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Tropical Cyclone Intensity Estimation From Geostationary Satellite Imagery Using Deep Convolutional Neural Networks 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 卷号: 60, 页码: 16
作者:  Wang, Chong;  Zheng, Gang;  Li, Xiaofeng;  Xu, Qing;  Liu, Bin;  Zhang, Jun
Adobe PDF(4821Kb)  |  收藏  |  浏览/下载：192/0  |  提交时间：2022/02/18
Estimation  Ocean temperature  Clouds  Tropical cyclones  Cyclones  Training  Geostationary satellites  Convolutional neural network (CNN)  deep learning  remote sensing  tropical cyclone (TC)  
A Deep Learning Model to Extract Ship Size From Sentinel-1 SAR Images 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 卷号: 60, 页码: 14
作者:  Ren, Yibin;  Li, Xiaofeng;  Xu, Huan
Adobe PDF(12529Kb)  |  收藏  |  浏览/下载：121/0  |  提交时间：2022/02/18
Marine vehicles  Radar polarimetry  Feature extraction  Synthetic aperture radar  Data mining  Radar imaging  Oceans  Custom loss function  deep learning (DL)  deep neural network (DNN) regression  ship size extraction  synthetic aperture radar (SAR) image  
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：132/0  |  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：186/0  |  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：181/0  |  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)  
Combination of Satellite Observations and Machine Learning Method for Internal Wave Forecast in the Sulu and Celebes Seas 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2021, 卷号: 59, 期号: 4, 页码: 2822-2832
作者:  Zhang, Xudong;  Li, Xiaofeng
Adobe PDF(28337Kb)  |  收藏  |  浏览/下载：204/0  |  提交时间：2021/06/24
Oceans  Predictive models  Satellite broadcasting  MODIS  Satellites  Machine learning  Spatial resolution  Celebes sea  internal wave (IW)  machine learning  Sulu sea