A knowledge based architecture for airborne minefield detection
"Airborne mine and minefield detection is an active area of research and has seen significant development in the last ten to fifteen years. One of the primary lessons learned during this airborne mid-wave infrared (MWIF) based mine and minefield detection research and development has been the fact that no single algorithm or static detection architecture is able to meet mine and minefield detection performance specifications. This is true not only because of the highly varied environmental and operational conditions under which an airborne sensor is expected to perform but also due to the highly data dependent nature of sensors and algorithms employed for detection. Attempts to make the algorithms themselves more robust to varying operating conditions have only been partially successful. In this thesis, a knowledge-based architecture to tackle this challenging problem is presented"--Abstract, leaf iii.
Agarwal, Sanjeev, 1971-
Kosbar, Kurt Louis
Stanley, R. Joe
Electrical and Computer Engineering
M.S. in Electrical Engineering
University of Missouri--Rolla
xi, 122 leaves
© 2005 Deepak Menon, All rights reserved.
Thesis - Citation
Library of Congress Subject Headings
Expert systems (Computer science) -- Design
Land mines -- Detection
Mines (Military explosives) -- Detection
Print OCLC #
Link to Catalog Record
Full-text not available: Request this publication directly from Missouri S&T Library or contact your local library.http://laurel.lso.missouri.edu/record=b5850371~S5
Menon, Deepak, "A knowledge based architecture for airborne minefield detection" (2005). Masters Theses. 4440.
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