Selecting suitable deep learning network for face recognition

Abstract

In this paper is given problems in face recognition methods and algorithms, ways of improving of recognition accuracy and decreasing errors. There are false acceptance and rejection errors in face recognition and these errors are decreased by normalization method when detected occlusion faces. For increasing face recognition accuracy and speed is proposed combining of deep learning networks and optimization of filter size.