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We study in this paper the problem of using multiple-instance semi-supervised learning to solve image relevance feedback problem. Many multiple-instance learning algorithms have been proposed to tackle this problem; most of them only have a global representation of images. In this paper, we present a semi-supervised version of multiple instance learning. By taking into account both the multiple-instance...
In this paper a region-based image indexing and retrieval (RBIR) algorithm is presented. As a basis for the indexing, a novel spectral segmentation approach using random walks on graphs is introduced. Based on the extracted regions, characteristic features are estimated using color and texture information. The focus of this study is to improve the capture of regions so as to enhance indexing and retrieval...
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