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Structured neural networks for multi-font Chinese character recognition using a newly developed digital neural network chip with adaptive segmentation of quantizer neuron architecture (ASQA)

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3 Author(s)
Kondo, K. ; Central Res. Lab., Matsushita Electr. Ind. Co. Ltd., Kyoto, Japan ; Imagawa, T. ; Maruno, S.

This paper describes structured networks that use a digital network chip with having adaptive segmentation of quantizer neuron architecture (ASQA) and presents results of applying the ASQA chip to the large scale problem of multi-font Chinese character recognition. The ASQA chip can simulate neural networks using ASQA model which can provide a proliferation of neurons based on input data for learning and can generate appropriate network structure with extremely fast processing speed. Moreover, this chip can simulate not only a single network but also sets of several structured networks; consequently, the chip can handle large scale problems. By applying the chip to multi-font Chinese character recognition, average accuracy of the open test increased to 97% and a recognition speed of 6 msec/character was achieved

Published in:

Neural Networks for Signal Processing [1996] VI. Proceedings of the 1996 IEEE Signal Processing Society Workshop

Date of Conference:

4-6 Sep 1996