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We propose in this paper a general kernel framework to deal with database object retrieval embedded in images with heterogeneous background. We use local features computed on fuzzy regions for image representation summarized in bags, and we propose original kernel functions to deal with sets of features and spatial constraints. Combined with SVMs classification and online learning scheme, the resulting...
In this paper, we present a system for image retrieval over a network of computer based on "ant-like" mobile-agents. Image databases are hosted on the network, and the user wants to find all the images matching a specific concept (cars, flower, Italy, etc...). Usually, content based image retrieval systems (CBIR) do not consider the dispertion of the data among the network. We train a SVM...
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