Aiming at improving context-sensitive similarity, we propose a novel algorithm for neighborhood structure mining, which satisfies the manifold assumption.
Extensive experimental results and comparisons manifest that with the neighborhood structure generated by SN, the proposed framework can yield state-of-the-art ...
[PDF] Improving context-sensitive similarity via smooth ...
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Semantic Scholar extracted view of "Improving context-sensitive similarity via smooth neighborhood for object retrieval" by S. Bai et al.
The key idea of context-sensitive similarity is that the similarity between two data points can be more reliably estimated with the local context of other ...
The key idea of context-sensitive similarity is that the similarity between two data points can be more reliably estimated with the local context of other ...
@article{SN_PR, title={Improving Context-sensitive Similarity via Smooth Neighborhood for Object Retrieval}, author={Bai, Song and Sun, Shaoyan and Bai ...
Improving context-sensitive similarity via smooth neighborhood for object retrieval. S Bai, S Sun, X Bai, Z Zhang, Q Tian. Pattern Recognition 83, 353-364 ...
Improving context-sensitive similarity via smooth neighborhood for object retrieval. S Bai, S Sun, X Bai, Z Zhang, Q Tian. Pattern Recognition 83, 353-364 ...
Improving context-sensitive similarity via smooth neighborhood for object retrieval · S. BaiShaoyan SunX. BaiZhaoxiang ZhangQ. Tian. Computer Science. Pattern ...
Song Bai, Shaoyan Sun, Xiang Bai, Zhaoxiang Zhang, Qi Tian. Improving context-sensitive similarity via smooth neighborhood for object retrieval. Pattern ...