Artificial retinal neural network for visual pattern recognition
Donghui Guo, L.M. Cheng, L. L. Cheng, Zhenxiang Chen, Ruitang Liu, Boxi Wu · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1996
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.