Gender classification of human faces using inference through contradictions

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations

Abstract

We present an empirical study of gender classification of human faces, using new learning methodology called inference through contradictions, introduced in [9]. This approach allows to incorporate a priori knowledge in the form of additional (unlabeled) samples, called the Universum, into the supervised learning process. Application of this methodology to gender classification shows that using this approach enables better generalization over standard SVM classification (using labeled data alone).

Original languageEnglish (US)
Title of host publication2008 International Joint Conference on Neural Networks, IJCNN 2008
Pages746-750
Number of pages5
DOIs
StatePublished - Nov 24 2008
Event2008 International Joint Conference on Neural Networks, IJCNN 2008 - Hong Kong, China
Duration: Jun 1 2008Jun 8 2008

Publication series

NameProceedings of the International Joint Conference on Neural Networks

Other

Other2008 International Joint Conference on Neural Networks, IJCNN 2008
Country/TerritoryChina
CityHong Kong
Period6/1/086/8/08

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