-jena.de"
 f3c60536cf7a397c9df6bca549824841a6d7598c,Automatic architecture selection for probability density function estimation in computer vision,"7308011
 UNIVERSITY  OF  SURREY  LIBRARY"
-f3f65a8113d6a2dcbc690fd47dfee2dff0f41097,Generating 3D Faces Using Convolutional Mesh Autoencoders,"Generating 3D faces using Convolutional Mesh
-Autoencoders
-Anurag Ranjan, Timo Bolkart, Soubhik Sanyal, and Michael J. Black
-Max Planck Institute for Intelligent Systems
-{aranjan, tbolkart, ssanyal,
-T¨ubingen, Germany"
 f36c3ddd43ea7c2e803694aad89e5fd903715c81,"Biometric quality: a review of fingerprint, iris, and face","Bharadwaj et al. EURASIP Journal on Image and Video Processing 2014, 2014:34
 http://jivp.eurasipjournals.com/content/2014/1/34
 REVIEW
@@ -75396,26 +63890,6 @@ Two-Stream Multi-Rate Recurrent Neural
 Network for Video-Based Pedestrian
 Re-Identiﬁcation
 Zhiqiang Zeng, Zhihui Li*, De Cheng, Huaxiang Zhang, Kun Zhan and Yi Yang"
-f36647e63a11486ef9cf7a5a1c86a40fda5d408a,CS 229 Final Report : Artistic Style Transfer for Face Portraits,"CS 229 Final Report: Artistic Style Transfer for Face Portraits
-Daniel Hsu, Marcus Pan, Chen Zhu
-{dwhsu, mpanj,
-Dec 16, 2016
-Introduction
-The goal of our project is to learn the content and style
-representations of face portraits, and then to combine
-them to produce new pictures. The content features of
-face are the features that identify a face, such as the
-outline shape. The stylistic features are the artistic char-
-cteristics of a certain portrait or painting, such as brush
-strokes, or background color. We forward-pass a content
-image, and several style images through a CNN to ex-
-tract the desired content and style features. Then we
-initialize a white noise image, and perform gradient de-
-scent on its pixels until it matches the desired style and
-ontent features.
-vNet. We hope our project can be a supplement to ex-
-isting implementations.
-Gradient Descent Loss Functions"
 f3002f126f7da75f838637cc314b5f8adc09da53,Robust Face Sketch Synthesis via Generative Adversarial Fusion of Priors and Parametric Sigmoid,"Proceedings of the Twenty-Seventh International Joint Conference on Artiﬁcial Intelligence (IJCAI-18)
 CUHK(b) XM2VTS(c) AR(d) Lighting(e) Pose(f) CelebrityPhotoMWFcGANpGANFigure1:Examplesoffacesketchesgeneratedfromfacephotostakeninthewild,i.e.,underuncontrolledconditions.Weonlyse-lect88subjectsintheCUHKstudentdatasetfortraining.Thesketchesgeneratedbydata-drivenmethod(MWF),model-basedmethod(cGAN)andourmethod(pGAN)arelistedinthesecond,thirdandfourthrows,respectively.(a)-(f)aretheresultsofdifferenttestingphotosfrom(a)theCUHKstudentdataset,(b)theXM2VTSdataset,(c)theARdataset,(d)thelightingvariationset,(e)theposevariationsetand(f)celebrityphotosobtainedfromtheWeb.Ourmethodachievessatisfactoryresultsundersuchuncontrolledcondi-tions.stillfailtosynthesizefacesketchesinthewild.Insuchcir-cumstances,thetestingphotosaretakenunderdifferentcon-ditionsfromthetrainingphotos,containingvariationsofil-lumination,pose,backgroundandethnicorigin,asshowninFigure1.Althoughtherearesomeworks[Zhangetal.,2010;Zhangetal.,2015b;Pengetal.,2016;Zhangetal.,2017;Songetal.,2017;Zhuetal.,2017b]payingattentiontothischallengingproblem,thesemethodsonlydealwithcertainaspects,suchasthelightingandposevariations[Zhangetal.,2010],thebackgroundandnon-facialfactors[Zhangetal.,2015b]orthelightingvariationsandclutterbackground[Pengetal.,2016].Mostexistingmethodssimulatethepro-cessofsketchsynthesisbyusinglowlevelfeatures,whichishardlytobegeneralizedtouncontrolledconditions.Incon-"
 f3cf10c84c4665a0b28734f5233d423a65ef1f23,Title Temporal Exemplar-based Bayesian Networks for facialexpression recognition,"Title
@@ -75451,10 +63925,6 @@ Department of Computer Science, ETH Zurich, Switzerland
 Vizrt"
 f39b88ac61264e9a33dcdf47722f0d048a8e490f,Interactive Data Integration and Entity Resolution for Exploratory Visual Data Analytics,"(cid:13)Copyright 2015
 Kristi Morton"
-f3b7938de5f178e25a3cf477107c76286c0ad691,Object Detection with Deep Learning: A Review,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, MARCH 2017
-Object Detection with Deep Learning: A Review
-Zhong-Qiu Zhao, Member, IEEE, Peng Zheng,
-Shou-tao Xu, and Xindong Wu, Fellow, IEEE"
 f3ea181507db292b762aa798da30bc307be95344,Covariance Pooling For Facial Expression Recognition,"Covariance Pooling for Facial Expression Recognition
 Computer Vision Lab, ETH Zurich, Switzerland
 VISICS, KU Leuven, Belgium
@@ -75539,16 +64009,6 @@ nd Boosting
 Matthew Cooper
 FX Palo Alto Laboratory
 Palo Alto, CA 94304 USA"
-935ce31268232b25c9f685128ae0ae9e5c3a0e8e,Implementation of Human detection system using DM 3730,"International Journal of Science and Research (IJSR)
-ISSN (Online): 2319-7064
-Impact Factor (2012): 3.358
-Implementation of Human detection system using
-DM3730
-Amaraneni Srilaxmi1, Shaik Khaddar Sharif2
-VNR Vignana Jyothi Institute of Engineering & Technology, Bachupally, Hyderabad, India
-VNR Vignana Jyothi Institute of Engineering & Technology, Bachupally, Hyderabad, India
-digital
-ontent  management,"
 93e962f8886eae13b02ad2aa98bdedfbd7e68709,Dual Conditional GANs for Face Aging and Rejuvenation,"Proceedings of the Twenty-Seventh International Joint Conference on Artiﬁcial Intelligence (IJCAI-18)
 Source： datasets(b)Target: our outputs are a series of images belonging to the same person010Input FaceOutputs2  78x/Age groupy/Personality  2178Non-sequential facial imagesSequential facial imagesFigure1:Anillustrationofourfaceagingandrejuvenationpro-cess.As(a)shows,ourtrainingexamplesarenon-sequentialandun-paired,andweaimtosimultaneouslyrenderaseriesofage-changedfacialimagesofapersonandpreservepersonality,asshownin(b).speciﬁcallydescribethechangesoffacesindifferentages.Thesemethodsparametricallymodelshapeandtexturepa-rametersfordifferentfeaturesofeachagegroup,e.g.,mus-cles[Suoetal.,2012],wrinkles[RamanathanandChellappa,2008;Suoetal.,2010]andfacialstructure[RamanathanandChellappa,2006;Lanitisetal.,2002].Ontheotherhand,prototype-basedmethods[KemelmacherShlizermanetal.,2014;Tiddemanetal.,2001]dividefacesintogroupsbyage,andthenconstructanaveragefaceasitsprototypeforeachagegroup.Afterthat,thesemethodscantransferthetexturedifferencebetweentheprototypestotheinputfacialimage.Morerecently,thedeeplearning-basedmethod[Wangetal.,2016;Liuetal.,2017]achievedthestate-of-the-artper-formance.In[Wangetal.,2016],RNNisappliedonthecoefﬁcientsofeigenfacesforagepatterntransition.Itper-formsthegroup-basedlearningwhichrequiresthetrueageoftestingfacestolocalizethetransitionstatewhichmightnotbeconvenient.Inaddition,theseapproachesonlypro-videageprogressionfromyoungerfacetoolderones.Toachieveflexiblebidirectionalagechanges,itmayneedtoretrainthemodelinversely.GenerativeAdversarialNet-"
 93a4c7ac0b09671db8cd3adbe62851d7befc4658,Machine Analysis of Facial Expressions,"We are IntechOpen,
@@ -75643,13 +64103,6 @@ Pascal Fua
 École Polytechnique Fédérale de Lausanne
 Visual Computing Group, University of Victoria
 Kwang Moo Yi"
-dcd88a249b480d2e25326cdd11c5879fa31865cc,A Cross-Modal Distillation Network for Person Re-identification in RGB-Depth,"A Cross-Modal Distillation Network for Person
-Re-identiﬁcation in RGB-Depth
-Frank Hafner
-, Amran Bhuiyan,
-, Julian F. P. Kooij
-, Eric Granger
-, Member, IEEE"
 dc452f3e531c4057c930f0538d5652ad9034d1aa,Quality metrics for practical face recognition,"1st International Conference on Pattern Recognition (ICPR 2012)
 November 11-15, 2012. Tsukuba, Japan
 978-4-9906441-0-9 ©2012 ICPR"
@@ -75766,26 +64219,6 @@ produced through a custom interface with Amazon Mechanical Turk. This dataset co
 location error of ∼ 7% of a typical body dimension, and orientation error of 12◦, approximating the
 variability of human raters. Our results provide an important step towards ef‌f‌icient image-based
 dense object tracking by allowing for the accurate determination of object location and orientation"
-dcba9cd587be2ed5437370e12e3591bdde86dc3c,TEMPLATE FOR REGULAR ENTRY,"TEMPLATE FOR REGULAR ENTRY
-(ENCYCLOPEDIA OF DATABASE SYSTEMS)
-TITLE OF ENTRY
-Automatic Image Annotation
-BYLINE
-Nicolas Hervé and Nozha Boujemaa, INRIA Paris-Rocquencourt, IMEDIA project, France.
-http://www-rocq.inria.fr/imedia/
-SYNONYMS
-Multimedia Content Enrichment, Image Classification, Object Detection and Recognition,
-Auto-annotation
-DEFINITION
-The widespread search engines, in the professional as well as the personal context, used to work
-on the basis of textual information associated or extracted from indexed documents. Nowadays,
-most of the exchanged or stored documents have multimedia content. To reduce the technological
-gap so that these engines still can work on multimedia content, it is very convenient developing
-methods capable to generate automatically textual annotations and metadata.  These methods will
-then allow to enrich the  upcoming new content or to post-annotate the existing  content with
-dditional information extracted automatically if ever this existing content is partly or not annotated.
-A broad diversity in the typology of manual annotation is usually found in image databases. Part of
-them   is   representing   contextual   information.   The   author,   date,   place   or   technical   shooting"
 dc9a6a821689de877bd07e970e52d4cdb1dd2714,Transfer of gender aftereffects in face silhouettes reveals face-specific mechanisms,"Transfer of gender aftereffects in face silhouettes reveals face-specific mechanisms
 Nicolas Davidenko
 Nathan Witthoft
@@ -75796,13 +64229,6 @@ dc9f29118e38602c03bb2866f8b12ce478aad52c,Large scale evolution of convolutional
 Networks Using Volunteer Computing
 Travis Desell∗
 March 17, 2017"
-dc550f361ae82ec6e1a0cf67edf6a0138163382e,Emotion Based Music Player,"ISSN XXXX XXXX © 2018 IJESC
-Research Article                                                                                                                           Volume 8 Issue No.3
-Vijay Chakole1, Aniket Choudhary2, Kalyani Trivedi3, Kshitija Bhoyar4, Ruchita Bodele5, Sayali Karmore6
-Emotion Based Music Player
-Professor1, UG Student2, 3, 4, 5, 6
-Department of Electronics Engineering
-K.D.K. College of Engineering Nagpur, India"
 dcce157aa2e5db081b36fd16544a038becb408ab,Fast and Accurate Pedestrian Detection in a Truck's Blind Spot Camera,"Fast and Accurate Pedestrian Detection
 in a Truck’s Blind Spot Camera
 Kristof Van Beeck1,2(B) and Toon Goedem´e1,2
@@ -75953,12 +64379,6 @@ Ezgi Mercan, Indriyati Atmosukarto, Jia Wu, Shu Liang and Linda G. Shapiro"
 878301453e3d5cb1a1f7828002ea00f59cbeab06,Faceness-Net: Face Detection through Deep Facial Part Responses,"Faceness-Net: Face Detection through
 Deep Facial Part Responses
 Shuo Yang, Ping Luo, Chen Change Loy, Senior Member, IEEE and Xiaoou Tang, Fellow, IEEE"
-87cab840df202609bfcfb5a9ee3293e61c7c85db,Vision based victim detection from unmanned aerial vehicles,"Vision Based Victim Detection from Unmanned Aerial Vehicles
-Mykhaylo Andriluka1, Paul Schnitzspan1, Johannes Meyer2, Stefan Kohlbrecher1,
-Karen Petersen1, Oskar von Stryk1, Stefan Roth1, and Bernt Schiele1,3
-Department of Computer Science, TU Darmstadt
-Department of Mechanical Engineering, TU Darmstadt
-MPI Informatics, Saarbr¨ucken"
 87ba4cce558c2defde90f4b42853262fd572ca3e,Silhouette estimation.,"J. Opt. Soc. Am. A / Vol. 31, No. 7 / July 2014
 Paxman et al.
 Silhouette estimation
@@ -76066,11 +64486,6 @@ they feel under surveillance or as criminals. Others, in turn, are characterized
 y problems with the acquisition of biometric pattern and require closeness
 to the reader. Among the biometric methods popular technique is to identify
 people on the basis of the face image, the advantage is the ease of obtaining"
-87bba3f4292727091027b7888b5d8f364425344d,End-to-End Learning of Driving Models with Surround-View Cameras and Route Planners,"End-to-End Learning of Driving Models with
-Surround-View Cameras and Route Planners
-Simon Hecker1, Dengxin Dai1, and Luc Van Gool1,2
-ETH Zurich, Zurich, Switzerland
-KU Leuven, Leuven, Belgium"
 87c6ba55b0f817de4504e39dbb201842ae102c9f,Three Dimensional Face Recognition Using Iso-Geodesic and Iso-Depth Curves,"Three Dimensional Face Recognition Using Iso-Geodesic and Iso-Depth
 Curves
 Sina Jahanbin, Hyohoon Choi, Yang Liu, Alan C. Bovik"
@@ -76113,10 +64528,6 @@ V´ıctor Campos∗†, Brendan Jou‡, Xavier Gir´o-i-Nieto§, Jordi Torres†
 Barcelona Supercomputing Center, ‡Google Inc,
 §Universitat Polit`ecnica de Catalunya, ΓColumbia University
 {victor.campos,"
-0b2277a0609565c30a8ee3e7e193ce7f79ab48b0,Cost-Sensitive Semi-Supervised Discriminant Analysis for Face Recognition,"Cost-Sensitive Semi-Supervised Discriminant
-Analysis for Face Recognition
-Jiwen Lu, Member, IEEE, Xiuzhuang Zhou, Member, IEEE, Yap-Peng Tan, Senior Member, IEEE,
-Yuanyuan Shang, Member, IEEE, and Jie Zhou, Senior Member, IEEE"
 0b0eb562d7341231c3f82a65cf51943194add0bb,Facial Image Analysis Based on Local Binary Patterns : A Survey,"> REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) <
 Facial Image Analysis Based on Local Binary
 Patterns: A Survey
@@ -76126,10 +64537,6 @@ Detection through Onboard Monocular Vision
 Ruimin Ke1               Jerome Lutin2               Jerry Spears3               Yinhai Wang1,*
 University of Washingtion    2New Jersey Transit    3Washington State Transit Insurance Pool
 {ker27,"
-0b2d49cb2d2de06b022e2c636e337d294171dc22,New features and insights for pedestrian detection,"New Features and Insights for Pedestrian Detection
-Stefan Walk1 Nikodem Majer1 Konrad Schindler1 Bernt Schiele1,2
-Computer Science Department, TU Darmstadt
-MPI Informatics, Saarbr¨ucken"
 0b19177107a102ee81e5ef1bb9fb2f2881441503,Comparing Robustness of Pairwise and Multiclass Neural-Network Systems for Face Recognition,"Hindawi Publishing Corporation
 EURASIP Journal on Advances in Signal Processing
 Volume 2008, Article ID 468693, 7 pages
@@ -76150,8 +64557,6 @@ pairwise recognition system is shown to outperform the multiclass-recognition sy
 test face images.
 Copyright © 2008 J. Uglov et al. This is an open access article distributed under the Creative Commons Attribution License, which
 permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited."
-0b20f75dbb0823766d8c7b04030670ef7147ccdd,Feature selection using nearest attributes,"Feature selection using nearest attributes
-Alex Pappachen James, Member, IEEE, and Sima Dimitrijev, Senior Member, IEEE"
 0b174d4a67805b8796bfe86cd69a967d357ba9b6,A Survey on Face Detection and Recognition Approaches,"Research Journal of Recent Sciences _________________________________________________ ISSN 2277-2502
 Vol. 3(4), 56-62, April (2014)
 Res.J.Recent Sci."
@@ -76164,26 +64569,6 @@ Chih-Yuan Yang Sifei Liu Ming-Hsuan Yang
 Electrical Engineering and Computer Science
 University of California at Merced
 {cyang35, sliu32,"
-0b6c10ea6bf8a6c254e00fcc2163c4b6fc0f1c3a,"Anti-Spoofing for Text-Independent Speaker Verification: An Initial Database, Comparison of Countermeasures, and Human Performance","Anti-Spoofing for Text-Independent Speaker Verification: An
-Initial Database, Comparison of Countermeasures, and Human
-Performance
-Citation for published version:
-Wu, Z, De Leon, P, Demiroglu, C, Khodabakhsh, A, King, S, Ling, Z, Saito, D, Stewart, B, Toda, T, Wester,
-M & Yamagishi, J 2016, 'Anti-Spoofing for Text-Independent Speaker Verification: An Initial Database,
-Comparison of Countermeasures, and Human Performance'  IEEE/ACM Transactions on Audio, Speech,
-nd Language Processing, vol. 24, no. 4, pp. 768 - 783. DOI: 10.1109/TASLP.2016.2526653
-Digital Object Identifier (DOI):
-0.1109/TASLP.2016.2526653
-Link:
-Link to publication record in Edinburgh Research Explorer
-Document Version:
-Peer reviewed version
-Published In:
-General rights
-Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s)
-nd / or other copyright owners and it is a condition of accessing these publications that users recognise and
-bide by the legal requirements associated with these rights.
-Take down policy"
 0b70facac4d10c7c73e7fdf3a85848ce429d98ab,"Segmentation features, visibility modeling and shared parts for object detection","Segmentation Features, Visibility Modeling and
 Shared Parts for Object Detection
 Patrick Ott
@@ -76257,12 +64642,6 @@ Weipeng Xu[1,2], Srinath Sridhar[3], Gerard Pons-Moll[1,2], Christian Theobalt[1
 [1] MPI For Informatics
 [2] Saarland Informatics Campus
 [3] Stanford University"
-0bf2765d431c16de7b8f9c644684e69fa52598eb,Integrating Remote PPG in Facial Expression Analysis Framework,"Integrating Remote PPG in Facial Expression Analysis
-Framework
-H. Emrah Tasli
-Marten den Uyl
-Vicarious Perception Technologies, Amsterdam, The Netherlands
-Amogh Gudi"
 0b888196dda951287dddb60bd44798aab16d6fca,Learning Common Sense through Visual Abstraction,
 0b937abb3b356a2932d804f9fc4b463485f63d0e,Visual word disambiguation by semantic contexts,"Visual word disambiguation by semantic contexts
 Yu Su, Frédéric Jurie
@@ -76297,15 +64676,6 @@ Retrieval in Large Scale Databases
 Simone Ercoli, Marco Bertini and Alberto Del Bimbo
 Media Integration and Communication Center, Università degli Studi di Firenze
 Viale Morgagni 65 - 50134 Firenze, Italy"
-0b87d91fbda61cdea79a4b4dcdcb6d579f063884,Research on Theory and Method for Facial Expression Recognition System Based on Dynamic Image Sequence,"The Open Automation and Control Systems Journal, 2015, 7, 569-579
-Open Access
-Research  on  Theory  and  Method  for  Facial  Expression  Recognition  Sys-
-tem Based on Dynamic Image Sequence
-Send Orders for Reprints to
-Yang Xinfeng1,* and Jiang Shan2
-School  of  Computer  &  Information  Engineering,  Nanyang  Institute  of  Technology,  Henan,  Nanyang,  473000,  P.R.
-China
-Henan University of Traditional Chinese Medicine, Henan, Zhengzhou, 450000, P.R. China"
 0bbd0060e79c5370c6d07bef7b5830e8732e7c1b,Automatic tracker selection w.r.t object detection performance,"Automatic Tracker Selection w.r.t Object Detection Performance
 Duc Phu Chau
 Monique Thonnat
@@ -76405,26 +64775,6 @@ Algorithms⋆
 Nikolay Degtyarev and Oleg Seredin
 Tula State University
 http://lda.tsu.tula.ru"
-0b3a5267c6543a8b4ff3473199bbc648596f6776,Supplementary Material for Superpixel Convolutional Networks using Bilateral Inceptions,"Supplementary Material for
-Superpixel Convolutional Networks using
-Bilateral Inceptions
-Raghudeep Gadde1(cid:63), Varun Jampani2(cid:63), Martin Kiefel2,3, Daniel Kappler2, and
-Peter V. Gehler2,3
-Universit´e Paris-Est, LIGM (UMR 8049), CNRS, ENPC, ESIEE, UPEM, France
-Max Planck Institute for Intelligent Systems, T¨ubingen, Germany
-Bernstein Center for Computational Neuroscience, T¨ubingen, Germany
-In this supplementary, we ﬁrst discuss the use of an approximate bilateral
-ﬁltering in BI modules (Sec. 1). Later, we present some qualitative results using
-different models for the approach presented in the main paper (Sec. 2).
-Approximate Bilateral Filtering
-The bilateral inception module presented in the main paper computes a matrix-
-vector product between a Gaussian ﬁlter K and a vector of activations zc. Bi-
-lateral ﬁltering is an important operation and many algorithmic techniques have
-een proposed to speed-up this operation [1,2,3]. In the main paper we opted
-to implement what can be considered the brute-force variant of explicitly con-
-structing K and then using BLAS to compute the matrix-vector product. This
-resulted in a few millisecond operation. The explicit way to compute is possi-
-le due to the reduction to super-pixels, e.g., it would not work for DenseCRF"
 0babc4af06d210cf38bdf8324c339b6cf3f424fa,A Predictive Model of Patient Readmission Using Combined ICD-9 Codes as Engineered Features,"A Predictive Model of Patient Readmission Using Combined ICD-9
 Codes as Engineered Features"
 0b4c4ea4a133b9eab46b217e22bda4d9d13559e6,MORF: Multi-Objective Random Forests for face characteristic estimation,"MORF: Multi-Objective Random Forests for Face Characteristic Estimation
@@ -76442,20 +64792,6 @@ Punarjay Chakravarty
 Tinne Tuytelaars
 KU Leuven, ESAT-PSI, iMinds, Belgium
 {rahaf.aljundi, Punarjay.Chakravarty,"
-0bfabcf5c74cc17fe8b5777093699789411868b9,Predictive Tagging of Social Media Images using Unsupervised Learning,"International Journal of Computer Applications (0975 – 8887)
-Volume 65– No.24, March 2013
-Predictive Tagging of Social Media Images using
-Unsupervised Learning
-Nishchol Mishra
-Asstt. Professor
-School of IT
-RGPV, Bhopal
-India
-Sanjay Silakari, PhD.
-Professor, Deptt. Of CSE
-UIT- RGPV
-Bhopal
-India"
 0b4453df81091bcdafedc07b64bea946bf3441b2,Fast and Accurate 3 D Face Recognition Using Registration to an Intrinsic Coordinate System and Fusion of Multiple Region Classifiers,"Int J Comput Vis
 DOI 10.1007/s11263-011-0426-2
 Fast and Accurate 3D Face Recognition
@@ -76485,22 +64821,6 @@ Graduate School."
 Francesco Solera Simone Calderara Rita Cucchiara
 Department of Engineering
 University of Modena and Reggio Emilia"
-0b572a2b7052b15c8599dbb17d59ff4f02838ff7,Automatic Subspace Learning via Principal Coefficients Embedding,"Automatic Subspace Learning via Principal
-Coefﬁcients Embedding
-Xi Peng, Jiwen Lu, Senior Member, IEEE, Zhang Yi, Fellow, IEEE and Rui Yan, Member, IEEE,"
-0b43a712f055f788fd0502cac4455e254b1adbeb,Multi-modal Face Pose Estimation with Multi-task Manifold Deep Learning,"IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. XX, NO. XX, XX XX
-Multi-modal Face Pose Estimation with
-Multi-task Manifold Deep Learning
-Chaoqun Hong, Jun Yu, Member, IEEE, and Jian Zhang"
-0b278c9dc9b16b46ed602eab884ad7a37a988031,Robust Face-Name Graph Matching for Movie Character Identification,"International Journal of Science and Research (IJSR)
-ISSN (Online): 2319-7064
-Index Copernicus Value (2015): 78.96 | Impact Factor (2015): 6.391
-Robust Face-Name Graph Matching for Movie
-Character Identification
-Jonnadula Narasimha1, S Nishanth Kumar2, Chiluka Shiva Kumar3, D Vamshi Krishna Rao4
-Associate Professor, Department of Computer Science and Engineering, CMR Technical Campus,
-Medchal, Hyderabad, Telangana, India
-, 3, 4Department of Computer Science and Engineering, CMR Technical Campus, Medchal, Hyderabad, Telangana, India"
 0b605b40d4fef23baa5d21ead11f522d7af1df06,Label-Embedding for Attribute-Based Classification,"Label-Embedding for Attribute-Based Classiﬁcation
 Zeynep Akataa,b, Florent Perronnina, Zaid Harchaouib and Cordelia Schmidb
 Computer Vision Group∗, XRCE, France
@@ -76563,39 +64883,11 @@ Domingo Mery, Vladimir Riffo, Irene Zuccar, Christian Pieringer
 Department of Computer Science – Pontiﬁcia Universidad Cat´olica de Chile
 Av. Vicu˜na Mackenna 4860(143) – Santiago de Chile
 http://dmery.ing.puc.cl"
-0b0b0d9b15613a6e3c4f9a4dd1c17c0313ca4303,Evaluation of 3D Face Recognition in the presence of facial expressions: an Annotated Deformable Model approach,"D face recognition
-in the presence of facial expressions:
-An annotated deformable model approach
-I.A. Kakadiaris, Member, IEEE, G. Passalis, G. Toderici, N. Murtuza, Y. Lu,
-N. Karampatziakis, and T. Theoharis
-August 15, 2006
-DRAFT"
-0bddd3a4f45ef68faeb96cee89ff763e8e497af1,Regularization Method for Solving Denoising and Inpainting Task Using Stacked Sparse Denoising Autoencoders,"Original Research Paper
-American Journal of Applied Sciences
-Regularization Method for Solving Denoising and Inpainting
-Task Using Stacked Sparse Denoising Autoencoders
-Pavel Vyacheslavovich Skribtsov and Sergey Olegovich Surikov
-PAWLIN Technologies Ltd, Dubna, Russia
-Article history
-Received: 06-10-2015
-Revised: 01-01-2016
-Accepted: 13-01-2016
-Corresponding Author:
-Pavel Vyacheslavovich Skribtsov,
-PAWLIN Technologies Ltd,
-Dubna, Russia
-Email:
-Introduction
-image  denoising  and"
 0b3a146c474166bba71e645452b3a8276ac05998,Who ’ s in the Picture ?,"Who’s in the Picture?
 Tamara L. Berg, Alexander C. Berg, Jaety Edwards and D.A. Forsyth
 Berkeley, CA 94720
 Computer Science Division
 U.C. Berkeley"
-0b6a5200c33434cbfa9bf24ba482f6e06bf5fff7,"The use of deep learning in image segmentation, classification and detection","The Use of Deep Learning in Image
-Segmentation, Classification and Detection
-Mihai-Sorin Badea, Iulian-Ionuț Felea, Laura Maria Florea, Constantin Vertan
-The Image Processing and Analysis Lab (LAPI), Politehnica University of Bucharest, Romania"
 b47ea4d5b0040d85181925bda74da4ab5303768f,LIFEisGAME: A Facial Character Animation System to Help Recognize Facial Expressions,"LIFEisGAME:A Facial Character Animation System to
 Help Recognize Facial Expressions
 Tiago Fernandes1,5, Samanta Alves2, José Miranda3,5, Cristina Queirós2,
@@ -76734,13 +65026,6 @@ Christian Eggert
 Multimedia Computing and Computer Vision Lab
 {anton.winschel, rainer.lienhart,
 University of Augsburg, Germany"
-b419e0e1192d307d536421d811d10657f65eb72b,Face Recognition using DCT based Energy Discriminant Mask,"International Journal of Computer Applications (0975 – 8887)
-Volume 170 – No.5, July 2017
-Face Recognition using DCT based Energy
-Discriminant Mask
-Vikas Maheshkar
-Division of Information technology
-New Delhi, India"
 b49aa569ff63d045b7c0ce66d77e1345d4f9745c,Convolutional Neural Networks for Crop Yield Prediction using Satellite Images,"Convolutional Neural Networks for Crop Yield Prediction using Satellite Images
 H. Russello"
 b4270de7380d305b4417f662686093c40d842da4,UNIVERSITY OF CALIFORNIA RIVERSIDE Graphical Models for Wide-Area Activity Analysis in Continuous Videos A Dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy,"UNIVERSITY OF CALIFORNIA
@@ -76780,9 +65065,6 @@ of image clusters
 Stephan Gammeter1, Till Quack1, David Tingdahl2, and Luc van Gool1,2
 BIWI, ETH Z¨urich1 http://www.vision.ee.ethz.ch
 VISICS, K.U. Leuven2 http://www.esat.kuleuven.be/psi/visics"
-b45a9f95980c434582c920bf15a8099ec267c1f7,Robust Kronecker Component Analysis,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015
-Robust Kronecker Component Analysis
-Mehdi Bahri, Student Member, IEEE, Yannis Panagakis, and Stefanos Zafeiriou, Member, IEEE"
 b4b1b39f8902208bbd37febfb68e08809098036d,TRECVid Semantic Indexing of Video : A 6-year Retrospective,"UvA-DARE (Digital Academic Repository)
 TRECVid Semantic Indexing of Video: A 6-year Retrospective
 Awad, G.; Snoek, C.G.M.; Smeaton, A.F.; Quénot, G.
@@ -76810,9 +65092,6 @@ Network
 Khan Farheen Wahab, 2Aniruddha Kailuke
 ,2Department of Electronics (Communication), Priyadarshini Institute of Engineering, The University of Nagpur
 (RTMNU) Nagpur"
-b4f3e9fc0a2b40595ae0a625d1d768a57a7c2eba,Recognizing Disguised Faces in the Wild,"Recognizing Disguised Faces in the Wild
-Maneet Singh, Student Member, IEEE, Richa Singh, Senior Member, IEEE, Mayank Vatsa, Senior
-Member, IEEE, Nalini Ratha, Fellow, IEEE, and Rama Chellappa, Fellow, IEEE"
 b4b6a0129bf6a716fca80a4cfc322687a72fa927,Automatic Generation of Planar Marionettes from Frontal Images,"Automatic Generation of Planar Marionettes from Frontal Images
 Elad Richardson and Gil Ben-Shachar
 Supervised by Anastasia Dubrovina and Aaron Weltzer"
@@ -76831,14 +65110,6 @@ Advisor: Xavier Giró i Nieto
 Barcelona, July 2015"
 b49affdff167f5d170da18de3efa6fd6a50262a2,Linking Names and Faces : Seeing the Problem in Different Ways,"Author manuscript, published in ""Workshop on Faces in 'Real-Life' Images: Detection, Alignment, and Recognition, Marseille : France
 (2008)"""
-b4b0bf0cbe1a2c114adde9fac64900b2f8f6fee4,Autonomous Learning Framework Based on Online Hybrid Classifier for Multi-view Object Detection in Video,"Autonomous Learning Framework Based on Online Hybrid
-Classifier for Multi-view Object Detection in Video
-Dapeng Luoa*Zhipeng Zenga Longsheng Weib Yongwen Liua Chen Luoc Jun Chenb Nong Sangd
-School of Electronic Information and Mechanics, China University of Geosciences, Wuhan, Hubei 430074, China
-School of Automation, China University of Geosciences, Wuhan, Hubei 430074, China
-Huizhou School Affiliated to Beijing Normal University, Huizhou 516002, China
-dNational Key Laboratory of Science and Technology on Multispectral Information Processing, School of Automation, Huazhong
-University of Science and Technology, Wuhan, 430074, China"
 b4ee64022cc3ccd14c7f9d4935c59b16456067d3,Unsupervised Cross-Domain Image Generation,"Unsupervised Cross-Domain Image Generation
 Xinru Hua, Davis Rempe, and Haotian Zhang"
 b40881a905cf6c4963658df4f64b860f9b1755fe,Unrestricted Facial Geometry Reconstruction Using Image-to-Image Translation,"Unrestricted Facial Geometry Reconstruction Using Image-to-Image Translation
@@ -76881,9 +65152,6 @@ Palabras clave: Expresiones faciales, clasiﬁcaci´on, m´aquinas de soporte
 vectorial,modelos activos de apariencia.
 Facial Expressions Recognition Based on Facial
 Landmarks Dynamics"
-a0fd85b3400c7b3e11122f44dc5870ae2de9009a,Learning Deep Representation for Face Alignment with Auxiliary Attributes,"Learning Deep Representation for Face
-Alignment with Auxiliary Attributes
-Zhanpeng Zhang, Ping Luo, Chen Change Loy, Member, IEEE and Xiaoou Tang, Fellow, IEEE"
 a0541d4a28d90a17cd3eaa9d1797882eacc8ccf0,Improving Person Re-identification via Pose-Aware Multi-shot Matching,"Improving Person Re-identiﬁcation via Pose-aware Multi-shot Matching
 Yeong-Jun Cho and Kuk-Jin Yoon
 Computer Vision Laboratory, GIST, South Korea
@@ -76952,25 +65220,11 @@ S. Muruganantham† and  Dr. T. Jebarajan††,
 Assistant Professor, S.T.Hindu College, Nagercoil.
 Principal, Kings College of Engineering, Chennai.
 that  compensates"
-a012b41fc54060e11744db20ef6d191b290f1879,Unconstrained Face Recognition From Blurred and Illumination with Pose Variant Face Image Using SVM,"ISSN(Online): 2320-9801
-ISSN (Print):  2320-9798
-International Journal of Innovative Research in Computer and Communication Engineering
-(An ISO 3297: 2007 Certified Organization)
-Vol.2, Special Issue 1, March 2014
-Proceedings of International Conference On Global Innovations In Computing Technology (ICGICT’14)
-Department of CSE, JayShriram Group of Institutions, Tirupur, Tamilnadu, India on 6th & 7th March 2014
-Organized by
-Unconstrained Face Recognition From Blurred and
-Illumination with Pose Variant Face Image Using
-Dept. of CSE, PG Student (SE), Sri Krishna College of Engineering and Technology, Coimbatore, Tamilnadu, India1
-C.Indhumathi1"
 a01f9461bc8cf8fe40c26d223ab1abea5d8e2812,Facial Age Estimation Through the Fusion of Texture and Local Appearance Descriptors,"Facial Age Estimation Through the Fusion of Texture
 nd local appearance Descriptors
 Ivan Huerta1, Carles Fern´andez2, and Andrea Prati1
 DPDCE, University IUAV, Santa Croce 1957, 30135 Venice, Italy
 Herta Security, Pau Claris 165 4-B, 08037 Barcelona, Spain"
-a05a770bb2b7778e195a578006482926dfc1af82,Learning to Recognize Pedestrian Attribute,"Learning to Recognize Pedestrian Attribute
-Yubin Deng, Ping Luo, Chen Change Loy, Member, IEEE, and Xiaoou Tang, Fellow, IEEE"
 a0e5afb1237d47f7a8ac66e7b5ada24cec5222cb,Semantic pooling for image categorization using multiple kernel learning,"SEMANTIC POOLING FOR IMAGE CATEGORIZATION USING MULTIPLE KERNEL
 LEARNING
 Thibaut Durand(1,2), David Picard(1), Nicolas Thome(2), Matthieu Cord(2)
@@ -77005,13 +65259,6 @@ Using Arm 11
 K. Sri Krishna Aditya1, T. Surya Kavita2, U. Yedukondalu3
 Assistant Professor, 2Associate Professor, 3Head of the Department E.C.E.
 Aditya Engineering College, 2Aditya Engineering College, 3Aditya Engineering College"
-a0ae4ffe252f32514240cf6d82d52538de5fb78c,AN ALGORITHM FOR PEDESTRIAN DETECTION IN MULTISPECTRAL IMAGE SEQUENCES,"AN ALGORITHM FOR PEDESTRIAN DETECTION IN MULTISPECTRAL IMAGE
-SEQUENCES
-V. V. Kniaza,b, V. V. Fedorenkoa (cid:3)
-State Res. Institute of Aviation Systems (GosNIIAS), Moscow, Russia - (vl.kniaz,
-Moscow Institute of Physics and Technology (MIPT), Russia
-KEY WORDS: pedestrian detection, optical flow, thermal vision, mobile robots
-Commission II, WG II/5"
 a079309d28b6f8753ca26a789bd0bc43de9bd9f8,Interpretable Counting for Visual Question Answering,"Published as a conference paper at ICLR 2018
 INTERPRETABLE COUNTING FOR VISUAL QUESTION
 ANSWERING
@@ -77029,10 +65276,6 @@ Institute of Computer Science, FORTH
 Computer Science Department, UOC
 Antonis Argyros1,2"
 a0c37f07710184597befaa7e6cf2f0893ff440e9,Fast Retinomorphic Event Stream for Video Recognition and Reinforcement Learning,
-a0703bef11c978cc8faf05eb229e29a889f8a0b1,Superpixel Hierarchy,"Superpixel Hierarchy
-Xing Wei, Qingxiong Yang, Member, IEEE, Yihong Gong, Member, IEEE, Ming-Hsuan Yang, Senior
-Member, IEEE, Narendra Ahuja, Fellow, IEEE,
-http://www.cs.cityu.edu.hk/∼qiyang/publications/SH/"
 a098fab95db313d8bd2a5175b519d7de5a3a675a,Performance evaluation and comparison of PCA Based human face recognition methods for distorted images,"Int. J. Mach. Learn. & Cyber. (2011) 2:245–259
 DOI 10.1007/s13042-011-0023-2
 O R I G I N A L A R T I C L E
@@ -77137,26 +65380,6 @@ Universitat Pompeu Fabra (DTIC)
 Barcelona, Spain
 Centre de Visió per Computador
 Barcelona, Spain"
-434300db45ea1b0b36b0c606ca728aaaed235275,The Effect of Distinctiveness in Recognizing Average Face: Human Recognition and Eigenface Based Machine Recognition,"IEICE TRANS. INF. & SYST., VOL.E96–D, NO.3 MARCH 2013
-PAPER SpecialSectiononFacePerceptionandRecognition
-The Effect of Distinctiveness in Recognizing Average Face: Human
-Recognition and Eigenface Based Machine Recognition
-Naiwala P. CHANDRASIRI†∗a), Ryuta SUZUKI†, Nobuyuki WATANABE†∗∗, Nonmembers,
-nd Hiroshi YAMADA†, Member
-SUMMARY
-Face perception and recognition have attracted more at-
-tention recently in multidisciplinary ﬁelds such as engineering, psychol-
-ogy, neuroscience, etc. with the advances in physical/physiological mea-
-surement and data analysis technologies.
-In this paper, our main inter-
-est is building computational models of human face recognition based on
-psychological experiments. We specially focus on modeling human face
-recognition characteristics of average face in the dimension of distinctive-
-ness. Psychological experiments were carried out to measure distinctive-
-ness of face images and their results are explained by computer analysis
-results of the images. Two psychological experiments, 1) Classical exper-
-iment of distinctiveness rating and, 2) Novel experiment of recognition of
-n average face were performed."
 43cb50f669a0d492256d11c6cc4128ba0ce79a3e,Per-Pixel Feedback for improving Semantic Segmentation,"Indian Institute of Technology Roorkee
 Department of Mathematics
 Per-Pixel Feedback for improving Semantic
@@ -77214,13 +65437,6 @@ for Facial Expression Recognition
 Caifeng Shan and Tommaso Gritti
 Philips Research, High Tech Campus 36, Eindhoven 5656 AE, The Netherlands
 {caifeng.shan,"
-433bb809862f472d6f7f82c5e1f677d194c3fbb3,An Experimental Investigation about the Integration of Facial Dynamics in Video-Based Face Recognition,"Electronic Letters on Computer Vision and Image Analysis 5(1):1-13, 2005
-An Experimental Investigation about the Integration of Facial
-Dynamics in Video-Based Face Recognition
-Abdenour Hadid and Matti Pietik¨ainen
-Machine Vision Group, Infotech Oulu and Department of Electrical and Information Engineering
-P.O. Box 4500 FIN-90014 University of Oulu, Finland
-Received 14 December 2004; accepted 1 February 2005"
 4344413b7814b2ba99cc79ead2903f259e98ed4b,Modelling Uncertainty in Representation of Facial Features for Face Recognition,"We are IntechOpen,
 the world’s leading publisher of
 Open Access books
@@ -77274,10 +65490,6 @@ in rats exposed to valproic acid prenatally
 Catherine E. Barrett 1,2*, Thomas M. Hennessey1,2, Katelyn M. Gordon1,2, Steve J. Ryan1,2, Morgan L. McNair1,2,
 Kerry J. Ressler3 and Donald G. Rainnie1,2
 Open Access"
-43ae4867d058453e9abce760ff0f9427789bab3a,Graph Embedded Nonparametric Mutual Information for Supervised Dimensionality Reduction,"Graph Embedded Nonparametric Mutual
-Information For Supervised
-Dimensionality Reduction
-Dimitrios Bouzas, Nikolaos Arvanitopoulos, Student Member, IEEE, and Anastasios Tefas, Member, IEEE"
 439da29cf857151f386e6af488b2d60c098c4fd8,Person Authentication Using Color Face Recognition,"Kiran Davakhar et al. Int. Journal of Engineering Research and Applications               www.ijera.com
 Vol. 3, Issue 5, Sep-Oct 2013, pp.178-182
 RESEARCH ARTICLE                                                                               OPEN ACCESS
@@ -77286,10 +65498,6 @@ Kiran Davakhar1, S. B. Mule2, Achala Deshmukh3
 (Department of E&TC, Sinhgad COE, Vadgaon, Pune, Pune University, India)
 (Department of E&TC, Sinhgad COE, Vadgaon, Pune, Pune University, India)
 (Department of E&TC, Sinhgad COE, Vadgaon, Pune, Pune University, India)"
-434a0aebf3522638d75614b0de1f0c2dcc1b19f1,Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontiers,"Visual Analytics in Deep Learning:
-An Interrogative Survey for the Next Frontiers
-Fred Hohman, Member, IEEE, Minsuk Kahng, Member, IEEE, Robert Pienta, Member, IEEE,
-nd Duen Horng Chau, Member, IEEE"
 43d4927f5113c5e376ab05d41e33063a6d06d727,Pedestrian Detection : Exploring Virtual Worlds,"Pedestrian Detection: Exploring Virtual Worlds
 Javier Mar´ın
 Computer Vision Center,
@@ -77341,30 +65549,6 @@ Faculty of Computer Science and Information Technology, University Putra Malaysi
 E-mail:
 systems
 surveillance"
-432326edbc598774315a0def91d1fc224d732922,Classification of Diseased Arecanut based on Texture Features,"International Journal of Computer Applications (0975 – 8887)
-Recent Advances in Information Technology, 2014
-Classification of Diseased Arecanut based on Texture
-Suresha M
-Department of Computer
-Science
-Kuvempu University
-Karnataka, India
-Features
-Ajit Danti
-Department of MCA
-JNN College of Engineering
-Karnataka, India
-S. K Narasimhamurthy
-Department of Mathematics
-Kuvempu University
-Karnataka, India"
-43fb9efa79178cb6f481387b7c6e9b0ca3761da8,Mixture of parts revisited: Expressive part interactions for Pose Estimation,"Mixture of Parts Revisited: Expressive Part Interactions for Pose Estimation
-Anoop R Katti
-IIT Madras
-Chennai, India
-Anurag Mittal
-IIT Madras
-Chennai, India"
 43167658228d59b81d48fce14bba4ae616b866ec,Face Recognition Using Multi-Classifier,"Applied Mathematical Sciences, Vol. 6, 2012, no. 45, 2235 - 2244
 Face Recognition Using Multi-Classifier
 Mohammad Said El-Bashir
@@ -77428,10 +65612,6 @@ Pedestrian-Agents
 Bolei Zhou · Xiaoou Tang · Xiaogang Wang
 Received: 9 September 2013 / Accepted: 24 May 2014
 © Springer Science+Business Media New York 2014"
-4338b6137ee0d02f4bebd14e9a2430c837590209,Automatic eyeglasses removal from face images,"Automatic Eyeglasses Removal
-from Face Images
-Chenyu Wu, Ce Liu, Heung-Yueng Shum, Member, IEEE, Ying-Qing Xu, and
-Zhengyou Zhang, Senior Member, IEEE"
 434bf475addfb580707208618f99c8be0c55cf95,DeXpression: Deep Convolutional Neural Network for Expression Recognition,"UNDER CONSIDERATION FOR PUBLICATION IN PATTERN RECOGNITION LETTERS
 DeXpression: Deep Convolutional Neural
 Network for Expression Recognition
@@ -77439,15 +65619,6 @@ Peter Burkert∗‡, Felix Trier∗‡, Muhammad Zeshan Afzal†‡,
 Andreas Dengel†‡ and Marcus Liwicki‡
 German Research Center for Artiﬁcial Intelligence (DFKI), Kaiserslautern, Germany
 University of Kaiserslautern, Gottlieb-Daimler-Str., Kaiserslautern 67663, Germany"
-43d073d3fdc22f0d74793fdac47ff56b66c95990,Online Localization and Prediction of Actions and Interactions,"Online Localization and Prediction of
-Actions and Interactions
-Khurram Soomro, Member, IEEE, Haroon Idrees, Member, IEEE, and Mubarak Shah, Fellow, IEEE"
-4335d53e763b2caf20f06928cd420ae09e5041ad,Discrete-continuous optimization for multi-target tracking,"Discrete-Continuous Optimization for Multi-Target Tracking
-Anton Andriyenko1
-Konrad Schindler2
-Stefan Roth1
-Department of Computer Science, TU Darmstadt
-Photogrammetry and Remote Sensing Group, ETH Z¨urich"
 439ac8edfa1e7cbc65474cab544a5b8c4c65d5db,Face authentication with undercontrolled pose and illumination,"SIViP (2011) 5:401–413
 DOI 10.1007/s11760-011-0244-6
 ORIGINAL PAPER
@@ -77460,20 +65631,6 @@ Online Multi-Target Tracking
 with Uniﬁed Handling of Complex Scenarios
 Huaizu Jiang, Jinjun Wang, Yihong Gong, Senior Member, IEEE
 Na Rong, Zhenhua Chai, and Nanning Zheng, Fellow, IEEE"
-43e77b5157b0fa0f365808e26af287c3164e002f,UnFlow: Unsupervised Learning of Optical Flow With a Bidirectional Census Loss,"UnFlow: Unsupervised Learning of Optical Flow
-with a Bidirectional Census Loss
-Simon Meister, Junhwa Hur, Stefan Roth
-Department of Computer Science
-TU Darmstadt, Germany"
-43bf6489abd63992b82f2008b4417a1638955f0c,Illumination Spaces in YDB and CMU-PIE,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 31, NO. 2, FEBRUARY 2009
-Short Papers___________________________________________________________________________________________________
-Principal Angles Separate Subject
-Illumination Spaces in YDB and CMU-PIE
-J. Ross Beveridge, Member, IEEE,
-Bruce A. Draper, Member, IEEE,
-Jen-Mei Chang, Michael Kirby,
-Holger Kley, and
-Chris Peterson"
 434c2c53af7b3cb3c0a47583a372fa3dc8143951,DeeSIL: Deep-Shallow Incremental Learning,"DeeSIL: Deep-Shallow Incremental Learning
 Eden Belouadah, Adrian Popescu
 CEA, LIST, Vision and Content Engineering Lab, F-91191 Gif-sur-Yvette, France"
@@ -77526,27 +65683,6 @@ b0554290e1c1d19ee5378485fadd1ff99c31bf2d,VANETs Meet Autonomous Vehicles: A Mult
 A Multimodal 3D Environment Learning Approach
 Yassine Maalej, Sameh Sorour, Ahmed Abdel-Rahim and Mohsen Guizani
 University of Idaho, Moscow, ID, USA"
-b0771b7ca52022b37a563464f823af67c0b36c03,Image Retrieval Technique Using Local Binary Pattern ( LBP ),"International Journal of Science and Research (IJSR)
-ISSN (Online): 2319-7064
-Index Copernicus Value (2013): 6.14 | Impact Factor (2013): 4.438
-Image Retrieval Technique Using Local Binary
-Pattern (LBP)
-Miss. Priyanka Pawar1, P.P.Belagali2
-P.G Student, Department of Electronics Engineering, Shivaji University, Dr.J.J.M.C.O.E Jaysingpur, Kolhapur, India
-Associate Professor, Department of Electronics Engineering, Shivaji University, Dr.J.J.M.C.O.E Jaysingpur, Kolhapur, India"
-b0b628bda8a6c4267eeaf91420b8610400ff398f,Intact emotion facilitation for nonsocial stimuli in autism: is amygdala impairment in autism specific for social information?,"Journal of the International Neuropsychological Society (2008), 14, 42–54.
-Copyright © 2008 INS. Published by Cambridge University Press. Printed in the USA.
-DOI: 10.10170S1355617708080107
-Intact emotion facilitation for nonsocial stimuli in autism:
-Is amygdala impairment in autism specific
-for social information?
-MIKLE SOUTH,1,2 SALLY OZONOFF,3 YANA SUCHY,1,4 RAYMOND P. KESNER,1,4
-WILLIAM M. McMAHON,2,4 and JANET E. LAINHART2,4
-Department of Psychology, University of Utah, Salt Lake City, Utah
-Department of Psychiatry, University of Utah School of Medicine and Utah Autism Research Project, Salt Lake City, Utah
-M.I.N.D. Institute, Department of Psychiatry and Behavioral Sciences, University of California–Davis, Sacramento, California
-The Brain Institute at the University of Utah, Salt Lake City, Utah
-(Received April 25, 2007; Final Revision July 11, 2007; Accepted July 18, 2007)"
 b05ac3b2286c30fcab385f682b3519a823857112,UvA-DARE ( Digital Academic Repository ) Spatial frequency information modulates response inhibition and decision-making processes,"UvA-DARE (Digital Academic Repository)
 Spatial frequency information modulates response inhibition and decision-making
 processes
@@ -77658,9 +65794,6 @@ Zhuowen Tu
 Dept. of CogSci"
 b0158b26f01d5fa18aac51ece055cad9a12f6d87,Memory-based Gait Recognition,"Pages 82.1-82.12
 DOI: https://dx.doi.org/10.5244/C.30.82"
-b0760764dc573b519f76d5a79531d49af333c67a,Neural Style Transfer: A Review,"Neural Style Transfer: A Review
-Yongcheng Jing, Yezhou Yang, Member, IEEE, Zunlei Feng, Jingwen Ye,
-Yizhou Yu, Senior Member, IEEE, and Mingli Song, Senior Member, IEEE"
 b09b693708f412823053508578df289b8403100a,Two-Stream SR-CNNs for Action Recognition in Videos,"WANG et al.: TWO-STREAM SR-CNNS FOR ACTION RECOGNITION IN VIDEOS
 Two-Stream SR-CNNs for Action
 Recognition in Videos
@@ -77687,13 +65820,6 @@ b0de0892d2092c8c70aa22500fed31aa7eb4dd3f,A Robust and Efficient Video Representa
 A robust and efﬁcient video representation for action recognition
 Heng Wang · Dan Oneata · Jakob Verbeek · Cordelia Schmid
 Received: date / Accepted: date"
-b02342a423eef6e19f473eba26b067405b525f16,Co-Occurrence Matrix Analysis-Based Semi-Supervised Training for Object Detection,"CO-OCCURRENCE MATRIX ANALYSIS-BASED SEMI-SUPERVISED TRAINING FOR
-OBJECT DETECTION
-Min-Kook Choi1, Jaehyeong Park1, Jihun Jung1, Heechul Jung2, Jin-Hee Lee1,
-Woong Jae Won1, Woo Young Jung1, Jincheol Kim3, and Soon Kwon1∗
-DGIST, Daegu, Republic of Korea1
-KAIST, Daejeon, Republic of Korea2
-SK Telecom, Seoul, Republic of Korea3"
 b07582d1a59a9c6f029d0d8328414c7bef64dca0,Employing Fusion of Learned and Handcrafted Features for Unconstrained Ear Recognition,"Employing Fusion of Learned and Handcrafted
 Features for Unconstrained Ear Recognition
 Maur´ıcio Pamplona Segundo∗†