TU3.R15.3
Low-Rank Adaptation of Geospatial Foundation Models for Wildfire Mapping Using Sentinel-2 Data
Ali Shibli, Andrea Nascetti, Yifang Ban, KTH Royal Institute of Technology, Sweden
Session:
TU3.R15: Foundation Models & Pretraining for Earth Observation Oral
Track:
AI and Big Data
Location:
TBD
Presentation Time:
Tue, 11 Aug, 14:15 - 14:30
Session Co-Chairs:
Ronny Hänsch, DLR and Dalton Lunga, ORNL
Presentation
Discussion
Resources
No resources available.
Session TU3.R15
TU3.R15.1: A Roadmap for Unified Multi-Modal Foundation Models in Earth Observation
Kumar Ankur, Nidhi Jha, Sujit Roy, The University of Alabama in Huntsville, United States; Rahul Ramachandran, National Aeronautics and Space Administration, United States
TU3.R15.2: CROSS-SCALE PRETRAINING: ENHANCING SELF-SUPERVISED LEARNING FOR LOW-RESOLUTION SATELLITE IMAGERY FOR SEMANTIC SEGMENTATION
John Waithaka, Gustave Bwirayesu, Moise Busogi, Carnegie Mellon University Africa, Rwanda
TU3.R15.3: Low-Rank Adaptation of Geospatial Foundation Models for Wildfire Mapping Using Sentinel-2 Data
Ali Shibli, Andrea Nascetti, Yifang Ban, KTH Royal Institute of Technology, Sweden
TU3.R15.4: Refocusing Pretrained Foundations for Remote Sensing Few-Shot Detection via Contrastive Recalibration
Buyi Chen, Linyi Qin, Northwestern Polytechnical University, China; Zhou Fei, The Chinese University of Hong Kong, China; Lei Zhang, Wei Wei, Northwestern Polytechnical University, China; Chen Ding, Xi'an University of Posts and Telecommunications, China; Yi Zhang, Liang Li, Mobile Research Institute, China; Xiangyu Yue, The Chinese University of Hong Kong, China
TU3.R15.5: FINE-TUNING NASA PRITHVI EO V2.0 FOUNDATION MODEL FOR DYNAMIC IRRIGATION MAPPING
Ehsan Jalilvand, Sujay Kumar, NASA goddard space flight center, United States; Hamed Alemohammad, Clark University, United States; Mohammad Fotouhi, John Deere co, United States; Sam Khallaghi, Clark University, United States
Contacts