WE1.R16.5
SAR-URBAN: GEOMETRY-CONDITIONED REPRESENTATION LEARNING FOR URBAN SEGMENTATION IN SAR
Tsenjung Tai, Masato Toda, Nagma Khan, Kenta Senzaki, NEC Corporation, Japan
Session:
WE1.R16: Urban: GeoAI and Deep Learning for Urban Infrastructure II Oral
Track:
Land Applications
Location:
Lincoln East
Presentation Time:
Wednesday, 12 August, 09:30 - 09:45
Session Chair:
Yuliya Tarabalka, Space42
Presentation
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Session WE1.R16
WE1.R16.1: Improving Road Graph Connectivity in Arid Regions via Geometry-Driven Reconstruction and Topology-Aware Supervision
Chengyuan Li, Abdalla Alloghani, Moez Ajili, Nikolay Kvasov, Yuliya tarabalka, Prashanth Marpu, SPACE42, United Arab Emirates
WE1.R16.2: EVALUATING THE COVERAGE AND QUALITY OF OPEN SOURCE BUILDING FOOTPRINT DATASETS
Trevor Stout, Dennis Melamed, Cameron Johnson, Kitware, United States
WE1.R16.3: USING GEOSPATIAL AI FOR LARGE-SCALE AUTOMATED BOMA MAPPING WITH PLANET EARTH IMAGERY
Keli Cheng, James Hurt, Grant Scott, University of Missouri, United States; William Oswald, RTI International, United States; Deogratias Mzurikwao, Muhimbili University of Health and Allied Sciences, Tanzania; George Kabona, Njombe Referral Hospital, Tanzania; Mabula Kasubi, Muhimbili National Hospital, Tanzania; Ambakisye Mhiche, RTI Tanzania, Tanzania; Weipeng Wu, Northwest Missouri State University, United States
WE1.R16.4: EVALUATING THE EFFECTIVENESS OF XAI TECHNIQUES IN BUILDING FOOTPRINT EXTRACTION THROUGH QUANTITATIVE AND QUALITATIVE MEASURES
TASKIN KAVZOGLU, ELIF OZLEM YILMAZ, Gebze Technical University, Türkiye
WE1.R16.5: SAR-URBAN: GEOMETRY-CONDITIONED REPRESENTATION LEARNING FOR URBAN SEGMENTATION IN SAR
Tsenjung Tai, Masato Toda, Nagma Khan, Kenta Senzaki, NEC Corporation, Japan
Resources
No resources available.