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diff --git a/reports/stats/unknown_papers.csv b/reports/stats/unknown_papers.csv
index 0e09b9e9..04d23f8d 100644
--- a/reports/stats/unknown_papers.csv
+++ b/reports/stats/unknown_papers.csv
@@ -3256,20 +3256,6 @@ Signal Processing Laboratory (LTS5),
 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."

-a3d78bc94d99fdec9f44a7aa40c175d5a106f0b9,Recognizing Violence in Movies,"Recognizing Violence in Movies
-CIS400/401 Project Final Report
-Lei Kang
-Univ. of Pennsylvania
-Philadelphia, PA
-Matteus Pan
-Univ. of Pennsylvania
-Philadelphia, PA
-Ben Sapp
-Univ. of Pennsylvania
-Philadelphia, PA
-Ben Taskar
-Univ. of Pennsylvania
-Philadelphia, PA"

 a3eab933e1b3db1a7377a119573ff38e780ea6a3,Sparse Representation for accurate classification of corrupted and occluded facial expressions,"978-1-4244-4296-6/10/$25.00 ©2010 IEEE
 ICASSP 2010"

 a3a34c1b876002e0393038fcf2bcb00821737105,Face Identification across Different Poses and Illuminations with a 3D Morphable Model,"Face Identification across Different Poses and Illuminations
@@ -7238,13 +7224,6 @@ M%&QRS1575J(1)whereVWXisapowerweightingconstant.2.1.ConvergencetoExtrinsicZ-
 bei.i.d.randomvectorswithvaluesinacompactsubsetofandLebesgueden-sity\.Let]?_,aVb]anddefineZF]7VHf].Then,withprobability(w.p.)gh""jk<JDCFH
moDJDCp\mFrHtr(2)whereoDJDCisaconstantindependentof\.Furthermore,themeanlengthuv<JDCFHwf
mconvergestothesamelimit.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)"

 74156a11c2997517061df5629be78428e1f09cbd,"Preparatory coordination of head, eyes and hands: Experimental study at intersections","Cancún Center, Cancún, México, December 4-8, 2016
 978-1-5090-4846-5/16/$31.00 ©2016 IEEE"

-748e72af01ba4ee742df65e9c030cacec88ce506,Discriminative Regions Selection for Facial Expression Recognition,"Discriminative Regions Selection for Facial Expression
-Recognition
-Hazar Mliki1 and Mohamed Hammami2
-1 MIRACL-FSEG, University of Sfax
-018 Sfax, Tunisia
-MIRACL-FS, University of Sfax
-018 Sfax, Tunisia"

 749d605dd12a4af58de1fae6f5ef5e65eb06540e,Multi-Task Video Captioning with Video and Entailment Generation,"Multi-Task Video Captioning with Video and Entailment Generation
 Ramakanth Pasunuru and Mohit Bansal
 UNC Chapel Hill
@@ -7754,13 +7733,6 @@ e-mail:"
 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"

-8a3bb63925ac2cdf7f9ecf43f71d65e210416e17,ShearFace: Efficient Extraction of Anisotropic Features for Face Recognition,"ShearFace: Efficient Extraction of Anisotropic
-Features for Face Recognition
-Mohamed Anouar Borgi1, Demetrio Labate2
-Research Groups on Intelligent Machines,
-University of Sfax,
-Sfax 3038, Tunisia
-nd  anisotropic"

 8adb2fcab20dab5232099becbd640e9c4b6a905a,Beyond Euclidean Eigenspaces: Bayesian Matching for Visual Recognition,"Beyond Euclidean Eigenspaces:
 Bayesian Matching for Visual Recognition
 Baback Moghaddam
@@ -9635,11 +9607,6 @@ University of California at Berkeley
 Technical Report No. UCB/EECS-2012-53
 http://www.eecs.berkeley.edu/Pubs/TechRpts/2012/EECS-2012-53.html
 May 1, 2012"

-3634b4dd263c0f330245c086ce646c9bb748cd6b,Temporal Localization of Fine-Grained Actions in Videos by Domain Transfer from Web Images,"Temporal Localization of Fine-Grained Actions in Videos
-y Domain Transfer from Web Images
-Chen Sun* Sanketh Shetty† Rahul Sukthankar† Ram Nevatia*
-*University of Southern California
-Google, Inc."

 5c6de2d9f93b90034f07860ae485a2accf529285,Compensating for pose and illumination in unconstrained periocular biometrics,"Int. J. Biometrics, Vol. X, No. Y, xxxx
 Compensating for pose and illumination in
 unconstrained periocular biometrics
@@ -12373,15 +12340,6 @@ Department of Electronics Engineering
 K.D.K. College of Engineering Nagpur, India"

 dcb44fc19c1949b1eda9abe998935d567498467d,Ordinal Zero-Shot Learning,"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17)
 labelunseen labelFigure1:Supervisionintensityfordifferentlabels.Greenrepre-sentsseenlabelsandredrepresentsunseenlabels.Thegroundtruthlabelofthisinstanceis“Good”,soithasthestrongestsupervisionintensity.Although“Common”isanunseenlabel,itstillhascertainsupervisioninformationbecauseitiscloselyrelatedto“Good”.classifier;[ZhangandSaligrama,2016]learnsajointlatentspaceusingstructuredlearning.Thedifficultyinobtainingthesideinformationorusingothertechniquestoprocessthesideinformationarethemostseriousissuesformanyexistingzero-shotlearningmethods.Fortheattribute-basedmethods,humanexpertsareneededtolabelattributesandthisisverytime-consumingandnoteasytoobtainthediscriminativecategory-levelattributes.Somemethodsdiscoverattributesinteractively[ParikhandGrau-man,2011][Bransonetal.,2010],butthisalsorequiresla-borioushumanparticipation.Althoughmanyalgorithmscandiscoverattribute-relatedconceptsontheWeb[Rohrbachetal.,2010][Bergetal.,2010],theycanalsobebiasedorlackinformationthatiscriticaltoaparticulartask[ParikhandGrauman,2011].Forthetextcorpora-basedmethods,theyfirstrequirealargelanguagecorpora,suchasWikipedia,andthenneedtolearnwordrepresentation[Socheretal.,2013]orusestandardNaturalLanguageProcessing(NLP)techniquestoproduceclassdescriptions[Elhoseinyetal.,2013].Itishardtoguaranteethecorrectnessofsuchclassdescriptionsforzero-shotlearning.Conclusively,althoughsideinforma-tionishelpfulforzero-shotlearning,ithasmanydisadvan-tages.Generatingthesesideinformationisverytediousandsometimeswecannotknowwhichsideinformationistrulywanted.IfwedependonhumanlabororNLPtechniques,noisysideinformationwillbecomealmostinevitableandin-fluencethefinalperformance.Toavoidtheseproblems,itisimportanttosolvezero-shotlearninginwhateverpossiblecasesthathavesomepropertieswecanutilizetoavoidusingsideinformation."

-dc7df544d7c186723d754e2e7b7217d38a12fcf7,Facial expression recognition using salient facial patches,"Facial expression recognition using salient facial patches
-Hazar Mliki
-MIRACL-ENET’COM
-University of Sfax
-Tunisia (3018), Sfax
-Mohamed Hammami
-MIRACL-FSS
-University of Sfax
-Tunisia (3018), Sfax"

 dc2e805d0038f9d1b3d1bc79192f1d90f6091ecb,Face Recognition and Facial Attribute Analysis from Unconstrained Visual Data,

 dc974c31201b6da32f48ef81ae5a9042512705fe,Am I Done? Predicting Action Progress in Videos,"Am I done? Predicting Action Progress in Video
 Federico Becattini1, Tiberio Uricchio1, Lorenzo Seidenari1,
@@ -12617,11 +12575,6 @@ Seattle, Washington, USA
 Narsimha Raju
 IIT Bombay
 Mumbai, Maharashtra, India"

-aadf4b077880ae5eee5dd298ab9e79a1b0114555,Using Hankel matrices for dynamics-based facial emotion recognition and pain detection,"Dynamics-based Facial Emotion Recognition and Pain Detection
-Using Hankel Matrices for
-Liliana Lo Presti and Marco La Cascia
-DICGIM - University of Palermo
-V.le delle Scienze, Ed. 6, 90128 Palermo (Italy)"

 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
@@ -13418,29 +13371,9 @@ 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"

-e1ab3b9dee2da20078464f4ad8deb523b5b1792e,Pre-Training CNNs Using Convolutional Autoencoders,"Pre-Training CNNs Using Convolutional
-Autoencoders
-Maximilian Kohlbrenner
-TU Berlin
-Russell Hofmann
-TU Berlin
-Sabbir Ahmmed
-TU Berlin
-Youssef Kashef
-TU Berlin"

 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"

-e1f6e2651b7294951b5eab5d2322336af1f676dc,Emotional Avatars: Appearance Augmentation and Animation based on Facial Expression Analysis,"Appl. Math. Inf. Sci. 9, No. 2L, 461-469 (2015)
-Applied Mathematics & Information Sciences
-An International Journal
-http://dx.doi.org/10.12785/amis/092L21
-Emotional Avatars: Appearance Augmentation and
-Animation based on Facial Expression Analysis
-Taehoon Cho, Jin-Ho Choi, Hyeon-Joong Kim and Soo-Mi Choi∗
-Department of Computer Science and Engineering, Sejong University, 98 Gunja, Gwangjin, Seoul 143-747, Korea
-Received: 22 May 2014, Revised: 23 Jul. 2014, Accepted: 24 Jul. 2014
-Published online: 1 Apr. 2015"

 e1d726d812554f2b2b92cac3a4d2bec678969368,Human Action Recognition Bases on Local Action Attributes,"J Electr Eng Technol.2015; 10(?): 30-40
 http://dx.doi.org/10.5370/JEET.2015.10.2.030
 ISSN(Print)
@@ -17139,26 +17072,6 @@ Hemanta Sapkota
 Daniel Rosser
 Yusuf Pisan
 Games Studio, Faculty of Engineering and IT, University of Technology, Sydney"

-8bed7ff2f75d956652320270eaf331e1f73efb35,Emotion Recognition in the Wild using Deep Neural Networks and Bayesian Classifiers,"Emotion Recognition in the Wild using
-Deep Neural Networks and Bayesian Classifiers
-Luca Surace
-Elena Ba(cid:138)ini S¨onmez
-University of Calabria - DeMACS
-Via Pietro Bucci
-Rende (CS), Italy
-Massimiliano Patacchiola
-Plymouth University - CRNS
-Portland Square PL4 8AA
-Plymouth, United Kingdom
-c.uk
-Istanbul Bilgi University - DCE
-Eski Silahtaraa Elektrik Santral Kazm
-Karabekir Cad. No: 2/13 34060 Eyp
-Istanbul, Turkey
-William Spataro
-University of Calabria - DeMACS
-Via Pietro Bucci
-Rende (CS), Italy"

 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