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CASIA OpenIR
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Building Regional Covariance Descriptors for Vehicle Detection 期刊论文
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2017, 卷号: 14, 期号: 4, 页码: 524-528
作者:  Chen, Xueyun;  Gong, Ren-Xi;  Xie, Ling-Ling;  Xiang, Shiming;  Liu, Cheng-Lin;  Pan, Chun-Hong
浏览  |  Adobe PDF(1623Kb)  |  收藏  |  浏览/下载：378/113  |  提交时间：2017/09/12
Deep Convolutional Neural Networks (Dcnns)  Regional Covariance Descriptor (Rcd)  Vehicle Detection  
Feature Extraction by Rotation-Invariant Matrix Representation for Object Detection in Aerial Image 期刊论文
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2017, 卷号: 14, 期号: 6, 页码: 851-855
作者:  Wang, Guoli;  Wang, Xinchao;  Fan, Bin;  Pan, Chunhong
Adobe PDF(1324Kb)  |  收藏  |  浏览/下载：436/174  |  提交时间：2017/05/09
Feature Extraction  Fisher Vector  Object Detection  Ring Pyramid Pooling (Rpp)  Rotation-invariant Matrix (Rim)  
Multilevel SIFT Matching for Large-Size VHR Image Registration 期刊论文
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2012, 卷号: 9, 期号: 2, 页码: 171-175
作者:  Huo, Chunlei;  Pan, Chunhong;  Huo, Leigang;  Zhou, Zhixin
Adobe PDF(659Kb)  |  收藏  |  浏览/下载：287/102  |  提交时间：2015/08/12
Coarse-to-fine Strategy  Geometric Constraint  Large-size Image Registration  Parallel-based Architecture  
Registration of Optical and SAR Satellite Images by Exploring the Spatial Relationship of the Improved SIFT 期刊论文
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2013, 卷号: 10, 期号: 4, 页码: 657-661
作者:  Fan, Bin;  Huo, Chunlei;  Pan, Chunhong;  Kong, Qingqun
Adobe PDF(753Kb)  |  收藏  |  浏览/下载：339/144  |  提交时间：2015/08/12
Optical And Sar Image Registration  Remote Sensing  Scale-invariant Feature Transform (Sift)  Spatial Consistent Matching (Scm)  Synthetic Aperture Radar (Sar)  
Change Field: A New Change Measure for VHR Images 期刊论文
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2014, 卷号: 11, 期号: 10, 页码: 1812-1816
作者:  Huo, Leigang;  Feng, Xiangchu;  Huo, Chunlei;  Zhou, Zhixin;  Pan, Chunhong
Adobe PDF(656Kb)  |  收藏  |  浏览/下载：267/62  |  提交时间：2015/08/12
Change Detection  Change Field  Progressive Transductive Classification  Very High Resolution (Vhr) Images