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Fusion of Stochastic and Linguistic Information Using a Conditional Event Framework
In: DTIC AND NTIS (2001)
Abstract: This report addresses a framework for merging different types and sources of information for applications involving image estimation. Complex decision-making systems rely on feature estimates derived from image data. It is imperative that all available information be used to effectively generate high quality estimates. This information includes stochastic raw sensor data, conditional information obtained from other sources and linguistic information such as if-then rules obtained from human experts who supervise the processing.
Keyword: *EXPERT SYSTEMS; *IMAGE PROCESSING; *STOCHASTIC PROCESSES; ADAPTIVE SYSTEMS; BAYES THEOREM; BAYESIAN NETWORKS; Computer Programming and Software; CONDITIONAL EVENT ALGEBRA; LINGUISTICS; PE62702F; RANDOM SETS; Range and Position Finding; SOFTWARE ENGINEERING; Statistics and Probability; Target Direction; WUAFRL4600IID2
URL: http://www.dtic.mil/docs/citations/ADA392127
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA392127
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