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Proceedings Paper

Improved Cartographic Classification Via Expert Systems
Author(s): Mark F. Doherty; Carolyn M. Bjorklund; Connie Y. Wang; Mark T. Noga; Robert H. Laprade
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Paper Abstract

Statistical classification algorithms currently achieve good, but not perfect, results when classifying complex aerial images into eight or more classes. We show results from one tree classifier which provided between 50% to 65% accuracy in an unsupervised mode. This paper explains how our Advanced Cartographic Expert System (ACES) can be utilized to improve this classification accuracy.

Paper Details

Date Published: 26 March 1986
PDF: 5 pages
Proc. SPIE 0635, Applications of Artificial Intelligence III, (26 March 1986); doi: 10.1117/12.964108
Show Author Affiliations
Mark F. Doherty, Lockheed Missiles and Space Co., Inc. (United States)
Carolyn M. Bjorklund, Lockheed Missiles and Space Co., Inc. (United States)
Connie Y. Wang, Lockheed Missiles and Space Co., Inc. (United States)
Mark T. Noga, Lockheed Missiles and Space Co., Inc. (United States)
Robert H. Laprade, Lockheed Missiles and Space Co., Inc. (United States)


Published in SPIE Proceedings Vol. 0635:
Applications of Artificial Intelligence III
John F. Gilmore, Editor(s)

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