TH1.P9.3
DETECTION OF ROBOT DOG BASED ON MICRO-DOPPLER SIGNATURES USING CONTRASTIVE SUPERVISED LEARNING
MINSEO SEONG, INSOO CHOI, YOUNGWOOK KIM, SOGANG UNIVERSITY, Korea (South)
Session:
TH1.P9: Radar Target Detection and Recognition Oral
Track:
Data Analysis
Location:
Plaza: Room P9
Presentation Time:
Thursday, 7 August, 08:30 - 08:45
Session Chair:
Gordon Staples, MDA
Presentation
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Discussion
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Session TH1.P9
TH1.P9.1: DEEP LEARNING-BASED COMPLEX-VALUED BINARY TRANSFORM FOR MILLIMETER-WAVE FMCW RADAR RANGE-DOMAIN TARGET DETECTION
Xibo Chen, Kai Xiong, Hongrui Zhang, Xiguang Wu, Bo Li, Bing Chen, Yan Liu, Genquan Han, Xidian University, China
TH1.P9.2: KOLMOGOROV–ARNOLD NETWORKS FOR HIGH-RESOLUTION RANGE PROFILE RECOGNITION IN RADAR APPLICATIONS
Kejun Ye, University of Sheffield, China; Yanhua Wang, Beijing Institute of Technology, China; Rola Saad, University of Sheffield, United Kingdom
TH1.P9.3: DETECTION OF ROBOT DOG BASED ON MICRO-DOPPLER SIGNATURES USING CONTRASTIVE SUPERVISED LEARNING
MINSEO SEONG, INSOO CHOI, YOUNGWOOK KIM, SOGANG UNIVERSITY, Korea (South)
TH1.P9.4: MULTI-PERSON TRACKING WITH IDENTIFICATION USING MMWAVE RADAR BASED ON MICRO-DOPPLER
Meiqiu Jiang, Shisheng Guo, University of Electronic Science and Technology of China, China
TH1.P9.5: FDA-MIMO RADAR INTERFERENCE IDENTIFY USING MULTI-CHANNEL COSINE SIMILARITY AND RANDOM FOREST
Zhonghao Wang, Yizhen Jia, WEN-QIN WANG, University of Electronic Science and Technology of China (UESTC), China
Resources
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