Close
Metadata

%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2012/07.05.19.16
%2 sid.inpe.br/sibgrapi/2012/07.05.19.16.04
%A Safaa El-Din, Yomna,
%A Moustafa, Mohamed N.,
%A Mahdi, Hani,
%@affiliation Department of Computer and Systems Engineering, Ain Shams University, Cairo, Egypt, yomna.safaa-eldin@eng.asu.edu.eg
%@affiliation Department of Computer Science and Engineering, American University in Cairo, New Cairo, Egypt, Email: moustafa@ieee.org, m.moustafa@aucegypt.edu
%@affiliation Department of Computer and Systems Engineering, Ain Shams University, Cairo, Egypt, Email: hani.mahdi@eng.asu.edu.eg
%T A mixture of two gender classification experts
%B Conference on Graphics, Patterns and Images, 24 (SIBGRAPI)
%D 2011
%E Lewiner, Thomas,
%E Torres, Ricardo,
%S Proceedings
%8 Aug. 28 - 31, 2011
%J Los Alamitos
%I IEEE Computer Society Conference Publishing Services
%C Maceió
%K gender classification, committee machines, face image analysis, Naive Bayes.
%X This paper presents a novel method for combining the outputs of different gender classification techniques based on facial images. Merging the methods is performed by a committee machine using the Bayesian theorem. We implement and compare several well-known individual classifiers on four different datasets, then we experiment the proposed machine, and show that it significantly improves the accuracy of classification compared to individual classifiers. We also include results that address the effect of scale on the performance of classifiers.
%@language en
%3 101351_CameraReady.pdf


Close