TH4.R11.5

IMPROVING DEEP LEARNING-BASED HEIGHT ESTIMATION FROM SINGLE SAR IMAGES BY INJECTING SENSOR PARAMETERS

Michael Recla, Michael Schmitt, University of the Bundeswehr Munich, Germany
Session:
TH4.R11: Physics Informed Artificial Intelligence for Synthetic Aperture Radar Applications I Oral
Track:
Community-Contributed Sessions
Location:
Room 106
Presentation Time:
Thu, 20 Jul, 16:33 - 16:45 Pacific Time (UTC -7)
Session Chair:
Mihai Datcu, ROSA
Session Manager:
Rahisha Thottolil
Presentation
Discussion
Resources
No resources available.
Session TH4.R11
TH4.R11.1: A DEEP LEARNING COREGISTRATION APPROACH FOR DISTRIBUTED GEOSYNCHRONOUS SAR THREE-DIMENSIONAL DEFORMATION RETRIEVAL
Xingzhe Zhao, Yuanhao Li, Zhiyang Chen, Yuhui Xie, Cheng Hu, School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China, China
TH4.R11.2: INTERNAL WAVE SIGNATURE EXTRACTION FROM SAR IMAGERY BASED ON DEEP LEARNING
Shuangshang Zhang, Xiaofeng Li, Xudong Zhang, Institute of Oceanology, Chinese Academy of Sciences, China
TH4.R11.3: CROSS-DOMAIN SAR SHIP DETECTION IN STRONG INTERFERENCE ENVIRONMENT BASED ON IMAGE-TO-IMAGE TRANSLATION
Xinyang Pu, Hecheng Jia, Feng Xu, Fudan University, China
TH4.R11.4: RECENT PROGRESS IN SPARSITY-REGULARIZATION BASED IMAGING METHOD FOR NEAR-FIELD 3D SAR
Xu Zhan, Xiaoling Zhang, Xiangdong Ma, Shunjun Wei, Jun Shi, Tianjiao Zeng, University of Electronic Science and Technology of China, China
TH4.R11.5: IMPROVING DEEP LEARNING-BASED HEIGHT ESTIMATION FROM SINGLE SAR IMAGES BY INJECTING SENSOR PARAMETERS
Michael Recla, Michael Schmitt, University of the Bundeswehr Munich, Germany
Resources
No resources available.