The role of global and feature based information in gender classification of faces: a comparison of human performance and computational models.

Article

Loomes, M., Davey, N., Frank, R. and Buchala, S. 2005. The role of global and feature based information in gender classification of faces: a comparison of human performance and computational models. International Journal of Neural Systems. 15 (1-2), pp. 121-128. https://doi.org/10.1142/S0129065705000074
TypeArticle
TitleThe role of global and feature based information in gender classification of faces: a comparison of human performance and computational models.
AuthorsLoomes, M., Davey, N., Frank, R. and Buchala, S.
Abstract

This paper describes a global and feature based representation of face images. We use dimensionality reduction techniques and a support vector machine classifier and show this method performs better than more traditional approaches. We present results of human performance on gender classification tasks and evaluate how the different techniques compare with their performance. The results support the psychological plausibility of the global and feature based representation. This aspect of the work was carried out in collaboration with practitioners in Psychiatry at a local hospital. The paper was selected for publication as an expanded version of a paper presented at ICONIP2004.

Research GroupSensoLab group
PublisherWorld Scientific Publishing Co. Pte Ltd
JournalInternational Journal of Neural Systems
ISSN0129-0657
Publication dates
Print01 Apr 2005
Publication process dates
Deposited17 Oct 2008
Output statusPublished
Digital Object Identifier (DOI)https://doi.org/10.1142/S0129065705000074
LanguageEnglish
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