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Proceedings Paper

Self-organizing integrated segmentation and recognition neural network
Author(s): James D. Keeler; David E. Rumelhart
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Paper Abstract

We present a neural network algorithm that simultaneously performs segmentation and recognition of input patterns that self-organizes to detect input pattern locations and pattern boundaries. We outline the algorithm and demonstrate this neural network architecture and algorithm on character recognition using the NIST database and report results herein. The resulting system simultaneously segments and recognizes touching characters, overlapping characters, broken characters, and noisy images with high accuracy. We also detail some of the characteristics of the algorithm on an artificial database in the appendix.

Paper Details

Date Published: 1 July 1992
PDF: 12 pages
Proc. SPIE 1710, Science of Artificial Neural Networks, (1 July 1992); doi: 10.1117/12.140155
Show Author Affiliations
James D. Keeler, Pavilion Technologies, Inc. (United States)
David E. Rumelhart, Stanford Univ. (United States)


Published in SPIE Proceedings Vol. 1710:
Science of Artificial Neural Networks
Dennis W. Ruck, Editor(s)

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