MO4.R15.1
Research on SAR Image Generation Method Basedon Deep Learning: Models, Challenges, andProspects
Shuo Yu, Dan Gao, Xiaofang Wu, Chunheng Liu, Academy of Military, China
Session:
MO4.R15: Methods for SAR & High-Resolution Image Understanding Oral
Track:
AI and Big Data
Location:
TBD
Presentation Time:
Mon, 10 Aug, 16:15 - 16:30
Session Co-Chairs:
Hongruixuan Chen, RIKEN Center for Advanced Intelligence Project (AIP) and Gülsen Taskin,
Presentation
Discussion
Resources
No resources available.
Session MO4.R15
MO4.R15.1: Research on SAR Image Generation Method Basedon Deep Learning: Models, Challenges, andProspects
Shuo Yu, Dan Gao, Xiaofang Wu, Chunheng Liu, Academy of Military, China
MO4.R15.2: JOINT PIXEL-LEVEL AND LATENT-LEVEL MASKED IMAGE MODELING FRAMEWORK FOR POLSAR IMAGE CLASSIFICATION
Lifan Wang, Zuzheng Kuang, Xi'an Jiaotong University, China; Shuxin Liu, Southwestern Institute of Physics, China; Lijun He, Haixia Bi, Fan Li, Xi'an Jiaotong University, China
MO4.R15.3: Geometric Consistency Protocol for Foundation Model Features in Multi-View Satellite Imagery
Qiyan Luo, Jie Yang, Yingdong Pi, Zhongli Fan, Lekang Wen, Mi Wang, Wuhan University, China
MO4.R15.4: EFFICIENT ICEBERG DETECTION IN SENTINEL-1 IMAGERY USING THE THOR FOUNDATION MODEL
Theodor Forgaard, Jarle H. Reksten, Norwegian Computing Center, Norway; David Arthurs, PolarView ApS, Canada; Arnt B. Salberg, Norwegian Computing Center, Norway
Contacts