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Proceedings Paper

Artificial immune system for multispectral feature extraction
Author(s): David F. McCoy; Venkat Devarajan
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Paper Abstract

We use an algorithm based on the natural immune system for classification of aerial multispectral imagery. Our artificial immune system works by maintaining a population of detectors that remove undesired patterns, but pass a specified training set of positive examples. Any detectors reacting with input patterns are optimized to remove as many of them as possible while not removing ones similar to the training examples. This paper consists of an introduction to the natural and artificial immune systems (AIS), explanation of the AIS algorithm, results of forest and water classification using multispectral data, and discussion of sources of error and possible improvements.

Paper Details

Date Published: 2 July 1998
PDF: 8 pages
Proc. SPIE 3372, Algorithms for Multispectral and Hyperspectral Imagery IV, (2 July 1998); doi: 10.1117/12.312605
Show Author Affiliations
David F. McCoy, Raytheon Systems Co. (United States)
Venkat Devarajan, Univ. of Texas/Arlington (United States)

Published in SPIE Proceedings Vol. 3372:
Algorithms for Multispectral and Hyperspectral Imagery IV
Sylvia S. Shen; Michael R. Descour, Editor(s)

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