CASIA OpenIR

浏览/检索结果: 共51条,第1-10条 帮助

限定条件    
已选(0)清除 条数/页:   排序方式:
Image Fingerprinting Based on Improved Image Normalization and DFT 会议论文
2014 2nd International Conference on Signal Processing, Image Processing and Pattern Recognition, Guilin, Guangxi, China, 2014.3.29-2014.3.30
作者:  Hu Guan;  Zhi Zeng;  Jie Liu;  Shuwu Zhang
浏览  |  Adobe PDF(3629Kb)  |  收藏  |  浏览/下载:343/112  |  提交时间:2017/09/20
Image Fingerprinting  Image Hashing  Zero Watermarking  Image Normalization  
A Novel Robust Digital Image Watermarking Algorithm based on Two Level DCT 会议论文
2014 International Conference on Information Science, Electronics and Electrical Engineering, Hokkaido,Japan, 2014.4.26-2014.4.28
作者:  Hu Guan;  Zhi Zeng;  Jie Liu;  Shuwu Zhang
浏览  |  Adobe PDF(209Kb)  |  收藏  |  浏览/下载:386/108  |  提交时间:2017/09/20
Digital Image Watermarking  Discrete Cosine Transformation  Invisibility  Robustness  
Transform-Invariant Dictionary Learning For Face Recognition 会议论文
, France, 2014年10月27-30日
作者:  Shu Zhang;  Man Zhang;  Ran He(赫然);  Zhenan Sun
浏览  |  Adobe PDF(268Kb)  |  收藏  |  浏览/下载:165/66  |  提交时间:2017/09/16
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, 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, 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, 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:277/35  |  提交时间:2017/09/13
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:158/0  |  提交时间:2017/01/13
Modified Split Hopkinson Torsional Bars  Shear Localization  Microstructural Evolution  
CSMMI: Class-Specific Maximization of Mutual Information for Action and Gesture Recognition 期刊论文
IEEE Transactions on Image Processing, 2014, 卷号: 23, 期号: 7, 页码: 3152-3165
作者:  Jun, Wan;  Wan J(万军)
浏览  |  Adobe PDF(5217Kb)  |  收藏  |  浏览/下载:266/72  |  提交时间:2016/10/26
Intra-class Mutual Information  Inter-class Mutual Information  Class-specific Dictionary  Action Recognition  
Discriminative Representative Selection via Structure Sparsity 会议论文
In Proceedings of the 22nd International Conference on Pattern Recognition (ICPR) 2014, Stockholm, August 24-28
作者:  Wang, Baoxing;  Yin, Qiyue;  Wu, Shu;  Wang, Liang
浏览  |  Adobe PDF(579Kb)  |  收藏  |  浏览/下载:265/118  |  提交时间:2016/10/24
Representative Selection  Structure Sparsity  
Image denoising via nonlocally sparse coding and tensor decomposition 会议论文
ACM International Conference Proceeding Series, 2014:283-288, Xiamen, China, July 10, 2014 - July 12, 2014
作者:  Wenrui Hu;  Yuan Xie;  Wensheng Zhang;  Limin Zhu;  Yanyun Qu;  Yuanhua Tan
浏览  |  Adobe PDF(601Kb)  |  收藏  |  浏览/下载:352/133  |  提交时间:2016/10/22
Collaborative Filtering  Sparse Coding  Ttensor Decomposition  Bregman Iteration  
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:436/133  |  提交时间:2016/08/11
Efficient Feature Coding Based on Auto-encoder Network for Image Classification 会议论文
Procceding of ACCV 2014, 新加坡, 2014-11
作者:  Xie, Guo-Sen;  Zhang, Xu-Yao;  Liu, Cheng-Lin
浏览  |  Adobe PDF(622Kb)  |  收藏  |  浏览/下载:290/81  |  提交时间:2016/07/14
Feature Coding