no code implementations • NeurIPS 2023 • Jianglin Lu, Yi Xu, Huan Wang, Yue Bai, Yun Fu
We begin by defining the pivotal nodes as $k$-hop starved nodes, which can be identified based on a given adjacency matrix.
no code implementations • 25 Jun 2022 • Jianglin Lu, Jie zhou, Yudong Chen, Witold Pedrycz, Kwok-Wai Hung
Specifically, ATH characterizes the domain distribution gap by the discrepancy between two asymmetric hash functions, and minimizes the feature gap with the help of a novel adaptive bipartite graph constructed on cross-domain data.
no code implementations • 24 Oct 2021 • Jianglin Lu, Hailing Wang, Jie zhou, Mengfan Yan, Jiajun Wen
Recently, deep hashing methods have been widely used in image retrieval task.
no code implementations • 10 Mar 2021 • Qinghong Lin, Weichan Zhong, Jianglin Lu
Most of the early algorithms are unsupervised methods, which use hand-crafted features to divide the image into many regions.