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Proceedings Paper

Multitarget and multibackground classification algorithm using neural networks
Author(s): Rustom Mamlook; Wiley E. Thompson
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Paper Abstract

A multi-target and multi-background classification algorithm using neural networks is presented. The algorithm uses a feedforward neural network algorithm, a double window filter, and thresholds to classify an image into targets and backgrounds. This algorithm's performance differs from that of the K-nearest neighbor (K-NN) classifier algorithm in that (1) it provides noiseless classification, (2) it is faster, and (3) it provides better accuracy. Examples are given to illustrate the results.

Paper Details

Date Published: 3 September 1993
PDF: 8 pages
Proc. SPIE 1955, Signal Processing, Sensor Fusion, and Target Recognition II, (3 September 1993); doi: 10.1117/12.154976
Show Author Affiliations
Rustom Mamlook, New Mexico State Univ. (Jordan)
Wiley E. Thompson, New Mexico State Univ. (United States)


Published in SPIE Proceedings Vol. 1955:
Signal Processing, Sensor Fusion, and Target Recognition II
Ivan Kadar; Vibeke Libby, Editor(s)

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