Character recognition using a multistage neural network
Ismail I. Jouny, Matt Sheridan · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1992
This paper uses two stages of multi-layer neural networks for character recognition. In the first stage, each neural network is trained to recognize a segment of the character image. The responses are then presented to another network where the final decision is made. The proposed method is computationally efficient, fault tolerant, has an associative memory capability, and has some of the merits of multi-decision pattern recognition techniques. The features used are gray-level representations of both typed and hand-written upper case characters. The proposed recognition scheme is tested extensively and its performance is compared with that of other non-parametric recognition methods.