Study of the neural network application in handwritten-digit recognition
Xuanjing Shen · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1992
In this paper, Hopfield networks, Hamming networks, and neocognitron models and their application in handwritten digit recognition are discussed. The neocognitron model is a multilayer network for a mechanism of visual pattern recognition and self-organized by `learning without a teacher,' and it acquires an ability to recognize stimulus patterns based on the geometrical similarity of their shapes without being affected by their positions and distortions, so it showed higher ability to recognize handwritten digits. We developed a handwritten digit recognition system based on the neocognitron (HDRSBN), and carried on the simulation experiments.