Sample reconstruction with deep autoencoder for one sample per person face recognition - Zhang, Yan; Peng, Hua (IET computer vision, 2017)
Keywords: AR database; CDA; class-specific deep autoencoder; CMU database; extended Yale face database B; face recognition; image classification; image coding; image reconstruction; image representation; minimum L2 distance; multisample subject to single-sample subject intraclass variations; one sample per person face recognition; OSPP face recognition; principal component analysis; principle component analysis; regression analysis; Research Article; sample reconstruction; softmax regression; sparse represented-based classifier; CDA; one sample per person face recognition; image classification; AR database; softmax regression; class-specific deep autoencoder; regression analysis; sparse represented-based classifier; minimum L2 distance; image reconstruction; CMU database; extended Yale face database B; principle component analysis; image representation; face recognition; OSPP face recognition; multisample subject to single-sample subject intraclass variations; image coding; sample reconstruction; principal component analysis