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Automatic Extraction of Water and Shadow from SAR Images Based on a Multi-Resolution Dense Encoder and Decoder Network.

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第一作者： Peng,Zhang

第一单位： School of Electrical and Information Engineering, Changsha University of Science & Technology, Changsha 410114, China.;Laboratory of Radar Remote Sensing Applications, Changsha University of Science & Technology, Changsha 410014, China.

作者： Peng,Zhang ^[1] ; Lifu,Chen ^[2] ; Zhenhong,Li ^[3] ; Jin,Xing ^[4] ; Xuemin,Xing ^[5] ; Zhihui,Yuan ^[1]

作者单位： School of Electrical and Information Engineering, Changsha University of Science & Technology, Changsha 410114, China.;Laboratory of Radar Remote Sensing Applications, Changsha University of Science & Technology, Changsha 410014, China. ^[1] School of Electrical and Information Engineering, Changsha University of Science & Technology, Changsha 410114, China. Lifu.Chen@newcastle.ac.uk.;Laboratory of Radar Remote Sensing Applications, Changsha University of Science & Technology, Changsha 410014, China. Lifu.Chen@newcastle.ac.uk.;School of Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU, UK. Lifu.Chen@newcastle.ac.uk. ^[2] School of Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU, UK.;College of Geological Engineering and Geomatics, Chang'an University, Xi'an 710054, China. ^[3] School of Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU, UK. ^[4] Laboratory of Radar Remote Sensing Applications, Changsha University of Science & Technology, Changsha 410014, China.;School of Traffic & Transportation Engineering, Changsha University of Science & Technology, Changsha 410114, China. ^[5]

关键词 CONVOLUTION LONG SHORT-TERM MEMORY (ConvLSTM)classification convolutional neural network (CNN)deep learning dense convolutional network (DenseNet)global convolutional network (GCN)shadow extraction synthetic aperture radar (SAR)water extraction

DOI 10.3390/s19163576

PMID 31426396

发布时间 2020-02-25

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