MOP2.PB.6
A SAR-ORIENTED ORDINAL LEARNING FRAMEWORK FOR SEA STATE CLASSIFICATION
Tianwen Zhang, Rui Zhu, Rong Deng, Gui Gao, Southwest Jiaotong University, China; Xiao Ke, University of Liverpool, United Kingdom; Xiaoling Zhang, University of Electronic Science and Technology of China, China
Session:
MOP2.PB: Advanced AI Methods for Geophysical Analysis Poster
Track:
AI and Big Data
Location:
Columbia, Poster Area B
Presentation Time:
Monday, 10 August, 15:00 - 16:15
Session Co-Chairs:
Ronny Hänsch, DLR and Dalton Lunga, ORNL
Presentation
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Session MOP2.PB
MOP2.PB.6: A SAR-ORIENTED ORDINAL LEARNING FRAMEWORK FOR SEA STATE CLASSIFICATION
Tianwen Zhang, Rui Zhu, Rong Deng, Gui Gao, Southwest Jiaotong University, China; Xiao Ke, University of Liverpool, United Kingdom; Xiaoling Zhang, University of Electronic Science and Technology of China, China
MOP2.PB.7: DEMONSTRATION OF A DEEP LEARNING MODEL FOR DOMAIN-SCALE PRECIPITATION RETRIEVAL USING GOES/ABI OBSERVATIONS
Yousef Saqer, Haonen Chen, Yifan Yang, Colorado State University, United States
MOP2.PB.8: GEOMETRIC FLOOD DEPTH ESTIMATION: FUSING TRANSFORMER-BASED SEGMENTATION WITH DIGITAL ELEVATION MODELS
Nhut Le, Ehsan Karimi, Maryam Rahnemoonfar, Lehigh University, United States
MOP2.PB.9: Towards Intelligent Crop Monitoring: Visions for Agro-Geoinformation Foundation Models
Chen Zhang, Liping Di, Eugene Yu, George Mason University, United States; Zhengwei Yang, USDA NASS, United States
Resources
No resources available.