FR1.R9.4
AN EVALUATION OF INSTANCE, PANOPTIC AND UNIVERSAL SEGMENTATION ARCHITECTURES FOR AUTOMATED AGRICULTURAL FIELD BOUNDARY DELINEATION AT SCALE
Zhanpei Fang, Fuxin Li, Jamon Van Den Hoek, Oregon State University, United States
Session:
FR1.R9: Application-Oriented Remote Sensing Image Analysis Tasks Oral
Track:
Community Contributed Themes
Location:
TBD
Presentation Time:
Fri, 14 Aug, 09:15 - 09:30
Presentation
Discussion
Resources
No resources available.
Session FR1.R9
FR1.R9.1: M3: A MULTISTAGE, MULTITASK, AND MULTISPECTRAL FRAMEWORK FOR BUILDING FOOTPRINT SEGMENTATION IN INDUSTRIAL ZONES
Denis Groshev, Technical University of Munich, Germany; Matthew T Martinez, International Atomic Energy Agency, Austria
FR1.R9.2: Enhanced LULC Segmentation via Lightweight Model Refinements on ALOS-2 SAR Data
Ali Caglayan, Nevrez Imamoglu, Toru Kouyama, National Institute of Advanced Industrial Science and Technologhy (AIST), Japan
FR1.R9.3: URBANPANO-ISPRS: A VERY-HIGH-RESOLUTION PANOPTIC SEGMENTATION DATASET FOR URBAN SCENE UNDERSTANDING
Lei Chen, Qijian Zhang, Dengfeng Chai, Zhejiang University, China
FR1.R9.4: AN EVALUATION OF INSTANCE, PANOPTIC AND UNIVERSAL SEGMENTATION ARCHITECTURES FOR AUTOMATED AGRICULTURAL FIELD BOUNDARY DELINEATION AT SCALE
Zhanpei Fang, Fuxin Li, Jamon Van Den Hoek, Oregon State University, United States
Contacts