A Semi-Supervised Active Learning Framework for Image Retrieval
Although recent studies have shown that unlabeled data are beneficial to boosting the image retrieval performance, very few approaches for image retrieval can learn with labeled and unlabeled data effectively. This paper proposes a novel semi-supervised active learning framework comprising a fusion...
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Main Authors: | , |
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Format: | text |
Language: | English |
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Institutional Knowledge at Singapore Management University
2005
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Online Access: | https://ink.library.smu.edu.sg/sis_research/2394 https://ink.library.smu.edu.sg/context/sis_research/article/3394/viewcontent/CVPR2005.pdf |
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Institution: | Singapore Management University |
Language: | English |