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Exploring Intrinsic Discrimination and Consistency for Weakly Supervised Object Localization 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2024, 卷号: 33, 期号: 0, 页码: 1045 - 1058
作者:  Changwei Wang;  Rongtao Xu;  Shibiao Xu;  Weiliang Meng;  Ruisheng Wang;  Xiaopeng Zhang
Adobe PDF(3269Kb)  |  收藏  |  浏览/下载：55/17  |  提交时间：2024/05/29
Weakly supervised object localization  intrinsic discrimination and consistency  deep metric learning  geometric transformation consistency  
Domain Adaptation by Class Centroid Matching and Local Manifold Self-Learning 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 卷号: 29, 页码: 9703-9718
作者:  Tian, Lei;  Tang, Yongqiang;  Hu, Liangchen;  Ren, Zhida;  Zhang, Wensheng
Adobe PDF(3443Kb)  |  收藏  |  浏览/下载：373/77  |  提交时间：2021/01/06
Domain adaptation  class centroid matching  local manifold self-learning  
Removing Turbulence Effect via Hybrid Total Variation and Deformation-Guided Kernel Regression 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2016, 卷号: 25, 期号: 10, 页码: 4943-4958
作者:  Xie, Yuan;  Zhang, Wensheng;  Tao, Dacheng;  Hu, Wenrui;  Qu, Yanyun;  Wang, Hanzi;  Yuan Xie
浏览  |  Adobe PDF(9193Kb)  |  收藏  |  浏览/下载：525/158  |  提交时间：2016/10/22
Image Restoration  Atmospheric Turbulence  Total Variation  Deformation-guided Kernel  
Robust Hyperspectral Unmixing With Correntropy-Based Metric 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2015, 卷号: 24, 期号: 11, 页码: 4027-4040
作者:  Wang, Ying;  Pan, Chunhong;  Xiang, Shiming;  Zhu, Feiyun
浏览  |  Adobe PDF(4371Kb)  |  收藏  |  浏览/下载：411/82  |  提交时间：2015/09/23
Hyperspectral Unmixing  Linear Mixture Model  Non-negative Matrix Factorization  Robust Estimation  Correntropy Based Metric  
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：400/113  |  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)