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Face Recognition based on Radial Basis Function and Clustering Algorithm

Face Recognition based on Radial Basis Function and Clustering Algorithm. Yuanfeng Gao 2008/12/12. Face Recognition task. Various methods Neural Network approach: - Can recessively express many rules for face recognition and has much stronger adaptability by training networks. Part I.

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Face Recognition based on Radial Basis Function and Clustering Algorithm

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  1. Face Recognition based on Radial Basis Function and Clustering Algorithm Yuanfeng Gao 2008/12/12

  2. Face Recognition task • Various methods • Neural Network approach: - Can recessively express many rules for face recognition and has much stronger adaptability by training networks.

  3. Part I • Radial basis function (RBF) neural networks is compared with other neural network techniques - K-means clustering algorithm - Subtractive clustering algorithm • Improve the RBF and classification accuracy

  4. Part I

  5. Part II • Recognize human faces • Accomplish experiments to apply K-means and subtractive clustering algorithm • Choosing a data base to perform the experiment.

  6. Thank you

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