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authoradamhrv <adam@ahprojects.com>2018-12-15 19:57:49 +0100
committeradamhrv <adam@ahprojects.com>2018-12-15 19:57:49 +0100
commit82b2c0b5d6d7baccbe4d574d96e18fe2078047d7 (patch)
treea8784b7ec2bc5a0451c252f66a6b786f3a2504f5 /scraper/datasets/scholar/entries/DEX: Deep EXpectation of apparent age from a single image.csv
parent8e978af21c2b29f678a09701afb3ec7d65d0a6ab (diff)
parentc5b02ffab8d388e8a2925e51736b902a48a95e71 (diff)
Merge branch 'master' of github.com:adamhrv/megapixels_dev
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+Dex: Deep expectation of apparent age from a single image|http://scholar.google.com/https://www.cv-foundation.org/openaccess/content_iccv_2015_workshops/w11/html/Rothe_DEX_Deep_EXpectation_ICCV_2015_paper.html|2015|155|15|12384435539194835187|None|http://scholar.google.com/scholar?cites=12384435539194835187&as_sdt=2005&sciodt=0,5&hl=en|http://scholar.google.com/scholar?cluster=12384435539194835187&hl=en&as_sdt=0,5|None|In this paper we tackle the estimation of apparent age in still face images with deep learning. Our convolutional neural networks (CNNs) use the VGG-16 architecture and are pretrained on ImageNet for image classification. In addition, due to the limited number of apparent age annotated images, we explore the benefit of finetuning over crawled Internet face images with available age. We crawled 0.5 million images of celebrities from IMDB and Wikipedia that we make public. This is the largest public dataset for age prediction to date. We pose the …