FR2.R9.4

HIGHLY CONTAMINATED WORK MODE IDENTIFICATION OF PHASED ARRAY RADAR USING DEEP LEARNING METHOD

Xiaolong Hui, Bin Wu, Peng Li, Chao Hou, Zhao Wang, Key Laboratory of Electronic Information Countermeasure and Simulation Technology Ministry of Education, School of Electronic Engineering, Xidian University, China

Session:
Classification Methods

Track:
Data Analysis Methods (Optical, Multispectral,Hyperspectral, SAR)

Presentation Time:
Fri, 2 Oct, 15:00-15:10 (UTC)
Fri, 2 Oct, 23:00-23:10 China Standard Time (UTC +8)
Fri, 2 Oct, 17:00-17:10 Central Europe Summer Time (UTC +2)
Fri, 2 Oct, 08:00-08:10 Pacific Daylight Time (UTC -7)

Session Co-Chairs:
Shoichiro Kojima, National Institute of Information and Communications Technology and Jonathan Li, University of Waterloo
Session Managers:
Elena Ionescu and Vasala Saicharan

Presentation

Discussion

Resources

Session

FR2.R9.1: POTENTIAL OF LAND COVER CLASSIFICATION BASED ON GF-1 AND GF-3 DATA
Ruikun Yu, Shandong Jianzhu University, China; Guanghui Wang, Ministry of Natural Resource, China; Tongguang Shi, Shandong Jianzhu University, China; Wei Zhang, Chen Lu, Tao Zhang, Ministry of Natural Resource, China
FR2.R9.2: Classification of Winter Land Cover in New Zealand Hill Country for Risky Practice Identification
Alexander Amies, Stella Belliss, Heather North, David Pairman, John Dymond, Jan Schindler, James Shepherd, John Drewry, Manaaki Whenua – Landcare Research, New Zealand
FR2.R9.3: SEMI-SUPERVISED LAND COVER CLASSIFICATION USING PI-SAR2 OBSERVATION DATA
Yuya Arima, Shoichiro Kojima, Jyunpei Uemoto, Tomohiko Konno, National Institute of Information and Communications Technology, Japan
FR2.R9.4: HIGHLY CONTAMINATED WORK MODE IDENTIFICATION OF PHASED ARRAY RADAR USING DEEP LEARNING METHOD
Xiaolong Hui, Bin Wu, Peng Li, Chao Hou, Zhao Wang, Key Laboratory of Electronic Information Countermeasure and Simulation Technology Ministry of Education, School of Electronic Engineering, Xidian University, China
FR2.R9.5: Kernel Rotational Network For Synthetic Aperture Radar Target Recognition
Yuanyuan Zhou, Yao Hu, Chen Wang, Mou Wang, Jun Shi, Shunjun Wei, University of Electronic Science and Technology of China, China
FR2.R9.6: EXTRACTION OF POWER LINES AND PYLONS FROM LIDAR POINT CLOUDS USING A GCN-BASED METHOD
Wen Li, Xiamen University, China; Ziyue Zhang, University of Nottingham Ningbo China, China; Zhipeng Luo, Zhenlong Xiao, Cheng Wang, Xiamen University, China; Jonathan Li, University of Waterloo, Canada
FR2.R9.7: A BOUNDARY-ENHANCED SUPERVOXEL METHOD FOR 3D POINT CLOUDS
Zhengchuan Sha, Qing Zhu, Yiping Chen, Cheng Wang, Xiamen University, China; Abdul Nurunnabi, University of Luxembourg, Luxembourg; Jonathan Li, Xiamen University, Luxembourg
FR2.R9.8: MAPPING THE LAND DEVELOPMENT PROCESSES USING DATA TRANSFORMATION AND CLUSTERING METHODS
Pariya Pourmohammadi, Donald Adjeroh, Michael Strager, West Virginia University, United States
FR2.R9.9: Kernel Local Sample Directional Discriminant Embedding for SAR Automatic Target Recognition
Xian Liu, Jifang Pei, Yulin Huang, Jianyu Yang, University of Electronic Science and Technology of China, China
FR2.R9.10: RADAR SIGNAL INTRA-PULSE MODULATION RECOGNITION BASED ON CONTOUR EXTRACTION
Zhengyang Yu, Jianlong Tang, Xidian University, China
FR2.R9.11: TREE SPECIES CLASSIFICATION BASED ON AIRBORNE LIDAR AND HYPERSPECTRAL DATA
Xukun Lu, Gang Liu, China Academy of Electronics and Information Technology, China; Silan Ning, Zhonghua Su, Ze He, University of Electronic Science and Technology of China, China