Design and Evaluation of Neural Networks for Coin Recognition by Using GA and SA

In this paper, we propose a method to design a neural network(NN) by using a genetic algorithm(GA) and simulated annealing(SA). And also, in order to demonstrate the effectiveness of the proposed scheme, we apply the proposed scheme to a coin recognition example. In general, as a problem becomes complex and large-scale, the number of operations increases and hardware implementation to real systems (coin recognition machines) using NNs becomes difficult. Therefore, we propose the method which makes a small-sized NN system to achieve a cost reduction and to simplify hardware implementation to the real machines. The coin images used in this paper were taken by a cheap scanner. Then they are not perfect, but a part of the coin image could be used in computer simulations. Input signals, which are Fourier spectra, are learned by a three-layered NN. The inputs to NN are selected by using GA with SA to make a small-sized NN. Simulation results show that the proposed scheme is effencive to ï...

• Type: Conference
• Year: 2000
• Where: IJCNN
• Authors: Yasue Mitsukura, Minoru Fukumi, Norio Akamatsu
• Keywords: Coin Recognition, Hardware Implementation, IJCNN 2000, Neural Networks, Small-sized Nn