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Conventional content-based image retrieval (CBIR) systems with the Euclidean distance metric in a high-dimensional visual feature space usually cannot achieve satisfactory performance due to the semantic gap. Relevance feedback (RF) has been introduced as a powerful tool to involve the user in the system to improve the performance of CBIR. Despite the success, an on-line learning task can be tedious...
Content-based image retrieval (CBIR) has attracted substantial attention during the past few years for its potential practical applications to image management. A variety of relevance feedback schemes have been designed to bridge the semantic gap between low-level visual features and high-level semantic concepts for an image retrieval task. Various collaborative image retrieval (CIR) schemes aim to...
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