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International Geoscience and Remote Sensing Symposium

In 2021 a joint initiative of Belgium and The Netherlands

TU1.O-15.6

A DEEP FEATURE TRANSFORMATION METHOD BASED ON DIFFERENTIAL VECTOR FOR FEW-SHOT LEARNING

Qian Guo, Feng Xu, Fudan University, China
Session:
DEEP Insight SAR I
Track:
Invited Sessions
Presentation Time:
Tue, 13 Jul, 09:45-10:00 (UTC)
Tue, 13 Jul, 11:45-12:00 Central Europe Summer Time (UTC +2)
Tue, 13 Jul, 17:45-18:00 China Standard Time (UTC +8)
Tue, 13 Jul, 05:45-06:00 Eastern Daylight Time (UTC -4)
Session Co-Chairs:
Mihai Datcu, Research Center for Spatial Information (CEOSpaceTech), University POLITEHNICA of Bucharest (UPB) and Earth Observation Center (EOC), German Aerospace Center (DLR) and Zhongling Huang, Northwestern Polytechnical University
Session Manager:
Lynette Dias
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Session TU1.O-15
TU1.O-15.1: CAN WE EVALUATE THE DISTINGUISHABILITY OF THE OPENSARURBAN DATASET ?
Ning Liao, Shanghai Jiao Tong University, China; Mihai Datcu, German Aerospace Center (DLR), Germany; Zenghui Zhang, Shanghai Jiao Tong University, China; Weiwei Guo, Tongji University, China; Wenxian Yu, Shanghai Jiao Tong University, China
TU1.O-15.3: NONCOHERENT IMAGING EXPERIMENTS OF CIRCULAR SAR
Yuxiao Luo, Daoxiang An, Leping Chen, Jingwei Chen, Xiaotao Huang, National University of Defence Technology, China
TU1.O-15.4: SELF-CALIBRATED CONVOLUTIONAL NEURAL NETWORK FOR SAR IMAGE DESPECKLING
Ye Yuan, Yan Jiang, Yanxia Wu, Harbin Engineering University, China; Richard Jiang, Lancaster University, United Kingdom
TU1.O-15.5: PROPOSAL OF POLSAR LAND CLASSIFICATION USING QUATERNION CONVOLUTIONAL NEURAL NETWORKS
Yuya Matsumoto, Ryo Natsuaki, Akira Hirose, University of Tokyo, Japan
TU1.O-15.6: A DEEP FEATURE TRANSFORMATION METHOD BASED ON DIFFERENTIAL VECTOR FOR FEW-SHOT LEARNING
Qian Guo, Feng Xu, Fudan University, China

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