Automatic Mapping of Tropical Cyclone-Induced Coastal Inundation in SAR Imagery Based on Clustering of Deep Features - Liu, Bin; Li, Xiaofeng; Zheng, Gang (IEEE International Geoscience and Remote Sensing Symposium proceedings, 2020)
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.