WE4.M3.3
DenSe-AdViT: A novel Vision Transformer for Dense SAR Object Detection
Yang Zhang, Jingyi Cao, Yanan You, Yuanyuan Qiao, Beijing University of Posts and Telecommunications, China
Session:
WE4.M3: Innovative Approaches in Radar and SAR Imaging for Object Detection and Image Enhancement I Oral
Track:
AI and Big Data
Location:
Mezzanine: Room M3
Presentation Time:
Wednesday, 6 August, 16:15 - 16:30
Session Chair:
Francescopaolo Sica, University of the Bundeswehr Munich
Session WE4.M3
WE4.M3.1: GEOSC-SAR FRAMEWORK FOR ENHANCED DYNAMIC SEA SURFACE WAVE IMAGING USING MBO2D-SC ALGORITHM
Yuhang Li, Mei Liu, Yuguan Hou, Harbin Institute of Technology, China
WE4.M3.2: AAFCFPNet: An adaptive attention multi-scale features cross fusion pyramid network to improve SAR ship detection
Ping Lang, Tsinghua University, China; Xiongjun Fu, Beijing Institute of Technology, China; Huizhang Yang, Nanjing University of Science and Technology, China; Junjun Yin, University of Science and Technology Beijing, China; Jian Yang, Tsinghua University, China
WE4.M3.3: DenSe-AdViT: A novel Vision Transformer for Dense SAR Object Detection
Yang Zhang, Jingyi Cao, Yanan You, Yuanyuan Qiao, Beijing University of Posts and Telecommunications, China
WE4.M3.4: SPACEBORNE SAR OPERATING MODE RECOGNITION USING DOPPLER HISTORY VARIATION INFORMATION
Jiayue Cao, Fei Teng, Guangzuo Li, Bing Han, Zhongqiu Xu, Wen Hong, Aerospace Information Research Institute, Chinese Academy of Sciences, China
WE4.M3.5: SARLOFTR：A SAR IMAGE MATCHING METHOD BASED ON ATTENTION MECHANISM
Yueting Zhang, Guangyao Zhou, Xia Ning, Wenjie Li, Yunbo Song, Yansong Wang, Yang Yang, Aerospace Information Research Institute, Chinese Academy of Sciences, China
Resources