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Proceedings Paper

Pattern Recognition With A Neural Net
Author(s): William Stoner; Terry M. Schilke
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Paper 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.

Paper Details

Date Published: 23 March 1986
PDF: 12 pages
Proc. SPIE 0698, Real-Time Signal Processing IX, (23 March 1986); doi: 10.1117/12.976259
Show Author Affiliations
William Stoner, Science Applications International Corporation (United States)
Terry M. Schilke, Science Applications International Corporation (United States)

Published in SPIE Proceedings Vol. 0698:
Real-Time Signal Processing IX
William J. Miceli, Editor(s)

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