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Labeling Complicated Objects: Multi-View Multi-Instance Multi-Label Learning 会议论文
, Québec City, Québec, Canada, July 27 - 31, 2014
作者:  Nguyen, Cam-Tu;  Wang, Xiaoliang;  Liu J(刘静);  Zhou, Zhi-Hua
Adobe PDF(305Kb)  |  收藏  |  浏览/下载:217/63  |  提交时间:2018/03/03
Face image super-resolution through locality-induced support regression 期刊论文
Signal Processing, 2014, 期号: 103, 页码: 168-183
作者:  Junjun Jiang;  Ruimin Hu;  Chao Liang;  Zhen Han;  Chunjie Zhang
浏览  |  Adobe PDF(5003Kb)  |  收藏  |  浏览/下载:326/112  |  提交时间:2017/09/19
Super-resolution  Face Image  Support Regression  Manifold Learning  
Online reinforcement learning for continuous-state systems 专著章节/文集论文
出自: Frontiers of Intelligent Control and Information Processing, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, 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Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore:World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World 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Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, 2014
作者:  Yuanheng Zhu;  Zhao DB(赵冬斌)
Adobe PDF(24150Kb)  |  收藏  |  浏览/下载:264/29  |  提交时间:2017/09/13
Semi-Supervised Subspace Segmentation 会议论文
Proc. IEEE International Conference on Image Processing, Paris, France, 2014
作者:  Dong Wang;  Qiyue Yin;  Ran He(赫然);  Liang Wang;  Tieniu Tan
浏览  |  Adobe PDF(361Kb)  |  收藏  |  浏览/下载:360/110  |  提交时间:2017/02/25
A New Method Combining LDA and PLS for Dimension Reduction. 期刊论文
PLos One, 2014, 卷号: 9(5), 期号: 5, 页码: e96944-e96944 (SCI)
作者:  Tang, Liang;  Peng, Silong;  Bi, Yiming;  Shan, Peng;  Hu, Xiyuan,
Adobe PDF(770Kb)  |  收藏  |  浏览/下载:155/0  |  提交时间:2017/01/13
Modified Split Hopkinson Torsional Bars  Shear Localization  Microstructural Evolution  
Robust Recognition via Information Theoretic Learning 专著
Newyork, USA:Springer, 2014
作者:  Ran He(赫然);  Baogang Hu;  Xiaotong Yuan;  Liang Wang
浏览  |  Adobe PDF(2846Kb)  |  收藏  |  浏览/下载:430/130  |  提交时间:2016/08/11
A Real-time Small Moving Object Detection System Based on Infrared Images 会议论文
Proceedings of 2014 IEEE International Conference on Mechatronics and Automation, Tianjin, China, August 3-6, 2014
作者:  Zhao Wang;  Haitao Song;  Han Xiao;  Wenhao He;  Jiaojiao Gu;  Kui Yuan
浏览  |  Adobe PDF(773Kb)  |  收藏  |  浏览/下载:426/120  |  提交时间:2015/11/25
Learning Robust Face Representation With Classwise Block-Diagonal Structure 期刊论文
IEEE Transactions on Information Forensics and Security, 2014, 卷号: 9, 期号: 12, 页码: 2051-2062
作者:  Li, Yong;  Liu, Jing;  Lu, Hanqing;  Ma, Songde
浏览  |  Adobe PDF(2662Kb)  |  收藏  |  浏览/下载:446/138  |  提交时间:2015/09/21
Robust Face Recognition  Low-rank And Sparse Representation  Classwise Block-diagonal Structure  
基于物理及数据驱动的特效动画模拟 学位论文
, 中国科学院自动化研究所: 中国科学院大学, 2014
作者:  徐士彪
Adobe PDF(14234Kb)  |  收藏  |  浏览/下载:312/0  |  提交时间:2015/09/02
特效动画  水墨扩散  水滴散落  表情动画  Effects Animation  Ink Diffusion  Water Droplets  Facial Animation  
A new Pansharp based method for PET/CT image fusion 会议论文
International Symposium on Biomedical Imaging (ISBI), Beijing, China, 2014
作者:  Mu, Wei;  Chen, Zhe;  Tian, Jie;  Zhu, Zhaohui;  Dong, Di;  Jie Tian
浏览  |  Adobe PDF(764Kb)  |  收藏  |  浏览/下载:345/112  |  提交时间:2015/08/19
Pet/ct  Image Fusion  Parsharp Model