Exploring Auxiliary Context: Discrete Semantic Transfer Hashing for Scalable Image Retrieval.
IEEE Transactions on Neural Networks and Learning Systems(2019)
摘要
Unsupervised hashing can desirably support scalable content-based image retrieval for its appealing advantages of semantic label independence, memory, and search efficiency. However, the learned hash codes are embedded with limited discriminative semantics due to the intrinsic limitation of image representation. To address the problem, in this paper, we propose a novel hashing approach, dubbed as ...
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关键词
Semantics,Visualization,Image retrieval,Optimization,Scalability,Training,Transforms
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