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A hierarchical manifold subgraph ranking system for content-based image retrieval
2013
2013 IEEE International Conference on Multimedia and Expo (ICME)
We present a novel hierarchical manifold subgraph ranking system for content-based image retrieval (CBIR). The proposed CBIR system is capable of searching a large scale imagery database via its hierarchical structure. To achieve this scalability, we first apply the SVM-based learning mechanism to construct users' relevance feedback groups and extract high-level semantic features for each image. We then build two-layer manifold subgraphs by incorporating both visual and semantic similarity into
doi:10.1109/icme.2013.6607466
dblp:conf/icmcs/ChangQ13
fatcat:uts2tcgo2fht7lqeptle4hw3pa