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

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