WEP1.PE.4
COMPARISON OF VISUAL FOUNDATION MODELS (VFMS) FOR FINE-GRAINED SEGMENTATION OF COCOS NUCIFERA TREES IN VERY HIGH RESOLUTION GEOSPATIAL DATASETS
Bhargav Parulekar, Anandakumar M. Ramiya, Indian Institute of Space Science and Technology, India
Session:
WEP1.PE: Earth Observation Foundation Models I Poster
Track:
Community-Contributed Sessions
Location:
Poster Area
Presentation Time:
Wednesday, 6 August, 09:15 - 10:30
Session Co-Chairs:
Xiao Xiang Zhu, Technical University Munich and Guido Grosse, Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research
Presentation
Discussion
Resources
No resources available.
Session WEP1.PE
WEP1.PE.2: ENHANCING LARGE LANGUAGE MODELS THROUGH INSTRUCTION TUNING FOR ANSWERING CLIMATE CHANGE QUESTIONS
Zhou Chen, Xiao Wang, Yuanhong Liao, Ming Lin, Mingrun Zang, Zimeng Wang, Yuqi Bai, Tsinghua University, China
WEP1.PE.3: Monitoring Illicit Rare Earth Mining in Myanmar via Self-Supervised Learning
Ollie Ballinger, University College London, United Kingdom
WEP1.PE.4: COMPARISON OF VISUAL FOUNDATION MODELS (VFMS) FOR FINE-GRAINED SEGMENTATION OF COCOS NUCIFERA TREES IN VERY HIGH RESOLUTION GEOSPATIAL DATASETS
Bhargav Parulekar, Anandakumar M. Ramiya, Indian Institute of Space Science and Technology, India
WEP1.PE.5: SHIP DETECTION IN OPTICAL SATELLITE IMAGERY USING VISION FOUNDATION MODEL
Hyunwoo Seo, University of Science and Technology, Korea (South); Han Oh, Korea Aerospace Research Institute, Korea (South); Dongbin Shin, University of Science and Technology, Korea (South); Chung Daewon, Korea Aerospace Research Institute, Korea (South)
WEP1.PE.6: FINE-TUNING THE SEGMENT ANYTHING MODEL FOR EARTH OBSERVATION
Rajat Sahay, Andreas Savakis, Rochester Institute of Technology, United States
WEP1.PE.7: MIMRS: A Survey on Mask Image Modeling in Remote Sensing
Shabnam Choudhury, Akhil Vasim, Indian Institute of Technology, India; Michael Schmitt, University of the Bundeswehr, Germany; Biplab Banerjee, Indian Institute of Technology, India
Resources
No resources available.