An effective face verification algorithm to fuse complete features in convolutional neural network - Details

Author：

Ma, Y. (Ma, Y..) | He, J. (He, J..) | Wu, L. (Wu, L..) | Qi, W. (Qi, W..)

Indexed by：

Scopus

Abstract：

Face　verification　for　on　line　application　is　a　difficult　problem　and　many　researchers　have　tried　to　solve　it　by　convolutional　neural　network.　Among　of　them,　most　works　used　the　last-hidden　layer　as　the　feature　of　face,　and　abandoned　the　features　in　the　lower　layers　which　indicate　local　information.　To　remedy　this,　we　extract　features　of　all　layers　in　the　convolutional　neural　net-work,　and　fuse　these　features　together　after　dimensionality　reduction　with　PCA.　Then　these　features　are　utilized　for　face　verification　with　neural　network　classifier.　Experiment　results　show　that　complete　features　can　improve　the　verification　rate　effectively　than　using　the　last-hidden　layer　only.　©　Springer　International　Publishing　Switzerland　2016.

Keyword：

Convolutional neural network; Deep learning; Face verification; Principle component analysis

Author Community：

[ 1 ] [Ma, Y.]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, 100124, China
[ 2 ] [He, J.]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, 100124, China
[ 3 ] [Wu, L.]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, 100124, China
[ 4 ] [Qi, W.]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, 100124, China

Reprint Author's Address：

[Wu, L.]School of Electronic Information and Control Engineering, Beijing University of TechnologyChina

Email：

lfwu@bjut.edu.cn

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Source ：

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ISSN： 0302-9743

Year： 2016

Volume： 9517

Page： 39-46

Language： English

Cited Count：

WoS CC Cited Count：

SCOPUS Cited Count： 9

ESI Highly Cited Papers on the List： 0 Unfold All

WanFang Cited Count：

Chinese Cited Count：

30 Days PV： 4

Affiliated Colleges：

信息科学技术学院本学院/部未明确归属的数据

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