Multi-expression face recognition using neural networks and feature approximation
ISMIS'06 Proceedings of the 16th international conference on Foundations of Intelligent Systems
Intelligent face recognition: local versus global pattern averaging
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
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This paper investigates a feature selection and classification technique for face recognition using genetic algorithms and artificial neural networks. The experiments using separate facial features and combined facial features have been conducted on a face image dataset which is extracted from FERET benchmark database and was used in our previous study. The experiments using just combined features have also been conducted on an extended version of this dataset. The new experiments have achieved much better recognition rate than some of the existing face recognition techniques and significantly improved our previously published results. A detailed comparative analysis of experimental results is included in this paper.