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Home> Schools> University of Wisconsin, Madison> Electrical and Computer Engr (ECE) > ECE 539> Face Recognition based on Radial Basis Function and Clustering Algorithm

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UW-Madison ECE 539 - Face Recognition based on Radial Basis Function and Clustering Algorithm

School name University of Wisconsin, Madison

Course Ece 539- Introduction to Artificial Neural Network and Fuzzy Systems

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Slide 1Face Recognition taskPart IPart IPart IISlide 6Face Recognition based on Radial Basis Function and Clustering AlgorithmYuanfeng Gao2008/12/12Face 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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 accuracyPart IPart IIRecognize human facesAccomplish experiments to apply K-means and subtractive clustering algorithmChoosing a data base to perform the experiment.Thank

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UW-Madison ECE 539 - Face Recognition based on Radial Basis Function and Clustering Algorithm

School: University of Wisconsin, Madison

Course: Ece 539- Introduction to Artificial Neural Network and Fuzzy Systems

Pages: 6

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