WE2.S1.4
Multi-Domain Spatio-Temporal Feature Representation with Graph Neural Networks for Radar Target Detection
Junjie Wang, Dongying Li, Wenxian Yu, Shanghai Jiao Tong university, China
Session:
WE2.S1: Classification and Clustering of Radar and LiDAR Data Oral
Track:
Data Analysis
Location:
Sky: Room S1
Presentation Time:
Wednesday, 6 August, 11:15 - 11:30
Session Co-Chairs:
Gabriele Moser, University of Genoa and Zhulin Zong, University of Electronic Science and Technology of China
Session WE2.S1
WE2.S1.1: GROUND HRRP TARGET RECOGNITION UNDER LOW SNR BASED ON MSFF-CNN MODEL
Xiaohui Wei, Zhulin Zong, University of Electronic Science and Technology of China, China
WE2.S1.2: SPHERICAL FEATURES FOR SAR SHIP CLASSIFICATION WITH ADVERSARIAL DOMAIN ADAPTATION
Zhichao Han, Haitao Lang, Wangkai Luo, Beijing University of Chemical Technology, China
WE2.S1.3: A RADAR SIGNAL SORTING METHOD TO REDUCE BATCH EXPANSION
Haoyang Yu, Weibo Huo, Yujie Zhang, Yulin Huang, Jifang Pei, Yin Zhang, University of Electronic Science and Technology of China, China
WE2.S1.4: Multi-Domain Spatio-Temporal Feature Representation with Graph Neural Networks for Radar Target Detection
Junjie Wang, Dongying Li, Wenxian Yu, Shanghai Jiao Tong university, China
WE2.S1.5: CROSS-MODAL ENHANCED INTERACTIVE TRANSFORMER FOR HSI AND LIDAR JOINT CLASSIFICATION
Pengbo Mi, Yi Yang, Deqaing Han, Xi’an Jiaotong University, China
Resources