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Exploiting Frequency-Domain Information of GNSS Reflectometry for Sea Surface Wind Speed Retrieval 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2023, 卷号: 61, 页码: 13
作者:  Chen, Keran;  Zhou, Yuan;  Li, Shuoshi;  Wang, Ping;  Li, Xiaofeng
收藏  |  浏览/下载：60/0  |  提交时间：2023/12/13
Cyclone global navigation satellite system (CyGNSS)  deep learning  frequency domain  global navigation satellite system reflectometry (GNSS-R)  wind speed retrieval  
Development of a Dual-Attention U-Net Model for Sea Ice and Open Water Classification on SAR Images 期刊论文
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2022, 卷号: 19, 页码: 5
作者:  Ren, Yibin;  Li, Xiaofeng;  Yang, Xiaofeng;  Xu, Huan
Adobe PDF(8369Kb)  |  收藏  |  浏览/下载：213/0  |  提交时间：2022/02/18
Sea ice  Radar polarimetry  Feature extraction  Decoding  Oceans  Kernel  Image segmentation  Dual-attention  sea ice and open water classification  synthetic aperture radar (SAR) image  U-Net  
A Data-Driven Deep Learning Model for Weekly Sea Ice Concentration Prediction of the Pan-Arctic During the Melting Season 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 卷号: 60, 页码: 19
作者:  Ren, Yibin;  Li, Xiaofeng;  Zhang, Wenhao
Adobe PDF(22032Kb)  |  收藏  |  浏览/下载：138/0  |  提交时间：2022/07/18
Deep fully convolutional networks (FCNs)  recursively predicting  satellite-derived sea ice concentration (SIC)  SIC prediction  temporal-spatial attention  
The Fusion of Physical, Textural, and Morphological Information in SAR Imagery for Hurricane Wind Speed Retrieval Based on Deep Learning 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 卷号: 60, 页码: 13
作者:  Mu, Shanshan;  Li, Xiaofeng;  Wang, Haoyu
Adobe PDF(2103Kb)  |  收藏  |  浏览/下载：208/0  |  提交时间：2022/07/18
Hurricanes  Synthetic aperture radar  Wind speed  Radar polarimetry  Sea surface  Sea measurements  Data models  Deep learning  hurricane wind  synthetic aperture radar (SAR)  
Multilayer Fusion Recurrent Neural Network for Sea Surface Height Anomaly Field Prediction 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 卷号: 60, 页码: 11
作者:  Zhou, Yuan;  Lu, Chang;  Chen, Keran;  Li, Xiaofeng
Adobe PDF(5381Kb)  |  收藏  |  浏览/下载：192/0  |  提交时间：2022/04/12
Computer architecture  Microprocessors  Predictive models  Mathematical models  Sea surface  Data models  Satellites  Deep learning (DL)  field prediction  satellite remote sensing data  sea surface height anomaly (SSHA)