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Titlebook: Visual and Multimedia Information Management; IFIP TC2/WG2.6 Sixth Xiaofang Zhou,Pearl Pu Book 2002 IFIP International Federation for Infor

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Hyperdatabasesll users have a pre-defined view on a global information space and have to access data by the same primitive means. However, a more convenient solution from a user’s point of view considers her/his individual context and interests by mapping the global information space to a personal one. Yet, the o
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Relevance Feedback in CBIRperformance. This effort tries to bridge the gap between low-level image features and high-level semantic contents of images as this gap is the bottleneck of CBIR. We consider relevance feedback in CBIR a small sample-learning process in sparse image feature space. Almost all of the previously propo
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Som-Based K-Nearest Neighbors Search in Large Image Databases using a self-organizing map algorithm. Then, we map each cluster into a point in one-dimensional distance space. From these mapped points, we construct a simple, compact and yet fast index structure, called .. Unlike most indexes of KNN algorithms that require storage space exponential in dimension
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