WE1.R18: Vessels Detection using Remote Sensing Data

Wed, 30 Sep, 12:00 - 14:00 (UTC)
Wed, 30 Sep, 20:00 - 22:00 China Standard Time (UTC +8)
Wed, 30 Sep, 14:00 - 16:00 Central Europe Summer Time (UTC +2)
Wed, 30 Sep, 05:00 - 07:00 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
Track: Data Analysis Methods (Optical, Multispectral,Hyperspectral, SAR)
12:00-12:10 (UTC)
20:00-20:10 (UTC +8)
14:00-14:10 (UTC +2)
05:00-05:10 (UTC -7)

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
12:10-12:20 (UTC)
20:10-20:20 (UTC +8)
14:10-14:20 (UTC +2)
05:10-05:20 (UTC -7)

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
12:20-12:30 (UTC)
20:20-20:30 (UTC +8)
14:20-14:30 (UTC +2)
05:20-05:30 (UTC -7)

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
12:30-12:40 (UTC)
20:30-20:40 (UTC +8)
14:30-14:40 (UTC +2)
05:30-05:40 (UTC -7)

WE1.R18.4: Ship Wake Component Detectability on Synthetic Aperture Radar (SAR)

Björn Tings, Stefan Wiehle, Sven Jacobsen, German Aerospace Center, Germany
12:40-12:50 (UTC)
20:40-20:50 (UTC +8)
14:40-14:50 (UTC +2)
05:40-05:50 (UTC -7)

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
12:50-13:00 (UTC)
20:50-21:00 (UTC +8)
14:50-15:00 (UTC +2)
05:50-06:00 (UTC -7)

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
13:00-13:10 (UTC)
21:00-21:10 (UTC +8)
15:00-15:10 (UTC +2)
06:00-06:10 (UTC -7)

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
13:10-13:20 (UTC)
21:10-21:20 (UTC +8)
15:10-15:20 (UTC +2)
06:10-06:20 (UTC -7)

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
13:20-13:30 (UTC)
21:20-21:30 (UTC +8)
15:20-15:30 (UTC +2)
06:20-06:30 (UTC -7)

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
13:30-13:40 (UTC)
21:30-21:40 (UTC +8)
15:30-15:40 (UTC +2)
06:30-06:40 (UTC -7)

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
13:40-13:50 (UTC)
21:40-21:50 (UTC +8)
15:40-15:50 (UTC +2)
06:40-06:50 (UTC -7)

WE1.R18.11: A New Automatic Ship Wake Detection for Sentinel-1 Imagery

Elena Grosso, Raffaella Guida, Surrey Space Centre, United Kingdom
13:50-14:00 (UTC)
21:50-22:00 (UTC +8)
15:50-16:00 (UTC +2)
06:50-07:00 (UTC -7)

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