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Human Face Recognition using Soft Computing RBF

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3 Author(s)
W. Pensuwon ; Department of Computer Engineering, Khon Kaen University, Thailand; Department of Computer Science, University of Hertfordshire, United Kingdom. ; R. G. Adams ; N. Davey

This paper proposes a new approach which derived from soft computing, for the construction of radial basis function neural network (RBFN). In training, the centres of radial basis functions are determined by soft computing. Experimental results show that the proposed soft computing RBFN in the human face recognition outperforms the conventional RBFN. It results in less sensitivity to learning parameters, faster convergence and lower recognition error. Hence, soft computing is expected to be a new alternative way to the construction of RBFN model in human face recognition

Published in:

TENCON 2006 - 2006 IEEE Region 10 Conference

Date of Conference:

14-17 Nov. 2006