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CASIA OpenIR
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Web Image Mining Based on Modeling Concept-Sensitive Salient Regions 会议论文
Proceedings of the 2006 IEEE International Conference on Multimedia and Expo, Toronto, Ontario, Canada, July 9-12, 2006
作者:  Jing Liu;  Qingshan Liu;  Jinqiao Wang;  Hanqing Lu;  Songde Ma
收藏  |  浏览/下载：147/0  |  提交时间：2017/02/20
Gaussian Processes  Data Mining  Expectation-maximisation Algorithm  Image Retrieval  Search Engines  Semantic Web  Gaussian Mixture Model  Web Image Mining  Concept-sensitive Salient Region Model  Exoexpectation-maximization Algorithm  Image Retrieval  Image Semantics  Probabilistic Model  Search Engine  Bridges  Detectors  Html  Humans  Image Analysis  Image Retrieval  Image Segmentation  Pixel  Search Engines  Skin  
Image Annotation Refinement using NSC-Based Word Correlation 会议论文
Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, Beijing, China, July 2-5, 2007
作者:  Jing Liu;  Mingjing Li;  Qingshan Liu;  Hanqing Lu;  Songde Ma
收藏  |  浏览/下载：171/0  |  提交时间：2017/02/20
Internet  Graph Theory  Image Retrieval  Corel Dataset  Nsc-based Word Correlation  Automatic Image Annotation  Candidate Annotations  Image Annotation Refinement  Nearest Spanning Chains  Synonymy Relationship  Untagged Image  Word Co-occurrence Information  Word Correlation Estimation  Word-based Graph  Asia  Automation  Data Mining  Explosions  Information Retrieval  Internet  Organizing  Statistical Distributions  Thesauri  Training Data  
Object-centered Narrative for Surveillance Video 会议论文
International Conference on Image and Processing, Orlando, Florida, USA., 2012.10
作者:  Wei Fu;  Jinqiao Wang;  Chaoyang Zhao;  Hanqing Lu;  Songde Ma
浏览  |  Adobe PDF(666Kb)  |  收藏  |  浏览/下载：265/87  |  提交时间：2016/10/26
Object Tracking  
Object Co-segmentation via Salient and Common Regions Discovery 期刊论文
Neurocomputing, 2016, 期号: 172, 页码: 225-234
作者:  Li, Yong;  Liu, Jing;  Li, Zechao;  Lu, Hanqing;  Ma, Songde
Adobe PDF(2793Kb)  |  收藏  |  浏览/下载：866/296  |  提交时间：2016/06/29
Object Co-segmentation  Low Rank Matrix Recovery  Discriminative Learning  
Weakly Supervised RBM for Semantic Segmentation 会议论文
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, Buenos Aires, Argentina, July 25-31, 2015
作者:  Yong Li;  Jing Liu;  Yuhang Wang;  Hanqing Lu;  Songde Ma
Adobe PDF(1527Kb)  |  收藏  |  浏览/下载：339/79  |  提交时间：2016/06/27
无  
Exclusive Constrained Discriminative Learning for Weakly-Supervised Semantic Segmentation 会议论文
ACM Digital Library, Brisbane, Queensland, Australia, 26 – 30,October,2015
作者:  Ying P(应鹏);  Liu J(刘静);  Lu HQ(卢汉清);  Ma SD(马颂德)
浏览  |  Adobe PDF(1375Kb)  |  收藏  |  浏览/下载：408/99  |  提交时间：2016/06/20
Semantic Segmentation  Weak Supervision  
Dual Cross-Media Relevance Model for Image Annotation 会议论文
Proceedings of the 15th International Conference on Multimedia 2007, Augsburg, Germany, September 24-29, 2007
作者:  Liu, Jing;  Wang, Bin;  Li, Mingjing;  Li, Zhiwei;  Ma, Wei-Ying;  Lu, Hanqing;  Ma, Songde
浏览  |  Adobe PDF(1404Kb)  |  收藏  |  浏览/下载：363/102  |  提交时间：2016/04/13
Kernel-based nonlinear discriminant analysis for face recognition 期刊论文
JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY, 2003, 卷号: 18, 期号: 6, 页码: 788-795
作者:  Liu, QS;  Huang, R;  Lu, HQ;  Ma, SD
收藏  |  浏览/下载：169/0  |  提交时间：2015/11/08
Linear Subspace Analysis  Kernel-based Nonlinear Discriminant Analysis  Kernel-based Principal Component Analysis  Face Recognition  
A graph-based image annotation framework 期刊论文
PATTERN RECOGNITION LETTERS, 2008, 卷号: 29, 期号: 4, 页码: 407-415
作者:  Liu, Jing;  Wang, Bin;  Lu, Hanqing;  Ma, Songde
浏览  |  Adobe PDF(225Kb)  |  收藏  |  浏览/下载：455/168  |  提交时间：2015/11/08
Image Annotation  Annotation Refinement  Graph Learning  Image Relation  Word Relation  
Face recognition using kernel scatter-difference-based discriminant analysis 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS, 2006, 卷号: 17, 期号: 4, 页码: 1081-1085
作者:  Liu, Qingshan;  Tang, Xiaoou;  Lu, Hanqing;  Ma, Songde
收藏  |  浏览/下载：110/0  |  提交时间：2015/11/08
Face Recognition  Fisher Linear Discriminant Analysis  Kernel Scatter-difference-based Discriminant Analysis