4 papers · 1 filter
Embeddings based Anomaly Detection for Cleaning Global Crop Type Reference Datasets
Syed Roshaan Ali Shah, Kristof Van Tricht, Christina Butsko +2
High quality reference data remain a critical bottleneck for crop-type mapping at any spatial and temporal scale. Operational systems such as WorldCereal aggregate labels from hete…
Delineate Anything v2: A Global Foundation Model for Field Delineation
Mykola Lavreniuk, Nataliia Kussul, Andrii Shelestov +4
Accurate agricultural field boundary delineation at large scale is a foundational task for food security, supply chain transparency, and carbon accounting. While vision foundation…
Delineate Anything Flow: Fast, Country-Level Field Boundary Detection from Any Source
Mykola Lavreniuk, Nataliia Kussul, Andrii Shelestov +4
Accurate delineation of agricultural field boundaries from satellite imagery is essential for land management and crop monitoring, yet existing methods often produce incomplete bou…
Delineate Anything: Resolution-Agnostic Field Boundary Delineation on Satellite Imagery
Mykola Lavreniuk, Nataliia Kussul, Andrii Shelestov +4
The accurate delineation of agricultural field boundaries from satellite imagery is vital for land management and crop monitoring. However, current methods face challenges due to l…