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Part-based Structured Representation Learning for Person Re-identification 期刊论文
ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2020, 卷号: 16, 期号: 4, 页码: 22
作者:  Li, Yaoyu;  Yao, Hantao;  Zhang, Tianzhu;  Xu, Changsheng
Adobe PDF(19052Kb)  |  收藏  |  浏览/下载：278/37  |  提交时间：2021/03/08
Person re-identification  representation learning  graph convolutional network  
Skeleton-based action recognition with hierarchical spatial reasoning and temporal stack learning network 期刊论文
PATTERN RECOGNITION, 2020, 卷号: 107, 期号: 107511, 页码: 12
作者:  Si, Chenyang;  Jing, Ya;  Wang, Wei;  Wang, Liang;  Tan, Tieniu
Adobe PDF(2378Kb)  |  收藏  |  浏览/下载：352/65  |  提交时间：2020/08/31
Skeleton-based action recognition  Hierarchical spatial reasoning  Temporal stack learning  Clip-based incremental loss  
Non-Negative Iterative Convex Refinement Approach for Accurate and Robust Reconstruction in Cerenkov Luminescence Tomography 期刊论文
IEEE TRANSACTIONS ON MEDICAL IMAGING, 2020, 卷号: 39, 期号: 10, 页码: 3207-3217
作者:  Cai, Meishan;  Zhang, Zeyu;  Shi, Xiaojing;  Yang, Junying;  Hu, Zhenhua;  Tian, Jie
Adobe PDF(2176Kb)  |  收藏  |  浏览/下载：316/64  |  提交时间：2021/01/07
Image reconstruction  Imaging  Mathematical model  Shape  Slabs  Iterative methods  Luminescence  Cerenkov luminescence tomography  sparse reconstruction  inverse problem  tumor  
Long video question answering: A Matching-guided Attention Model 期刊论文
PATTERN RECOGNITION, 2020, 卷号: 102, 期号: 1, 页码: 11
作者:  Wang, Weining;  Huang, Yan;  Wang, Liang
Adobe PDF(1963Kb)  |  收藏  |  浏览/下载：358/69  |  提交时间：2020/06/02
Long video QA  Matching-guided attention  
Instance segmentation of apple flowers using the improved mask R-CNN model 期刊论文
BIOSYSTEMS ENGINEERING, 2020, 卷号: 193, 页码: 264-278
作者:  Tian, Yunong;  Yang, Guodong;  Wang, Zhe;  Li, En;  Liang, Zize
Adobe PDF(4718Kb)  |  收藏  |  浏览/下载：379/106  |  提交时间：2020/06/02
Apple flower images acquisition  Image augmentation  Deep learning  MASU R-CNN  Instance segmentation  
Research progress of parallel control and management 期刊论文
IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2020, 卷号: 7, 期号: 2, 页码: 355-367
作者:  Xiong, Gang;  Dong, Xisong;  Lu, Hao;  Shen, Dayong
浏览  |  Adobe PDF(12496Kb)  |  收藏  |  浏览/下载：290/52  |  提交时间：2020/06/02
ACP methodology  artificial systems  computational experiments  parallel control  parallel management  parallel systems  
EDP: An Efficient Decomposition and Pruning Scheme for Convolutional Neural Network Compression 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 32, 期号: 0, 页码: 0
作者:  Ruan, Xiaofeng;  Liu, Yufan;  Yuan, Chunfeng;  Li, Bing;  Hu, Weiming;  Li, Yangxi;  Maybank, Stephen
Adobe PDF(3625Kb)  |  收藏  |  浏览/下载：297/43  |  提交时间：2021/06/17
Data-driven  low-rank decomposition  model compression and acceleration  structured pruning  
Computational modeling of Emotion-motivated Decisions for Continuous Control of Mobile Robots 期刊论文
IEEE Transactions on Cognitive and Developmental Systems, 2020, 卷号: 13, 期号: 2020, 页码: 1-14
作者:  Huang, Xiao;  Wu, Wei;  Qiao, Hong
浏览  |  Adobe PDF(5970Kb)  |  收藏  |  浏览/下载：251/87  |  提交时间：2020/06/09
Brain-inspired Computing  Emotion-motivated Learning  Emotion-memory Interactions  Decision-making  Reinforcement Learning  
Lightweight Two-Stream Convolutional Neural Network for SAR Target Recognition 期刊论文
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2020, 卷号: 18, 期号: 0, 页码: 1-5
作者:  Huang, Xiayuan;  Yang, Qiao;  Qiao, Hong
浏览  |  Adobe PDF(736Kb)  |  收藏  |  浏览/下载：170/67  |  提交时间：2020/10/13
Lightweight  synthetic aperture radar (SAR) target recognition  two-stream convolutional neural network (CNN)  
Unsupervised Multi-View Constrained Convolutional Network for Accurate Depth Estimation 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 卷号: 29, 页码: 7019-7031
作者:  Zhang, Yuyang;  Xu, Shibiao;  Wu, Baoyuan;  Shi, Jian;  Meng, Weiliang;  Zhang, Xiaopeng
Adobe PDF(8221Kb)  |  收藏  |  浏览/下载：304/68  |  提交时间：2020/08/03
Estimation  Training  Feature extraction  Geometry  Computer vision  Cameras  Unsupervised learning  Unsupervised learning  DenseDepthNet  multi-view geometry constraint  depth consistency