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CASIA OpenIR
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DCAT: Dual Cross-Attention-Based Transformer for Change Detection 期刊论文
Remote Sensing, 2023, 卷号: 15, 期号: 9, 页码: 2395
作者:  Yuan Zhou;  Chunlei Huo;  Jiahang Zhu;  Leigang Huo;  Chunhong Pan
Adobe PDF(47919Kb)  |  收藏  |  浏览/下载：138/19  |  提交时间：2023/06/16
change detection  transformer  dual cross-attention  remote sensing  
HENet: Head-Level Ensemble Network for Very High Resolution Remote Sensing Images Semantic Segmentation 期刊论文
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2022, 卷号: 19, 页码: 5
作者:  Cao, Yong;  Huo, Chunlei;  Xu, Nuo;  Zhang, Xin;  Xiang, Shiming;  Pan, Chunhong
收藏  |  浏览/下载：233/0  |  提交时间：2022/06/06
Head  Computational modeling  Semantics  Image segmentation  Feature extraction  Correlation  Mathematical models  Cooperative learning (CL)  ensemble learning  semantic segmentation  
CMT: Cross Mean Teacher Unsupervised Domain Adaptation for VHR Image Semantic Segmentation 期刊论文
IEEE Geoscience and Remote Sensing Letters, 2021, 卷号: 0, 期号: 0, 页码: 1-5
作者:  Liang Yan;  Bin Fan;  Shiming Xiang;  Chunhong Pan
Adobe PDF(1700Kb)  |  收藏  |  浏览/下载：163/36  |  提交时间：2021/06/15
Cross mean teacher (CMT)  self-training (ST)  semantic segmentation  unsupervised domain adaptation (UDA)  very-high-resolution (VHR) image  
Triplet Adversarial Domain Adaptation for Pixel-Level Classification of VHR Remote Sensing Images 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2020, 卷号: 58, 期号: 5, 页码: 3558-3573
作者:  Yan, Liang;  Fan, Bin;  Liu, Hongmin;  Huo, Chunlei;  Xiang, Shiming;  Pan, Chunhong
Adobe PDF(6348Kb)  |  收藏  |  浏览/下载：355/68  |  提交时间：2020/06/22
Domain adaptation (DA)  pixel-level classification  self-training  triplet adversarial learning  very high resolution (VHR)  
Semantic labeling in very high resolution images via a self-cascaded convolutional neural network 期刊论文
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2018, 卷号: 145, 期号: 1, 页码: 78-95
作者:  Liu, Yongcheng;  Fan, Bin;  Wang, Lingfeng;  Bai, Jun;  Xiang, Shiming;  Pan, Chunhong
浏览  |  Adobe PDF(1679Kb)  |  收藏  |  浏览/下载：490/101  |  提交时间：2019/01/08
Semantic labeling  Convolutional neural networks (CNNs)  Multi-scale contexts  End-to-end  
Simultaneous change region and pattern identification for very high-resolution images 期刊论文
JOURNAL OF APPLIED REMOTE SENSING, 2017, 卷号: 11
作者:  Huo, Chunlei;  Huo, Leigang;  Zhou, Zhixin;  Pan, Chunhong
收藏  |  浏览/下载：244/0  |  提交时间：2018/03/03
Change Detection  Change Pattern  Feature Classification  Feature Learning  Distance Tuning  
Efficient Sea--Land Segmentation Using Seeds Learning and Edge Directed Graph Cut 期刊论文
Neurocomputing, 2016, 期号: 207, 页码: 36-47
作者:  Cheng, Dongcai;  Meng, Gaofeng;  Xiang, Shiming;  Pan, Chunhong
浏览  |  Adobe PDF(5764Kb)  |  收藏  |  浏览/下载：356/75  |  提交时间：2017/12/06
Sea--land Segmentation  Graph Cut (Gc)  Superpixel  Multi-feature Descriptor  Seeds Learning  
Gated Convolutional Neural Network for Semantic Segmentation in High-Resolution Images 期刊论文
REMOTE SENSING, 2017, 卷号: 9, 期号: 5, 页码: 446
作者:  Wang, Hongzhen;  Wang, Ying;  Zhang, Qian;  Xiang, Shiming;  Pan, Chunhong
浏览  |  Adobe PDF(2410Kb)  |  收藏  |  浏览/下载：462/95  |  提交时间：2017/07/18
Semantic Segmentation  Cnn  Deep Learning  Isprs  Remote Sensing  Gate  
Automatic Road Detection and Centerline Extraction via Cascaded End-to-End Convolutional Neural Network 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2017, 卷号: 55, 期号: 6, 页码: 3322-3337
作者:  Cheng, Guangliang;  Wang, Ying;  Xu, Shibiao;  Wang, Hongzhen;  Xiang, Shiming;  Pan, Chunhong
浏览  |  Adobe PDF(11402Kb)  |  收藏  |  浏览/下载：591/121  |  提交时间：2017/05/09
Cascaded Convolutional Neural Network (Casnet)  End-to-end  Road Centerline Extraction  Road Detection  
Accurate urban road centerline extraction from VHR imagery via multiscale segmentation and tensor voting 期刊论文
Neurocomputing, 2016, 期号: 205, 页码: 407-420
作者:  Cheng GL(程光亮);  Zhu FY(朱飞云);  Xiang SM(向世明);  Wang Y(王颖);  Pan CH(潘春洪)
浏览  |  Adobe PDF(4943Kb)  |  收藏  |  浏览/下载：458/153  |  提交时间：2017/05/09
Road Centerline Extraction  Multiscale Segmentation  Tensor Voting  Non-maximum Suppression  Fitting Based Centerline Connection