TU1.R16.4
BrightStars: Scalable Unsupervised Classification and Spectral Compression of Large Multispectral Images via Dense-Mode Detection
Lionel Laurore, Liuyun DUAN, LuxCarta Technology, France
Session:
TU1.R16: Land Use Applications I Oral
Track:
Land Applications
Location:
TBD
Presentation Time:
Tue, 11 Aug, 09:15 - 09:30
Presentation
Discussion
Resources
No resources available.
Session TU1.R16
TU1.R16.1: FEW-SHOT SEGMENTATION OF MINING AREAS VIA ADAPTIVE PRIOR ENHANCEMENT AND SELECTIVE EDGE ATTENTION
Quan Cui, Longzhou Hu, Yan Zhou, Gaodian Zhou, Xiangtan University, China
TU1.R16.2: The impact of map accuracy on area estimation with remotely sensed data within the stratified random sampling design
Sergii Skakun, University of Maryland, United States
TU1.R16.3: RIPARIAN ZONE CLASSIFICATION USING SENTINEL-1 AND SENTINEL-2 TIME SERIES AND 3D CNNS
Luan Casagrande, Roberto Hirata Junior, University of São Paulo (USP), Brazil
TU1.R16.4: BrightStars: Scalable Unsupervised Classification and Spectral Compression of Large Multispectral Images via Dense-Mode Detection
Lionel Laurore, Liuyun DUAN, LuxCarta Technology, France
Contacts