A genetic algorithm for training image classification neural networks

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.<
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