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- W2566166288 abstract "In this paper, we propose four techniques for extraction of facial features namely PCA, LDA, KPCA and KFA. The purpose of face feature extraction is to capture certain discriminative features that are unique for a person. In the previous works that uses PCA for face feature extraction involves merging the features and reducing the dimensions that results in some information loss. To overcome this problem, in the first method we used PCA for face feature extraction, LDA for making class labels and NN with RBF for face recognition. Similarly we used the three more techniques namely LDA, KPCA and KFA for face feature extraction and then NN with RBF for face recognition. The proposed method is tested on the ORL database Keywords: 2DPCA, LDA, KPCA, FFNN and KFA." @default.
- W2566166288 created "2017-01-06" @default.
- W2566166288 creator A5090148027 @default.
- W2566166288 date "2015-01-01" @default.
- W2566166288 modified "2023-09-27" @default.
- W2566166288 title "Face Recognition using Radial Basis Neural Network" @default.
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- W2566166288 hasPublicationYear "2015" @default.
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