WE3.M2.3
TRANSDUCTIVE TRANSFER-LEARNING FOR LAND USE LAND COVER CLASSIFICATION USING GEOSPATIAL FOUNDATION MODELS
Sina Klampt, Tatsuya Ishikawa, Daiki Kimura, IBM Research, Japan
Session:
WE3.M2: Foundation Models for Geospatial Artificial Intelligence I Oral
Track:
Community-Contributed Sessions
Location:
Room M2
Presentation Time:
Wednesday, 6 August, 13:45 - 14:00
Session Co-Chairs:
Adway Mitra, Indian Institute of Technology Kharagpur and Shailesh Deshpande, Tata Consultancy Services Research
Presentation
Discussion
Resources
No resources available.
Session WE3.M2
WE3.M2.1: A DEEP LEARNING FRAMEWORK USING REMOTE-SENSING FOUNDATION MODEL WITH SIAMESE U-NET AND KAN-BASED CNN FOR OPTICAL AND SAR CHANGE DETECTION
Shubhrangshu Ghosh, Syed Mujibul Islam, Abhishek Roy Choudhury, Arpan Pal, Tata Consultancy Services Ltd, India
WE3.M2.2: Seeing the Difference: Vision Transformer-Powered Multitemporal Generic Change Detection
Mikhail Klassen, Ramesh Nair, Ash Hoover, Brad Neuberg, Creon Levit, Planet Labs, United States
WE3.M2.3: TRANSDUCTIVE TRANSFER-LEARNING FOR LAND USE LAND COVER CLASSIFICATION USING GEOSPATIAL FOUNDATION MODELS
Sina Klampt, Tatsuya Ishikawa, Daiki Kimura, IBM Research, Japan
WE3.M2.4: Advancing Flood Mapping with Geo-Spatial Models and Indian Satellites
Kamal Das, Ayush Jain, Vinamra Baghel, Manikandan Padmanaban, Jagabondhu Hazra, Ranjini Guruprasad, Devyani Lambhate, Amith Singhee, Helen Tamura-Wicks, Geoffrey Dawson, Anne Jones, Paolo Fraccaro, Juan Bernabe Moreno, IBM Research, India
WE3.M2.5: ON THE GENERALIZABILITY OF FOUNDATION MODELS FOR CROP TYPE MAPPING
Yi-Chia Chang, University of Illinois Urbana-Champaign, United States; Adam Stewart, Technical University of Munich, Germany; Favyen Bastani, Piper Wolters, Allen Institute for AI, United States; Shreya Kannan, George Huber, Jingtong Wang, Arindam Banerjee, University of Illinois Urbana-Champaign, United States
Resources
No resources available.