Artificial retinal neural network for visual pattern recognition

Donghui Guo; Lee Ming Cheng; L. L. Cheng; Zhenxiang Chen; Ruitang Liu; Boxi Wu

doi:10.1117/12.234251

4 March 1996 Artificial retinal neural network for visual pattern recognition

Donghui Guo, Lee Ming Cheng, L. L. Cheng, Zhenxiang Chen, Ruitang Liu, Boxi Wu

Proceedings Volume 2664, Applications of Artificial Neural Networks in Image Processing; (1996) https://doi.org/10.1117/12.234251
Event: Electronic Imaging: Science and Technology, 1996, San Jose, CA, United States

Abstract

With feed-forward adaptive network (FFAN) and feed-back associative network (FBAN) respectively imitating the performances of retina and cerebral cortex, an artificial retinal neural network (ARNN) was presented in this paper for fast recognition of visual patterns. In our ARNN model to be implemented with neural network chip MD1200, every synaption of neurons can be arbitrarily given as an integer value from minus 2¹⁵ to 2¹⁵. After these synaptions are trained, the visual pattern not only under geometric transformation but also in the presence of noise can be recognized by the ARNN's system.

Citation Download Citation

Donghui Guo, Lee Ming Cheng, L. L. Cheng, Zhenxiang Chen, Ruitang Liu, and Boxi Wu "Artificial retinal neural network for visual pattern recognition", Proc. SPIE 2664, Applications of Artificial Neural Networks in Image Processing, (4 March 1996); https://doi.org/10.1117/12.234251

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