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ADAPTIVE RECOGNITION OF HAND-WRITTEN KANJI CHARACTERS USING SELF-ORGANIZED NEURAL NETWORK
Miyanaga, Yoshikazu,Tochinai, Koji,Kondo, Masanori,Hayashi, Masato 대한전자공학회 1994 ISPACS:Intelligent Signal Processing and Communica Vol.1 No.1
This port introduces an image recognition system for hand-written Kanji characters. The method is based on a self-organized neural network and a single layer perception network. The self-organized neural network is used for adaptive clustering. The single perception network is used for recognition. It is well known that a large amount of time is required in the training by a mullti-layered perception when some cluster distributions have complicated structures. However, since only the simplest perception is applied in this proposed system, a quite short time is enough to learn training data. The reason why multi-layered perception is not required to recognize data in this system is based on the use of a self-organized network. The self-organized network can change a complicated structure of cluster distribution to a simple structure without the loss of information. Thus, it can be shown that the simple perception is enough to recognize even nonlinear characteristic distribution.