USU-Corn-WeedDB: A UAV RGB Image Dataset for Multi-Species Weed Detection in Forage Corn
Paper • 2606.06709 • Published
Datasets:
image imagewidth (px) 640 640 | split stringclasses 3
values | objects dict | base_image_index stringdate 1015-01-01 00:00:00 1297-01-01 00:00:00 | x_coord stringclasses 7
values | y_coord stringclasses 5
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End of preview. Expand in Data Studio
Usu Corn Weeddb Detection
This dataset comprises real-world RGB images capturing corn fields with various weed species. Collected directly in agricultural field environments, it provides ground-truth bounding box annotations for weed detection tasks in precision farming applications. The dataset contains 800 images with 10,539 bounding box annotations across 3 categories.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
The original train/test/val split has been preserved in the split column.
Citation
@article{bhandari2026usu,
title={USU-Corn-WeedDB: A UAV RGB Image Dataset for Multi-Species Weed Detection in Forage Corn},
author={Bhandari, Utsav and Burlakoti, Saroj and Miller, Rhonda and Young, Sierra and Westra, Eric and Etienne, Aaron},
journal={arXiv preprint arXiv:2606.06709},
year={2026}
}
Bhandari, U., & Etienne, A. (2026). USU-Corn-WeedDB: A UAV RGB Image Dataset for Multi-Species Weed Detection in Forage Corn [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.20044178
This dataset was reformatted from its original format to match HuggingFace standards.
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