5 citations · 9 across the 7 of their papers we have counts for
6 papers
Distribution-Consistency-Guided Multi-modal Hashing
Jin-Yu Liu, Xian-Ling Mao, Tian-Yi Che +1
Multi-modal hashing methods have gained popularity due to their fast speed and low storage requirements. Among them, the supervised methods demonstrate better performance by utiliz…
Unsupervised Hashing with Semantic Concept Mining
Rong-Cheng Tu, Xian-Ling Mao, Kevin Qinghong Lin +5
Recently, to improve the unsupervised image retrieval performance, plenty of unsupervised hashing methods have been proposed by designing a semantic similarity matrix, which is bas…
A multi-level approach with visual information for encrypted H.265/HEVC videos
Wenying Wen, Rongxin Tu, Yushu Zhang +2
High-efficiency video coding (HEVC) encryption has been proposed to encrypt syntax elements for the purpose of video encryption. To achieve high video security, to the best of our…
Deep Cross-modal Hashing via Margin-dynamic-softmax Loss
Rong-Cheng Tu, Xian-Ling Mao, Rongxin Tu +3
Due to their high retrieval efficiency and low storage cost for cross-modal search task, cross-modal hashing methods have attracted considerable attention. For the supervised cross…
Deep Cross-Modal Hashing with Hashing Functions and Unified Hash Codes Jointly Learning
Rong-Cheng Tu, Xian-Ling Mao, Bing Ma +4
Due to their high retrieval efficiency and low storage cost, cross-modal hashing methods have attracted considerable attention. Generally, compared with shallow cross-modal hashing…
Object Detection based Deep Unsupervised Hashing
Rong-Cheng Tu, Xian-Ling Mao, Bo-Si Feng +2
Recently, similarity-preserving hashing methods have been extensively studied for large-scale image retrieval. Compared with unsupervised hashing, supervised hashing methods for la…