WE1.R18.7

Dense Docked Ship Detection via Spatial Group-wise Enhance Attention in SAR Images

Xiaoya Wang, Zongyong Cui, Zongjie Cao, Sihang Dang, University of Electronic Science and Technology of China, China

Session:
Vessels Detection using Remote Sensing Data

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

Presentation Time:
Wed, 30 Sep, 13:00-13:10 (UTC)
Wed, 30 Sep, 21:00-21:10 China Standard Time (UTC +8)
Wed, 30 Sep, 15:00-15:10 Central Europe Summer Time (UTC +2)
Wed, 30 Sep, 06:00-06:10 Pacific Daylight Time (UTC -7)

Session Co-Chairs:
Björn Tings, German Aerospace Center (DLR) and Xiaoling Zhang, University of Electronic Science and Technology of China
Session Manager:
Muhammad Adnan Siddique

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Session

WE1.R18.1: SHIPDENET-18: AN ONLY 1 MB WITH ONLY 18 CONVOLUTION LAYERS LIGHT-WEIGHT DEEP LEARNING NETWORK FOR SAR SHIP DETECTION
Tianwen Zhang, Xiaoling Zhang, Jun Shi, Shunjun Wei, University of Electronic Science and Technology of China, China
WE1.R18.2: AN INTEGRATED METHOD OF SHIP DETECTION AND RECOGNITION IN SAR IMAGES BASED ON DEEP LEARNING
Zesheng Hou, Zongyong Cui, Zongjie Cao, Nengyuan Liu, University of Electronic Science and Technology of China, China
WE1.R18.3: SHIP DETECTION IN RADAR IMAGE SERIES BASED ON THE LONG SHORT-TERM MEMORY NETWORK
Yi Xu, Bing Sun, Chunsheng Li, Jie Chen, Beihang University, China
WE1.R18.4: Ship Wake Component Detectability on Synthetic Aperture Radar (SAR)
Björn Tings, Stefan Wiehle, Sven Jacobsen, German Aerospace Center, Germany
WE1.R18.5: FAST SINGLE-SHOT SHIP INSTANCE SEGMENTATION BASED ON POLAR TEMPLATE MASK IN REMOTE SENSING IMAGES
Zhenhang Huang, Shihao Sun, Ruirui Li, Beijing University of Chemical Technology, China
WE1.R18.6: Recognition Of Ship By ISAR With Improved Partial-modal Generative Adversarial Networks
Gaopeng Li, Jie Wang, Yun Zhang, Harbin Institute of Technology, China
WE1.R18.7: Dense Docked Ship Detection via Spatial Group-wise Enhance Attention in SAR Images
Xiaoya Wang, Zongyong Cui, Zongjie Cao, Sihang Dang, University of Electronic Science and Technology of China, China
WE1.R18.8: SHIP TARGET SIGNATURE INDICATION BASED ON COMPLEX SIGNAL KURTOSIS IN SAR IMAGES
Xiangguang Leng, Kefeng Ji, Boli Xiong, Gangyao Kuang, National University of Defense Technology, China
WE1.R18.9: A SVA BASED SIDELOBE SUPPRESSION METHOD FOR SEA-LAND SEGMENTATION AND SHIP DETECTION IN SAR IMAGES
Yinli Huang, Xidian University, China; Lu Sun, 93128 Troops of the Chinese peoples's liberation army, China; Liang Guo, Guangcai Sun, Mengdao Xing, Xidian University, China; Jun Yang, Xi’an University of Science and Technology, China; Yihua Hu, National University of Defense Technology, China
WE1.R18.10: SHIP DETECTION FROM POLSAR IMAGERY BASED ON THE SCATTERING DIFFERENCE PARAMETER
Tao Zhang, Tsinghua University, China; Zhen Yang, Jiangxi Science and Technology Normal University, China; Cheng Xing, Liang Zeng, Tsinghua University, China; Junjun Yin, University of Science and Technology Beijing, China; Jian Yang, Tsinghua University, China
WE1.R18.11: A New Automatic Ship Wake Detection for Sentinel-1 Imagery
Elena Grosso, Raffaella Guida, Surrey Space Centre, United Kingdom
WE1.R18.12: Ship Detection in Large Scale SAR Images Based on Bias Classification
Xiaoya Wang, Zongyong Cui, Zongjie Cao, Yu Tian, University of Electronic Science and Technology of China, China