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• 地理科学与资源研究... [37]

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• OAI收割 [37]

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• 期刊论文 [31]
• SCI/SSCI论文 [5]
• 会议论文 [1]

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• 2023 [2]
• 2022 [4]
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• Analytical... [1]
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浏览/检索结果: 共37条，第1-10条 帮助 限定条件 专题：地理科学与资源研究所    第一署名单位    第一作者单位    通讯作者单位     条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择提交时间升序提交时间降序发表日期升序发表日期降序题名升序题名降序作者升序作者降序 Super-Resolution Rural Road Extraction from Sentinel-2 Imagery Using a Spatial Relationship-Informed Network 期刊论文  OAI收割 REMOTE SENSING, 2023, 卷号: 15, 期号: 17, 页码: 18 作者:  Jia, Yuanxin;  Zhang, Xining;  Xiang, Ru;  Ge, Yong   |  收藏  |  浏览/下载：8/0  |  提交时间：2023/10/09 spatial relationship  deep learning  super-resolution mapping  rural road extraction  feature enhancement   High-quality super-resolution mapping using spatial deep learning 期刊论文  OAI收割 ISCIENCE, 2023, 卷号: 26, 期号: 6, 页码: 106875 作者:  Zhang, Xining;  Ge, Yong;  Chen, Jin;  Ling, Feng;  Wang, Qunming   |  收藏  |  浏览/下载：11/0  |  提交时间：2023/08/22 Micro-Distribution of Elements and Speciation of Arsenic in the Sporangium of Pteris Vittata 期刊论文  OAI收割 SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 卷号: 42, 期号: 2, 页码: 478-482 作者:  Wan Xiao-ming;  Zeng Wei-bin;  Lei Mei;  Chen Tong-bin   |  收藏  |  浏览/下载：21/0  |  提交时间：2022/09/21 Synchrotron radiation X-ray absorption spectroscopy  X-ray fluorescence microprobe  Pteris vittata  Spore  Arsenic speciation   Micro-Distribution of Elements and Speciation of Arsenic in the Sporangium of Pteris Vittata 期刊论文  OAI收割 SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 卷号: 42, 期号: 2, 页码: 478-482 作者:  Wan Xiao-ming;  Zeng Wei-bin;  Lei Mei;  Chen Tong-bin   |  收藏  |  浏览/下载：16/0  |  提交时间：2022/09/21 Synchrotron radiation X-ray absorption spectroscopy  X-ray fluorescence microprobe  Pteris vittata  Spore  Arsenic speciation   Generating Fine-Scale Aerosol Data through Downscaling with an Artificial Neural Network Enhanced with Transfer Learning 期刊论文  OAI收割 ATMOSPHERE, 2022, 卷号: 13, 期号: 2, 页码: 18 作者:  Wang, Menglin;  Franklin, Meredith;  Li, Lianfa   |  收藏  |  浏览/下载：13/0  |  提交时间：2022/09/21 downscaling  artificial neural network  transfer learning  deep learning  G5NR  MERRA-2   Fast and Slow Changes Constrained Spatio-Temporal Subpixel Mapping 期刊论文  OAI收割 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 卷号: 60, 页码: 16 作者:  Zhang, Chengyuan   |  收藏  |  浏览/下载：15/0  |  提交时间：2022/09/21 Spatial resolution  Neurons  Monitoring  Image resolution  Uncertainty  Remote sensing  Satellites  Downscaling  Hopfield neural network (HNN)  land cover and land use (LCLU)  spatio-temporal dependence  subpixel mapping (SPM)  super-resolution mapping   Applications of Deep Learning-Based Super-Resolution for Sea Surface Temperature Reconstruction 期刊论文  OAI收割 IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2021, 卷号: 14, 页码: 887-896 作者:  Ping, Bo;  Su, Fenzhen;  Han, Xingxing;  Meng, Yunshan   |  收藏  |  浏览/下载：22/0  |  提交时间：2021/06/10 Advanced microwave scanning radiometer 2 (AMSR2)  deep learning  moderate-resolution imaging spectroradiometer (MODIS)  sea surface temperature  super-resolution   Graph Convolutional Networks-Based Super-Resolution Land Cover Mapping 期刊论文  OAI收割 IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2021, 卷号: 14, 页码: 7667-7681 作者:  Zhang, Xining;  Ge, Yong;  Ling, Feng;  Chen, Jin;  Chen, Yuehong   |  收藏  |  浏览/下载：22/0  |  提交时间：2021/11/05 Deep neural networks (DNNs)  graph convolutional networks (GCNs)  land cover  subpixel  super-resolution mapping (SRM).   Graph Convolutional Networks-Based Super-Resolution Land Cover Mapping 期刊论文  OAI收割 IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2021, 卷号: 14, 页码: 7667-7681 作者:  Zhang, Xining;  Ge, Yong;  Ling, Feng;  Chen, Jin;  Chen, Yuehong   |  收藏  |  浏览/下载：9/0  |  提交时间：2021/11/05 Deep neural networks (DNNs)  graph convolutional networks (GCNs)  land cover  subpixel  super-resolution mapping (SRM).   Internal Learning for Image Super-Resolution by Adaptive Feature Transform 期刊论文  OAI收割 SYMMETRY-BASEL, 2020, 卷号: 12, 期号: 10, 页码: 19 作者:  He, Yifan;  Cao, Wei;  Du, Xiaofeng;  Chen, Changlin   |  收藏  |  浏览/下载：20/0  |  提交时间：2021/03/16 super-resolution  internal learning  feature transform  deep convolutional neural network