Extracting ship and heading from Sentinel-2 images using convolutional neural networks with point and vector learningOA
Extracting ship and heading from Sentinel-2 images using convolutional neural networks with point and vector learning
Xiunan LI;Peng CHEN;Jingsong YANG;Wentao AN;Dan LUO;Gang ZHENG;Aiying LU
Ocean College,Zhejiang University,Zhoushan 316021,China||State Key Laboratory of Satellite Ocean Environment Dynamics,Second Institute of Oceanography,Ministry of Natural Resources,Hangzhou 310012,ChinaState Key Laboratory of Satellite Ocean Environment Dynamics,Second Institute of Oceanography,Ministry of Natural Resources,Hangzhou 310012,ChinaOcean College,Zhejiang University,Zhoushan 316021,China||State Key Laboratory of Satellite Ocean Environment Dynamics,Second Institute of Oceanography,Ministry of Natural Resources,Hangzhou 310012,ChinaNational Satellite Ocean Application Service,Ministry of Natural Resources,Beijing 100081,ChinaOcean College,Zhejiang University,Zhoushan 316021,China||State Key Laboratory of Satellite Ocean Environment Dynamics,Second Institute of Oceanography,Ministry of Natural Resources,Hangzhou 310012,ChinaState Key Laboratory of Satellite Ocean Environment Dynamics,Second Institute of Oceanography,Ministry of Natural Resources,Hangzhou 310012,ChinaState Key Laboratory of Satellite Ocean Environment Dynamics,Second Institute of Oceanography,Ministry of Natural Resources,Hangzhou 310012,China
deep learningship detectionheadingremote sensingSentinel-2
deep learningship detectionheadingremote sensingSentinel-2
《海洋湖沼学报（英文版）》 2025 (1)
16-28,13
Supported by the National Key R&D Program of China(No.2022YFB3902400)and the China High Resolution Earth Observation System Program(No.41-Y30F07-9001-20/22)
评论