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MTA
2002

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MUSE: A Content-Based Image Search and Retrieval System Using Relevance Feedback

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MUSE: A Content-Based Image Search and Retrieval System Using Relevance Feedback

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ThefieldofContent-BasedVisualInformationRetrieval(CBVIR)hasexperiencedtremendousgrowth in the recent years and many research groups are currently working on solutions to the problem of finding a desired image or video clip in a huge archive without resorting to metadata. This paper describes the ongoing development of a CBVIR system for image search and retrieval with relevance feedback capabilities. It supports browsing, queryby-example, and two different relevance feedback modes that allow users to refine their queries by indicating which images are good or bad at each iteration.

Oge Marques, Borko Furht

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Added	22 Dec 2010
Updated	22 Dec 2010
Type	Journal
Year	2002
Where	MTA
Authors	Oge Marques, Borko Furht

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