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The field of Content-Based Visual Information Retrieval (CBVIR) has experienced tremendous growth 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 modesdoi:10.1023/a:1014679605305 fatcat:c6qlrv4jizawval2u6srsnxrdi