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20232026
most citedFields of The World: A Machine Learning Benchmark Dataset For Global Agricultural Field Boundary Segmentation

2 citations · 7 across the 24 of their papers we have counts for

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Showing 2026 · cs.CVShow all

10 papers · 2 filters

cs.CV2026

Fields of the Planet: Field Boundary Mapping Beyond 10m

Isaac Corley, Caleb Robinson, Jennifer Marcus +1

Field-boundary maps support crop monitoring, irrigation planning, and yield estimation, but many smallholder parcels span only a few 10 m Sentinel-2 pixels. We introduce Fields of…

cs.CV2026★ 1 cited

No One Knows the State of the Art in Geospatial Foundation Models

Isaac Corley, Nils Lehmann, Caleb Robinson +6

Geospatial foundation models (GFMs) have been proposed as generalizable backbones for disaster response, land-cover mapping, food-security monitoring, and other high-stakes Earth-o…

cs.CV2026

Overhead Wildlife Locator (OWL): Benchmarking Weakly Supervised Learning for Aerial Wildlife Surveys

Isai Daniel Chacón, Zhongqi Miao, Bruno Demuro +9

Automated aerial wildlife surveys increasingly rely on deep learning, yet standard object detectors require bounding-box annotations, reported to be up to seven times slower and th…

cs.CV2026★ 1 cited

The first global agricultural field boundary map at 10m resolution

Caleb Robinson, Gedeon Muhawenayo, Subash Khanal +9

The agricultural field is the natural unit at which crops are planted, managed, regulated, and reported, yet most global remote-sensing products for agriculture are only available…

cs.CV2026

WATCH: Wide-Area Archaeological Site Tracking for Change Detection

Girmaw Abebe Tadesse, Titien Bartette, Andrew Hassanali +7

Monitoring archaeological sites at scale is vital for protecting cultural heritage, yet pinpointing when disturbances occur remains difficult because visual cues are subtle and gro…

cs.CV2026

GeoAI Agency Primitives

Akram Zaytar, Rohan Sawahn, Caleb Robinson +5

We present ongoing research on agency primitives for GeoAI assistants -- core capabilities that connect Foundation models to the artifact-centric, human-in-the-loop workflows where…

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

Advancing Earth Observation Through Machine Learning: A TorchGeo Tutorial

Caleb Robinson, Nils Lehmann, Adam J. Stewart +4

Earth observation machine learning pipelines differ fundamentally from standard computer vision workflows. Imagery is typically delivered as large, georeferenced scenes, labels may…

cs.CV2026

Satellite-Based Detection of Looted Archaeological Sites Using Machine Learning

Girmaw Abebe Tadesse, Titien Bartette, Andrew Hassanali +7

Looting at archaeological sites poses a severe risk to cultural heritage, yet monitoring thousands of remote locations remains operationally difficult. We present a scalable and sa…

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…