Pattern Recognition With A Neural Net

William Stoner; Terry M. Schilke

doi:10.1117/12.976259

23 March 1986 Pattern Recognition With A Neural Net

William Stoner, Terry M. Schilke

Proceedings Volume 0698, Real-Time Signal Processing IX; (1986) https://doi.org/10.1117/12.976259
Event: 30th Annual Technical Symposium, 1986, San Diego, United States

Abstract

Following the neocognitron architecture described by Fukushima, an Artificial Neural System (ANS) has been programmed in Fortran and run on an IBM PC AT. Our independent experience with this ANS confirms the findings of Fukushima for the neocognitron architecture. Specifically we exercised both the learning and recognition modes of the ANS. In the learning mode, alphanumeric characters are learned and distinguished without instruction or outside correction of errors. In the recognition mode, alphanumeric characters are recognized with tolerance to position, scale and geometric distortion. We describe the neocognitron architecture and explain the basis of its operation for both the learning and recognition modes.

Citation Download Citation

William Stoner and Terry M. Schilke "Pattern Recognition With A Neural Net", Proc. SPIE 0698, Real-Time Signal Processing IX, (23 March 1986); https://doi.org/10.1117/12.976259

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