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Proceedings Paper

Learned fusion operators based on matrix completion
Author(s): Kelly K. D. Risko; Charles F. Hester
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Paper Abstract

The efficient and timely management of imagery captured in the battlefield requires methods capable of searching the voluminous databases and extracting highly symbolic concepts. When processing images, a semantic and definition gap exists between machine representations and the user's language. Based on matrix completion techniques, we present a fusion operator that fuses imagery and expert knowledge provided by user inputs during post analysis. Specifically, an information matrix is formed from imagery and a class map as labeled by an expert. From this matrix an image operator is derived for the extraction/prediction of information from future imagery. We will present results using this technique on single mode data.

Paper Details

Date Published: 6 June 2011
PDF: 12 pages
Proc. SPIE 8064, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2011, 80640K (6 June 2011); doi: 10.1117/12.885011
Show Author Affiliations
Kelly K. D. Risko, U.S. Army Aviation and Missile Research, Development, and Engineering Ctr. (United States)
Charles F. Hester, U.S. Army Aviation and Missile Research, Development, and Engineering Ctr. (United States)


Published in SPIE Proceedings Vol. 8064:
Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2011
Jerome J. Braun, Editor(s)

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