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Face Recognition Using Principal Component Analysis and RBF Neural Networks
2008
2008 First International Conference on Emerging Trends in Engineering and Technology
In this paper, an efficient method for face recognition using principal component analysis (PCA) and radial basis function (RBF) neural networks is presented. Recently, the PCA has been extensively employed for face recognition algorithms. It is one of the most popular representation methods for a face image. It not only reduces the dimensionality of the image, but also retains some of the variations in the image data. After performing the PCA, the hidden layer neurons of the RBF neural
doi:10.1109/icetet.2008.104
dblp:conf/icetet/ThakurSBNK08
fatcat:kfrkko7ourbxtbnqjhdwt5zghq