IEEE IGARSS 2021 || Brussels, Belgium || July 12–14, 2021 • Physical

TU2.MM-4: Semantic Segmentation in SAR/PolSAR Data

Tue, 13 Jul, 11:00 - 12:10 (UTC)
Tue, 13 Jul, 13:00 - 14:10 Central Europe Summer Time (UTC +2)
Tue, 13 Jul, 19:00 - 20:10 China Standard Time (UTC +8)
Tue, 13 Jul, 07:00 - 08:10 Eastern Daylight Time (UTC -4)

Session Co-Chairs: Alireza Taravat, Deimos Space UK and Florence Tupin, Telecom Paris

Session Manager: María Culman

Track: Data Analysis Methods (Optical, Multispectral,Hyperspectral, SAR)

TU2.MM-4.1: Forest canopy mapping using synthetic aperture radar by means of pulse coupled neural networks

Alireza Taravat, Deimos Space UK, United Kingdom; Iraj Emadodin, Kiel University, Germany

TU2.MM-4.2: AN IMPROVED DARK-SPOT SEGMENTATION BASED ON NON-CIRCULARITY ENHANCED SAR IMAGERY: A PRELIMINARY EXPLORATION

Haitao Lang, Chenguang Ge, Wenjing Li, Shuangmei Zhao, Chunnan Li, Lihui Niu, Guang’an Yang, Beijing University of Chemical Technology, China

TU2.MM-4.3: Bayesian U-Net for Segmenting Glaciers in SAR Imagery

Andreas Hartmann, Amirabbas Davari, Thorsten Seehaus, Matthias Braun, Andreas Maier, Vincent Christlein, Friendrich-Alexander Universität Erlangen-Nürnberg, Germany

TU2.MM-4.4: Glacier Calving Front Segmentation Using Attention U-Net

Michael Holzmann, Amirabbas Davari, Thorsten Seehaus, Matthias Braun, Andreas Maier, Vincent Christlein, Friendrich-Alexander Universität Erlangen-Nürnberg, Germany

TU2.MM-4.5: A SUPERPIXEL AGGREGATION METHOD BASED ON MULTI-DIRECTION GRAY LEVEL CO-OCCURRENCE MATRIX FOR SAR IMAGE SEGMENTATION

Meiling Cui, Yulin Huang, Rufei Wang, Jifang Pei, Weibo Huo, Yin Zhang, Haiguang Yang, University of Electronic Science and Technology of China, China

TU2.MM-4.6: DEEP LEARNING BASED OIL SPILL CLASSIFICATION USING UNET CONVOLUTIONAL NEURAL NETWORK

Abdul Basit, Muhammad Adnan Siddique, Information Technology University (ITU), Pakistan; Muhammad Saquib Sarfraz, Institute for Anthropomatics and Robotics, Karlsruhe Institute of Technology (KIT), Germany

TU2.MM-4.7: OIL SPILL DETECTION BASED ON CBD-NET USING MARINE SAR IMAGE

Yanan Zhang, Qiqi Zhu, Qingfeng Guan, China University of Geosciences, China

TU2.MM-4.8: DISTRIBUTION CHARACTERISTICS OF GREEN ALGAE IN YELLOW SEA USING AN DEEP LEARNING AUTOMATIC DETECTION PROCEDURE

Yuan Guo, Le Gao, Xiaofeng Li, Institute of Oceanography, Chinese Academy of Sciences, China

TU2.MM-4.9: CLASSIFYING SEA ICE TYPES FROM SAR IMAGES USING A U-NET-BASED DEEP LEARNING MODEL

Yan Huang, Yibin Ren, Xiaofeng Li, Institute of Oceanology, Chinese Academy of Sciences and Center for Ocean Mega-Science, Chinese Academy of Sciences, China

TU2.MM-4.10: Convolutional Autoencoder for unsupervised representation learning of PolSAR Time-Series

Thomas Di Martino, ONERA, CentraleSupélec, Université Paris-Saclay, France; Régis Guinvarc'h, Laétitia Thirion-Lefevre, CentraleSupélec, France; Elise Colin Koeniguer, ONERA, Université Paris-Saclay, France