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Graph Regularized Non-Negative Low-Rank Matrix Factorization for Image Clustering 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2017, 卷号: 47, 期号: 11, 页码: 3840-3853
作者:  Li, Xuelong;  Cui, Guosheng;  Dong, Yongsheng
Adobe PDF(1643Kb)  |  收藏  |  浏览/下载：278/1  |  提交时间：2017/12/25
Data Representation  Graph Regularization  Image Clustering  Low-rank Recovery  Non-negative Matrix Factorization (Nmf)  
Similarity Constraints-Based Structured Output Regression Machine: An Approach to Image Super-Resolution 期刊论文
IEEE Transactions on Neural Networks and Learning Systems, 2016, 卷号: 27, 期号: 12, 页码: 2472-2485
作者:  Deng, Cheng;  Xu, Jie;  Zhang, Kaibing;  Tao, Dacheng;  Gao, Xinbo;  Li, Xuelong;  Deng, C (reprint author), Xidian Univ, Sch Elect Engn, Xian 710071, Peoples R China.
Adobe PDF(5982Kb)  |  收藏  |  浏览/下载：253/1  |  提交时间：2016/12/30
NoNlocal (Nl) Self-similarity  Structured Output  Super-resolution (Sr)  Support Vector Regression (Svr)  
Incrementally Detecting Moving Objects in Video with Sparsity and Connectivity 期刊论文
COGNITIVE COMPUTATION, 2016, 卷号: 8, 期号: 3, 页码: 420-428
作者:  Pan, Jing;  Li, Xiaoli;  Li, Xuelong;  Pang, Yanwei
Adobe PDF(1525Kb)  |  收藏  |  浏览/下载：176/2  |  提交时间：2016/09/18
Subspace Learning  Object Detection  Sparsity  Connectivity  
Efficient and Robust Learning for Sustainable and Reacquisition-Enabled Hand Tracking 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2016, 卷号: 46, 期号: 4, 页码: 945-958
作者:  Aziz, Muhammad Ali Abdul;  Niu, Jianwei;  Zhao, Xiaoke;  Li, Xuelong
Adobe PDF(1955Kb)  |  收藏  |  浏览/下载：153/1  |  提交时间：2016/08/18
Computer Vision  Histograms Of Oriented Gradient (Hog)  Local Binary Pattern (Lbp)  Machine Learning  Mean Shift Implanted Particle Filter  
Weakly Supervised Human Fixations Prediction 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2016, 卷号: 46, 期号: 1, 页码: 258-269
作者:  Zhang, Luming;  Li, Xuelong;  Nie, Liqiang;  Yang, Yi;  Xia, Yingjie;  Xia, YJ
Adobe PDF(1963Kb)  |  收藏  |  浏览/下载：235/2  |  提交时间：2016/01/22
Attention  Computer Vision  Graphlets  Machine Learning  Manifold Embedding  Weakly Supervised  
Learning Spatio-Temporal Representations for Action Recognition: A Genetic Programming Approach 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2016, 卷号: 46, 期号: 1, 页码: 158-170
作者:  Liu, Li;  Shao, Ling;  Li, Xuelong;  Lu, Ke;  Shao, L
Adobe PDF(2314Kb)  |  收藏  |  浏览/下载：210/2  |  提交时间：2016/01/22
Action Recognition  Feature Extraction  Feature Learning  Genetic Programming (Gp)  Spatio-temporal Descriptors