MOP2.PB.2
DEMONSTRATION OF A DEEP LEARNING MODEL FOR DOMAIN-SCALE PRECIPITATION RETRIEVAL USING GOES/ABI OBSERVATIONS
Yousef Saqer Yousef Saqer, Colorado State University, United States
Session:
MOP2.PB: Advanced AI Methods for Geophysical Analysis Poster
Track:
AI and Big Data
Location:
TBD
Presentation Time:
Mon, 10 Aug, 15:00 - 16:15
Session Co-Chairs:
Ronny Hänsch, DLR and Dalton Lunga, ORNL
Presentation
Discussion
Resources
No resources available.
Session MOP2.PB
MOP2.PB.1: 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.2: DEMONSTRATION OF A DEEP LEARNING MODEL FOR DOMAIN-SCALE PRECIPITATION RETRIEVAL USING GOES/ABI OBSERVATIONS
Yousef Saqer Yousef Saqer, Colorado State University, United States
MOP2.PB.3: EARTH EMBEDDINGS AS PRODUCTS: TAXONOMY, ECOSYSTEM, AND STANDARDIZED ACCESS
Heng Fang, KTH Royal Institute of Technology, Sweden; Adam J. Stewart, Technical University of Munich, Germany; Isaac Corley, Wherobots, United States; Xiao Xiang Zhu, Technical University of Munich, Germany; Hossein Azizpour, KTH Royal Institute of Technology, Sweden
MOP2.PB.4: GEOMETRIC FLOOD DEPTH ESTIMATION: FUSING TRANSFORMER-BASED SEGMENTATION WITH DIGITAL ELEVATION MODELS
Nhut Le, Ehsan Karimi, Maryam Rahnemoonfar, Lehigh University, United States
MOP2.PB.5: 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
Contacts