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Proceedings Paper

Test results for a 32x32 PCNN array
Author(s): John L. Johnson; S. Richard F. Sims; T. W. Branch
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Paper Abstract

Pulse coupled neural network (PCNN) algorithms for image preprocessing have minimal requirements for interconnects and essentially no memory requirements. They are an effective technique for rapid intensity segmentation and noise smoothing as an initial step in many image processing algorithms. A test array with 32 X 32 active PCNN pixels has been undergoing initial evaluation. Its performance is discussed and comparison with software versions of the PCNN algorithm is given.

Paper Details

Date Published: 22 March 1999
PDF: 4 pages
Proc. SPIE 3728, Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks, (22 March 1999); doi: 10.1117/12.343036
Show Author Affiliations
John L. Johnson, U.S. Army Aviation and Missile Command (Germany)
S. Richard F. Sims, U.S. Army Aviation and Missile Command (United States)
T. W. Branch, U.S. Army Aviation and Missile Command (United States)


Published in SPIE Proceedings Vol. 3728:
Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks
Thomas Lindblad; Mary Lou Padgett; Jason M. Kinser, Editor(s)

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