TUP.P3.1

META LEARNING-BASED APPROACH FOR FEW-SHOT TARGET RECOGNITION IN ISAR IMAGES

Jing Jin, Feng Wang, Fudan University, China
Session:
TUP.P3: Target Recognition in Remote Sensing Image I Poster
Track:
Data Analysis
Location:
Poster Area 3
Presentation Time:
Tue, 18 Jul, 14:15 - 15:45 Pacific Time (UTC -8)
Session Chair:
Hichem Sahbi, CNRS Sorbonne University
Session Managers:
Ge Jiang and Lanying Wang and Ayoti Banerjee and Shubham Awasthi
Presentation
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Discussion
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Resources
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Session TUP.P3
TUP.P3.1: META LEARNING-BASED APPROACH FOR FEW-SHOT TARGET RECOGNITION IN ISAR IMAGES
Jing Jin, Feng Wang, Fudan University, China
TUP.P3.2: A DECISION FUSION FRAMEWORK FOR ISAR IMAGES RECOGNITION BASED ON SCATTERING CENTER AND ZERNIKE MOMENT
Pengling Tang, Bo Long, Feng Wang, Fudan University, China
TUP.P3.3: HYBRID DIFFERENTIAL MORPHOLOGICAL PROFILE ENABLED FASTER R-CNN FOR OBJECT DETECTION IN HIGH-RESOLUTION REMOTE SENSING IMAGERY
J. Alex Hurt, Curt H. Davis, Grant J. Scott, University of Missouri, United States
TUP.P3.4: AERIAL IMAGE OBJECT DETECTION WITH VISION TRANSFORMER DETECTOR (VITDET)
Liya Wang, Alex Tien, The Mitre Cooperation, United States
TUP.P3.5: AN EXTREMELY LIGHTWEIGHT U-NET WITH SOFT FUSION FOR FLOOD DETECTION USING MULTI-SOURCE SATELLITE IMAGES
Zhihao Wang, Xueqian Wang, Gang Li, Department of Electronic Engineering, Tsinghua University, China
TUP.P3.6: DENSE CONTRASTIVE LEARNING BASED OBJECT DETECTION FOR REMOTE SENSING IMAGES
Shuo Liu, Huanxin Zou, Meilin Li, Xu Cao, Shitian He, Juan Wei, Li Sun, Yuqing Zhang, National University of Defense Technology, China
TUP.P3.7: HIDDEN OBJECT DETECTION BASED ON PROBABILISTIC FUZZY FUSION AND FISHER VECTORS IN PASSIVE MILLIMETER-WAVE IMAGES
Bo Fang, School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, China, China; Dong Zhu, School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, China/ National key Laboratory of Science and Technology on Multi-Spectral Information Processing , Wuhan 430074, China, China; Yayun Cheng, School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China, China; Fei Hu, School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, China/ National key Laboratory of Science and Technology on Multi-Spectral Information Processing , Wuhan 430074, China, China
TUP.P3.8: OPTICAL FLOW-BASED MOVING VEHICLE DETECTION FROM SINGLE-PASS WORLDVIEW-3 IMAGERY
Yongjun Song, Yongil Kim, Seoul National University, South Korea
TUP.P3.9: DEEP-NET INVERSION FOR FRUGAL SATELLITE IMAGE CHANGE DETECTION
Hichem Sahbi, CNRS Sorbonne University, France; Sebastien Deschamps, Sorbonne University, France
TUP.P3.10: DETECTION OF HEAVY-POLLUTING ENTERPRISES FROM OPTICAL SATELLITE REMOTE SENSING IMAGES
Zhibao Wang, Xi Zhao, Northeast Petroleum University, China; Lu Bai, Ulster University, United Kingdom; Mei Wang, Northeast Petroleum University, China; Man Zhao, Qiqihaer University, China; Meng Fan, Jinhua Tao, Liangfu Chen, Chinese Academy of Sciences, China
TUP.P3.11: MAPPING INSTALLED SOLAR PANELS USING WEAKLY SUPERVISED APPROACH WITH CROSS-SCALE ATTENTION ACCUMULATION AND HIERARCHICAL SUBSPACE LEARNING
Jue Zhang, UNSW canberra, Australia; Xiaohan Yu, Jun Zhou, Griffith University, Australia; Jiankun Hu, Xiuping Jia, University of New South Wales,Canberra, Australia
TUP.P3.12: 3D-MGLNET: MOVING VEHICLE DETECTION IN SATELLITE VIDEOS WITH 3D MOTION-GUIDED LIGHTWEIGHT NETWORK
Xiaoyu Zhu, Xidian University, China; Jie Li, Space Platform Business Division, China; Jie Feng, Quanpeng Jiang, Xiangrong Zhang, Licheng Jiao, Xidian University, China
Resources
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