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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 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, 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：257/28  |  提交时间：2017/09/13
RGB-D视频处理与三维目标跟踪 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:  刘绍国
Adobe PDF(4894Kb)  |  收藏  |  浏览/下载：481/0  |  提交时间：2015/09/02
Rgb-d视频处理  深度图像复原  模糊核大小估计  图匹配  单应矩阵估计  三维头部姿态估计  Rgb-d Video Processing  Blur-kernel Size Estimation  Graph Matching  Homography Estimation  3d Head Pose Estimatio  
基于主动学习的图像分类与检索 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:  钮彪
Adobe PDF(15203Kb)  |  收藏  |  浏览/下载：276/0  |  提交时间：2015/09/02
图像内容分析  语义标注  图像检索  相关反馈  Image Content Analysis  Semantic Annotation  Image Retrieval  Relevance Feedback  
摄像机一维标定的加权线性算法研究 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:  史坤峰
Adobe PDF(4235Kb)  |  收藏  |  浏览/下载：169/0  |  提交时间：2015/09/02
摄像机标定  一维物体  加权线性算法  一阶误差分析  Camera Calibration  1d Objects  Weighted Linear Algorithm  First-order Error Analysis  
3D object tracking via boundary constrained region-based model 会议论文
International Conference on Image Processing (ICIP), Paris, France, 2014
作者:  Song Zhao;  LingFeng Wang;  Wei Sui;  Huai-Yu Wu;  Chunhong Pan
Adobe PDF(1659Kb)  |  收藏  |  浏览/下载：576/111  |  提交时间：2015/08/19
Boundary Term  Occlusion-aware Updating  Pose Tracking  Stochastic Optimization  
Structured Sparse Method for Hyperspectral Unmixing 期刊论文
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2014, 卷号: 88, 页码: 101-118
作者:  Zhu, Feiyun;  Wang, Ying;  Xiang, Shiming;  Fan, Bin;  Pan, Chunhong
Adobe PDF(10734Kb)  |  收藏  |  浏览/下载：364/72  |  提交时间：2015/08/12
Hyperspectral Unmixing (Hu)  Hyperspectral Image Analysis  Structured Sparse Nmf (ss-Nmf)  Mixed Pixel  Nonnegative Matrix Factorization (Nmf)  
Spectral Unmixing via Data-Guided Sparsity 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2014, 卷号: 23, 期号: 12, 页码: 5412-5427
作者:  Zhu, Feiyun;  Wang, Ying;  Fan, Bin;  Xiang, Shiming;  Meng, Gaofeng;  Pan, Chunhong
Adobe PDF(6232Kb)  |  收藏  |  浏览/下载：390/109  |  提交时间：2015/08/12
Data-guided Sparse (Dgs)  Data-guided Map (dgMap)  Nonnegative Matrix Factorization (Nmf)  Dgs-nmf  Mixed Pixel  Hyperspectral Unmixing (Hu)  
Beyond visual word ambiguity: Weighted local feature encoding with governing region 期刊论文
JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 2014, 卷号: 25, 期号: 6, 页码: 1387-1398
作者:  Zhang, Chunjie;  Xiao, Xian;  Pang, Junbiao;  Liang, Chao;  Zhang, Yifan;  Huang, Qingming
Adobe PDF(2537Kb)  |  收藏  |  浏览/下载：276/45  |  提交时间：2015/08/12
Visual Word Ambiguity  Governing Region  Weighted Encoding  Image Classification  Sparse  Bag-of-visual Words  Object Categorization  Locality Constraint  
Image classification by non-negative sparse coding, correlation constrained low-rank and sparse decomposition 期刊论文
COMPUTER VISION AND IMAGE UNDERSTANDING, 2014, 卷号: 123, 页码: 14-22
作者:  Zhang, Chunjie;  Liu, Jing;  Liang, Chao;  Xue, Zhe;  Pang, Junbiao;  Huang, Qingming
Adobe PDF(2664Kb)  |  收藏  |  浏览/下载：365/99  |  提交时间：2015/08/12
Sparse Coding  Image Classification  Low-rank Decomposition  Non-negative  Correlation Constrained  
Function-structure associations of the brain: Evidence from multimodal connectivity and covariance studies 期刊论文
NEUROIMAGE, 2014, 卷号: 102, 期号: 1, 页码: 11-23
作者:  Sui Jing(隋婧);  Huster, Rene;  Yu, Qingbao;  Segall, Judith M.;  Calhoun, Vince D.
Adobe PDF(513Kb)  |  收藏  |  浏览/下载：268/50  |  提交时间：2015/08/12
Multimodal Fusion  Fmri  Smri  Diffusion Mri  Eeg  Brain Connectivity