WEP2.PI.1
UNSUPERVISED LEARNING-BASED INTERPRETING ARCHITECTURE FOR REMOTE SENSING IMAGERY
Haiyan Gu, Hengtong Shen, Haitao Li, Yi Yang, Honglin Li, Yang Wang, Zongyu Yang, Haozhu Kong, Chinese Academy of Surveying and Mapping, China
Session:
WEP2.PI: Foundation Models for Geospatial Artificial Intelligence II Poster
Track:
Community-Contributed Sessions
Location:
Poster Area
Presentation Time:
Wednesday, 6 August, 14:30 - 15:45
Session Co-Chairs:
Jagobondhu Hazra, IBM India Research Lab and Adway Mitra, Indian Institute of Technology Kharagpur
Presentation
Discussion
Resources
No resources available.
Session WEP2.PI
WEP2.PI.1: UNSUPERVISED LEARNING-BASED INTERPRETING ARCHITECTURE FOR REMOTE SENSING IMAGERY
Haiyan Gu, Hengtong Shen, Haitao Li, Yi Yang, Honglin Li, Yang Wang, Zongyu Yang, Haozhu Kong, Chinese Academy of Surveying and Mapping, China
WEP2.PI.2: NASA’S AI FOUNDATION MODELS FOR SCIENCE: CURRENT INITIATIVES, WORKFLOW, ROADMAP AND LESSONS LEARNED
Rahul Ramachandran, Tsengdar Lee, Kevin Murphy, NASA, United States
WEP2.PI.3: A Review of Challenges and Applications in remote sensing Foundation Models
Peijin Wang, Ziqi Zhang, Yingchao Feng, Wenxin Yin, Wenhui Diao, Xian Sun, Chinese Academy of Sciences, China
WEP2.PI.4: ENHANCING SATELLITE IMAGE ANALYSIS WITH FINE-TUNED VISION-LANGUAGE MODELS
Han Oh, Korea Aerospace Research Institute, Korea (South); Dongbin Shin, Hyunwoo Seo, University of Science and Technology, Korea (South); Sun Gu Lee, Daewon Chung, Korea Aerospace Research Institute, Korea (South)
WEP2.PI.5: Boosting Remote Sensing Vision-Language Models via Large-Scale Data Generation with Stable Diffusion Fine-tuning
Yujie Zan, Muying Luo, Shunping Ji, Wuhan University, China
WEP2.PI.6: Global Multimodal Approach to Biodiversity Assessment
Michal Muszynski, IBM Sustainability Software, Ireland; Levente Klein, IBM Research, United States; Harini Srinivasan, Gurkanwar Singh, Kewen Gu, Steve Meliksetian, Sonya Leech, IBM Sustainability Software, United States; Julian Kuehnert, Hendrik Hamann, Campbell Watson, IBM Research, Kenya
Resources
No resources available.