May 21, 2018 · In this paper, we develop a deep supervised hashing method for multi-label image retrieval, in which we propose to learn a binary “mask” map that can identify ...

A deep supervised hashing method for multi-label image retrieval is developed, in which it is proposed to learn a binary “mask” map that can identify the ...

Learning-based hashing is a leading approach of approximate nearest neighbor search for large-scale image retrieval. In this paper, we develop a deep ...

Jun 11, 2018 · In this paper, we develop a deep supervised hashing method for multi-label image retrieval, in which we propose to learn a binary “mask” map ...

Learning-based hashing is a leading approach of approximate nearest neighbor search for large-scale image retrieval. In this paper, we develop a deep ...

Object-Location-Aware Hashing for Multi-Label Image Retrieval via Automatic Mask Learning ... IEEE Transactions on Image Processing. Pub Date: September ...

Learning-based hashing is a leading approach of approximate nearest neighbor search for large-scale image retrieval. In this paper, we develop a deep ...

This paper proposes a deep architecture that learns instance-aware image representations for multi-label image data, which are organized in multiple groups, ...

Mar 10, 2016 · Abstract—Similarity-preserving hashing is a commonly used method for nearest neighbour search in large-scale image re- trieval.

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