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Proceedings Paper

Implementation of the morphological shared-weight neural network (MSNN) for target recognition on the Parallel Algebraic Logic (PAL) computer
Author(s): Hongzheng Li; Hongchi Shi; Paul D. Gader; James M. Keller
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Paper Abstract

The morphological shared-weight neural network (MSNN) is an effective approach to automatic target recognition. Implementation of the network in parallel is critical for real-time target recognition systems. Although there is significant parallelism inherent in the MSNN, it is a challenge to implement it on an SIMD parallel computer consisting of a large array of simple processing elements. This paper discusses issues related to detection accuracy and throughput in implementing the MSNN on the Parallel Algebraic Logic computer.

Paper Details

Date Published: 21 September 1998
PDF: 12 pages
Proc. SPIE 3452, Parallel and Distributed Methods for Image Processing II, (21 September 1998); doi: 10.1117/12.323468
Show Author Affiliations
Hongzheng Li, Univ. of Missouri/Columbia (United States)
Hongchi Shi, Univ. of Missouri/Columbia (United States)
Paul D. Gader, Univ. of Missouri/Columbia (United States)
James M. Keller, Univ. of Missouri/Columbia (United States)


Published in SPIE Proceedings Vol. 3452:
Parallel and Distributed Methods for Image Processing II
Hongchi Shi; Patrick C. Coffield, Editor(s)

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