Design and evaluation of neural networks for coin recognition by using GA and SA

Yasue Mitsukura, Minoru Fukumi, Norio Akamatsu

Research output: Contribution to conferencePaperpeer-review

19 Citations (Scopus)


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 effective to find a small number of input signals for coin recognition.

Original languageEnglish
Number of pages6
Publication statusPublished - 2000
Externally publishedYes
EventInternational Joint Conference on Neural Networks (IJCNN'2000) - Como, Italy
Duration: 2000 Jul 242000 Jul 27


OtherInternational Joint Conference on Neural Networks (IJCNN'2000)
CityComo, Italy

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence


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