SexNet: A neural network identifies sex from human faces
NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3
The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Gender with Support Faces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Gender Classification with Support Vector Machines
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
PCA for Gender Estimation: Which Eigenvectors Contribute?
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
A Unified Learning Framework for Real Time Face Detection and Classification
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Robust Real-Time Face Detection
International Journal of Computer Vision
Boosting Sex Identification Performance
International Journal of Computer Vision
Evaluation of Gender Classification Methods with Automatically Detected and Aligned Faces
IEEE Transactions on Pattern Analysis and Machine Intelligence
An experimental comparison of gender classification methods
Pattern Recognition Letters
LUT-based Adaboost for gender classification
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Gender recognition: A multiscale decision fusion approach
Pattern Recognition Letters
Ethnicity estimation with facial images
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Gender recognition using a min-max modular support vector machine
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Multi-view gender classification using local binary patterns and support vector machines
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Semi-supervised feature selection for gender classification
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part II
Mixture of experts for classification of gender, ethnic origin, and pose of human faces
IEEE Transactions on Neural Networks
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This paper attacks the problem of gender classification using genetic algorithms. We use local binary patterns and principle component analysis to extract a set of features from face images in the FERET database. The genetic algorithm searches the space of feature subsets to find a set of features that maximizes gender classification accuracy using a support vector machine classifier with hand tuned parameters. Starting with 142 features, the genetic algorithm reduces the feature set size by approximately half resulting in 98.5% accuracy with 100% reliability. This accuracy and reliability are better than when using all 142 features.