TH1.R3.4
ACCURACY AND LOCAL EDITABILITY OF DENSE CONCEPT BOTTLENECK MODELS FOR SENTINEL-1/2 LAND COVER MAPPING
Taewoong Ham, Baoxin Hu, York University, Canada
Session:
TH1.R3: Explainable Artificial Intelligence for Big Data and Scientific Discovery Oral
Track:
Community Contributed Themes
Location:
TBD
Presentation Time:
Thu, 13 Aug, 09:00 - 09:15
Session Chair:
Phung Lai,
Presentation
Discussion
Resources
No resources available.
Session TH1.R3
TH1.R3.1: RESEARCH ON A GENERAL ARTIFICIAL INTELLIGENCE TECHNOLOGY FRAMEWORK AND COLLABORATIVE APPLICATION FOR THE MARINE FIELD
xiaoyi jiang, shengwen cao, National Marine Data and Information Service, China
TH1.R3.2: INTEGRATING SPATIAL-SEMANTIC REASONING VIA GEOGRAPHIC KNOWLEDGE GRAPH: ADVANCING FROM DIGITAL TO INTELLIGENT OCEAN GOVERNANCE
Hanrui Sun, Xiaoyi Jiang, Jin Wang, Xue Guo, Long He, Linchong Kang, National Marine Data and Information Service, China
TH1.R3.4: ACCURACY AND LOCAL EDITABILITY OF DENSE CONCEPT BOTTLENECK MODELS FOR SENTINEL-1/2 LAND COVER MAPPING
Taewoong Ham, Baoxin Hu, York University, Canada
TH1.R3.5: EXPLAINABLE AI (XAI) FOR ISLAND WAKE SEGMENTATION OF SYNTHETIC APERTURE RADAR IMAGERY
Madeleine Dawson, Hans Graber, University of Miami, United States
Contacts