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- W2384363515 abstract "An efficient method for face recognition using principal component analysis(PCA),cluster merge algorithm and radial basis function neural networks(RBFNN) is proposed.The dimensions of the human face expression are greatly reduced by using PCA.The hidden layer neurons of the RBFNN is determined by cluster merge algorithm.Then,the spreads of each layer neuron of the RBFNN are estimated according to two kinds of distances: the first are between samples within class and class cluster center,and the second are among class cluster centers.The proposed method has been evaluated using the ATT(formerly ORL) face databases.Experimental results show that the proposed method has encouraging recognition performance just using low face characteristic dimensions." @default.
- W2384363515 created "2016-06-24" @default.
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- W2384363515 date "2009-01-01" @default.
- W2384363515 modified "2023-09-22" @default.
- W2384363515 title "Face Recognition Based on Principal Component Analysis Cluster Merge Algorithm and RBF Neural Networks" @default.
- W2384363515 hasPublicationYear "2009" @default.
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