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- W2057145265 abstract "This paper proposes a new content based image retrieval (CBIR) system combined with relevance feedback and the online feature selection procedures. A measure of inconsistency from relevance feedback is explicitly used as a new semantic criterion to guide the feature selection. By integrating the user feedback information, the feature selection is able to bridge the gap between low-level visual features and high-level semantic information, leading to the improved image retrieval accuracy. Experimental results show that the proposed method obtains higher retrieval accuracy than a commonly used approach." @default.
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- W2057145265 date "2010-09-01" @default.
- W2057145265 modified "2023-09-27" @default.
- W2057145265 title "Image retrieval with feature selection and relevance feedback" @default.
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- W2057145265 doi "https://doi.org/10.1109/icip.2010.5651984" @default.
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