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Recently, much research on application of neural network (NN) using genetic algorithm (GA) has been reported. In this paper, we apply GA to a neuro-pattern recognition system for paper currency with masks. We regard the position of the masked part as a gene on the input image. We operate crossover, mutation, and selection to some genes. By repeating a series of these operations, we can get effective masks for recognition of paper currency. We compare the ability of NN using the optimized masks by the GA with the one of NN using the random masks. Then we show that the GA is effective to mask optimization for the method of neuro-pattern recognition. Furthermore, we refer to a high-speed neuro-recognition board to realize the neuro-pattern recognition for paper currency in the commercial products.

Mask Optimization by Genetic Algorithm for a Neuro-Pattern Recognition Machine with Masks