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4 March 1996 Artificial retinal neural network for visual pattern recognition
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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.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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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