TH4.R1.2

LABEL AUGMENTATION NETWORK BASED ON SELF-DISTILLATION FOR SAR SHIP DETECTION IN COMPLEX BACKGROUND

Chuan Qin, Xueqian Wang, Gang Li, Tsinghua University, China
Session:
TH4.R1: Novel Object Detection Methods for SAR Oral
Track:
Data Analysis
Location:
Room B
Presentation Time:
Thu, 20 Jul, 15:57 - 16:09 Pacific Time (UTC -7)
Session Co-Chairs:
Horst Hammer, Fraunhofer IOSB and Xueqian Wang, Tsinghua University
Session Manager:
sunni kanta prasad kushwaha
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Session TH4.R1
TH4.R1.1: A Novel Moving Target Detection Method for Hybrid Quad-Pol SAR
Yuwei Ren, Aerospace Information Research Institute, Chinese Academy of Sciences 2. University of Chinese Academy of Sciences, China; Mingjie Zheng, Aerospace Information Research Institute, Chinese Academy of Sciences, China; Peng Li, Beijing Autoroad Tech Co., Ltd, China; Zhongzheng Yin, 1.Aerospace Information Research Institute, Chinese Academy of Sciences. 2. University of Chinese Academy of Sciences, China
TH4.R1.2: LABEL AUGMENTATION NETWORK BASED ON SELF-DISTILLATION FOR SAR SHIP DETECTION IN COMPLEX BACKGROUND
Chuan Qin, Xueqian Wang, Gang Li, Tsinghua University, China
TH4.R1.3: REQUIREMENTS FOR 3D MODELS TO BE USED IN SAR IMAGE SIMULATION
Horst Hammer, Silvia Kuny, Antje Thiele, Fraunhofer IOSB, Germany
TH4.R1.4: IMPROVING THE ROAD TOPOLOGICAL RELATION BASED ON A ROAD INTERSECTION DETECTION METHOD
Jun He, Jinpeng Li, Weijia Li, Sun Yat-sen University, China
Resources
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