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Developing effective fusion schemes for multiple feature types has always been a hot issue in content-based image retrieval. In this paper, we propose a novel method for graph-based visual reranking, which addresses two major limitations in existing methods. First, in the phase of graph construction, our method introduces fine-grained measurements for image relations, by assigning the edge weights...
Developing effective fusion schemes for multiple feature types has always been a hot issue in content-based image retrieval. In this paper, we propose a novel method for graph based visual reranking, which addresses two major limitations in existing methods. Firstly, in the phase of graph construction, our method introduces fine-grained measurements for image relations, by assigning the edge weights...
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