Bacterial Leaf Blight (BLB) UAV Dataset and U-Net with ResNet-101 Code for BLB Detection

The UAV dataset of paddy rice affected by Bacterial Leaf Blight (BLB) disease, with available code for a U-Net architecture using a ResNet-101 backbone for model training and analysis.

The dataset can be accessed through the following Google Drive link: https://drive.google.com/drive/folders/17mCuj35euNjwNEIEqNqM_bJqNdHLuXwL?usp=sharing

If you use this code or dataset for your research, please consider citing:

@article{logavitool2025field,
title={Field-scale detection of Bacterial Leaf Blight in rice based on UAV multispectral imaging and deep learning frameworks},
author={Logavitool, Guntaga and Horanont, Teerayut and Thapa, Aakash and Intarat, Kritchayan and Wuttiwong, Kanok-on},
journal={PloS one},
volume={20},
number={1},
pages={e0314535},
year={2025},
publisher={Public Library of Science}
}

• Logavitool G, Horanont T, Thapa A, Intarat K, Wuttiwong K-o (2025) Field-scale detection of Bacterial Leaf Blight in rice based on UAV multispectral imaging and deep learning frameworks. PLoS ONE 20(1): e0314535. https://doi.org/10.1371/journal.pone.0314535