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In this paper, the authors design a fuzzy system for image retrieval to reduce the semantic gap in the content - based image retrieval systems. The main contribution is three - fold: designing a fuzzy modeling approach to model the expert human behavior in the image retrieval task, a fuzzy system for semantic - based image retrieval, and a training algorithm for creating the fuzzy rules. The proposed solution not only is a novel idea in the semantic - based image retrieval field, but has enough potential in learning semantics from the user and making a powerful approach to improve the performance of CBIR systems, as their experiments on a set of 2000 images supports their claim.
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