TU2.M4.3
HYBRID FOREST HEIGHT ESTIMATION FOR NON-ZERO-BASELINE REPEAT-PASS POLINSAR
Qi Zhang, Yuanyuan Wang, Xiao Xiang Zhu, Technical University of Munich, Germany
Session:
TU2.M4: Deep Learning for Multi-channel SAR processing: Current State of Art and Future Trends in the Application of Deep Learning for 3D Reconstruction II Oral
Track:
Community-Contributed Sessions
Location:
Room M4
Presentation Time:
Tuesday, 5 August, 11:00 - 11:15
Session Co-Chairs:
Giampaolo Ferraioli, Università degli Studi di Napoli Parthenope, Napoli, Italy. and Sergio Vitale, University of Naples Parthenope
Presentation
Discussion
Resources
No resources available.
Session TU2.M4
TU2.M4.1: TomoSAR from Theory to Practice – Overview of the Advancements and Challenges
Hossein Aghababaei, University of Twente, Netherlands; Giampaolo Ferraioli, Università degli Studi di Napoli Parthenope, Napoli, Italy., Italy
TU2.M4.2: Exploring Spatial Feature Regularization in Deep-Learning-Based TomoSAR Reconstruction: A Preliminary Study and Performance Analysis
Tianjiao Zeng, Xu Zhan, University of Electronic Science and Technology of China, China; Yu Ren, Xiangdong Ma, Liang Liu, University of Electronic Sicence and Technology of China, China; Jun Shi, Shunjun Wei, Mou Wang, Xiaoling Zhang, University of Electronic Science and Technology of China, China
TU2.M4.3: HYBRID FOREST HEIGHT ESTIMATION FOR NON-ZERO-BASELINE REPEAT-PASS POLINSAR
Qi Zhang, Yuanyuan Wang, Xiao Xiang Zhu, Technical University of Munich, Germany
TU2.M4.4: COMPARISON OF ML AND DL BASED METHODS FOR FOREST HEIGHT ESTIMATION THROUGH MULTI-CHANNEL SAR DATA
Francesca Razzano, Wenyu Yang, Sergio Vitale, Giampaolo Ferraioli, Vito Pascazio, University of Naples Parthenope, Italy; Silvia Liberata Ullo, University of Sannio, Italy; Gilda Schirinzi, University of Naples Parthenope, Italy
TU2.M4.5: Equivariance-Embedded TomoSAR Robust Imaging
Jinyu Qiu, Tianjiao Zeng, Mou Wang, Jun Shi, Shunjun Wei, Xiaoling Zhang, Xu Zhan, University of Electronic Science and Technology of China, China
Resources
No resources available.