Ho Sang Jeon, Jae Chan Nam Gung

The Transactions of the Korea Information Processing Society (1994 ~ 2000), Vol. 7, No. 2, pp. 552-557, Feb. 2000
10.3745/KIPSTE.2000.7.2.552,   PDF Download:

Abstract

In this paper, we proposed a face recognition method that uses GA-BP(Genetic Algorithm-Back propagation Network) that optimizes initial parameters such as bias values or weights. Each pixel in the picture is used for input of the neural network. The initial weights of neural network is consist of fixed-point real values and converted to bit string on purpose of using the individuals that are expressed in the Genetic Algorithm. For the fitness value, we defined the value that shows the lowest error of neural network, which is evaluated using newly defined adaptive re-learning operator and built the optimized and most advanced neural network. Then we made experiments on the face recognition. In comparison with learning convergence speed, the proposed algorithm shows faster convergence speed than solo executed back propagation algorithm and provides better performance, about 2.9% in proposed method than solo executed back propagation algorithm.

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