Automatic Mapping of Tropical Cyclone-Induced Coastal Inundation in SAR Imagery Based on Clustering of Deep Features
Researchers have already verified that the deep learning (DL) technology can realize accurate and robust mapping of tropical cyclone-induced coastal inundation in synthetic aperture radar imagery. In order to liberate the DL-based inundation mapping from human supervision, we propose to use the clus...
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| Veröffentlicht in: | IEEE International Geoscience and Remote Sensing Symposium proceedings S. 5765 - 5768 |
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26.09.2020
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| Abstract | Researchers have already verified that the deep learning (DL) technology can realize accurate and robust mapping of tropical cyclone-induced coastal inundation in synthetic aperture radar imagery. In order to liberate the DL-based inundation mapping from human supervision, we propose to use the clustering of deep convolutional autoencoder-generated features. The mapping results of Lekima 2019-induced inundation demonstrate the advantages and availability of the proposed method. |
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| AbstractList | Researchers have already verified that the deep learning (DL) technology can realize accurate and robust mapping of tropical cyclone-induced coastal inundation in synthetic aperture radar imagery. In order to liberate the DL-based inundation mapping from human supervision, we propose to use the clustering of deep convolutional autoencoder-generated features. The mapping results of Lekima 2019-induced inundation demonstrate the advantages and availability of the proposed method. |
| Author | Liu, Bin Zheng, Gang Li, Xiaofeng |
| Author_xml | – sequence: 1 givenname: Bin surname: Liu fullname: Liu, Bin organization: College of Marine Sciences, Shanghai Ocean University,Shanghai,China,201306 – sequence: 2 givenname: Xiaofeng surname: Li fullname: Li, Xiaofeng email: Xiaofeng.Li@ieee.org organization: Center for Ocean Mega-Science, Chinese Academy of Sciences,Qingdao,Shandong,China,266071 – sequence: 3 givenname: Gang surname: Zheng fullname: Zheng, Gang organization: State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources,Hangzhou,Zhejiang,China,310012 |
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| Snippet | Researchers have already verified that the deep learning (DL) technology can realize accurate and robust mapping of tropical cyclone-induced coastal inundation... |
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| SubjectTerms | clustering Coastal inundation mapping deep convolutional autoen-coder (DCAE) Feature extraction Floods Radar imaging Radar polarimetry Sea measurements Sensors Synthetic aperture radar synthetic aperture radar (SAR) imagery |
| Title | Automatic Mapping of Tropical Cyclone-Induced Coastal Inundation in SAR Imagery Based on Clustering of Deep Features |
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