3 papers
cs.CV2026
PRUE: A Practical Recipe for Field Boundary Segmentation at Scale
Gedeon Muhawenayo, Caleb Robinson, Subash Khanal +10
Large-scale maps of field boundaries are essential for agricultural monitoring tasks. Existing deep learning approaches for satellite-based field mapping are sensitive to illuminat…
cs.CV2026
Fields of The World: A Field Guide for Extracting Agricultural Field Boundaries
Isaac Corley, Hannah Kerner, Caleb Robinson +1
Field boundary maps are a building block for agricultural data products and support crop monitoring, yield estimation, and disease estimation. This tutorial presents the Fields of…
cs.CV2024
Fields of The World: A Machine Learning Benchmark Dataset For Global Agricultural Field Boundary Segmentation
Hannah Kerner, Snehal Chaudhari, Aninda Ghosh +9
Crop field boundaries are foundational datasets for agricultural monitoring and assessments but are expensive to collect manually. Machine learning (ML) methods for automatically e…