collaborators

5 papers

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.LG2025

Deploying Geospatial Foundation Models in the Real World: Lessons from WorldCereal

Christina Butsko, Kristof Van Tricht, Gabriel Tseng +6

The increasing availability of geospatial foundation models has the potential to transform remote sensing applications such as land cover classification, environmental monitoring,…

cs.CV2025

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…