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A genetic algorithm for training image classification neural networks

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2 Author(s)
Ching Zhang ; Dept. of Syst. Design Eng., Waterloo Univ., Ont., Canada ; Fangju Wang

Neural networks are becoming effective tools for digital image classification. They have advantages including simple and flexible structures and higher tolerance to errors. The major drawbacks which limit neural networks for practical applications include slow training phase and divergence of training. In this research, a new method has been developed to address the drawbacks. This method is based on genetic algorithms

Published in:

Systems, Man, and Cybernetics, 1994. Humans, Information and Technology., 1994 IEEE International Conference on  (Volume:3 )

Date of Conference:

2-5 Oct 1994