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Proceedings Paper

Using a blackboard architecture or expert system to identify obfuscated targets from symptoms
Author(s): Jeremy Straub
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Paper Abstract

A variety of techniques exist for enhancing or inferring the existence and characteristics of an obscured or partially concealed target. Targets, however, may be completely blocked from view, presenting nothing to enhance and no image area to extend inferentially. Despite the difficulty, concealed (particularly intentionally) targets may be the most important to detect. This paper proposes a technique for using a Blackboard Architecture or Expert system to infer a target’s existence from symptoms (maneuvers of other units, water and soil deformation, etc.) and discusses the differences between the two approaches (Blackboard Architecture and expert system) for doing so.

Paper Details

Date Published: 15 May 2015
PDF: 11 pages
Proc. SPIE 9454, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XX, 945408 (15 May 2015); doi: 10.1117/12.2177982
Show Author Affiliations
Jeremy Straub, Univ. of North Dakota (United States)

Published in SPIE Proceedings Vol. 9454:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XX
Steven S. Bishop; Jason C. Isaacs, Editor(s)

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