<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=sharingIf you use this code or dataset for your research, please consider citing:<i>@article{logavitool2025field,</i><br><i>title={Field-scale detection of Bacterial Leaf Blight in rice based on UAV multispectral imaging and deep learning frameworks},</i><br><i>author={Logavitool, Guntaga and Horanont, Teerayut and Thapa, Aakash and Intarat, Kritchayan and Wuttiwong, Kanok-on},</i><br><i>journal={PloS one},</i><br><i>volume={20},</i><br><i>number={1},</i><br><i>pages={e0314535},</i><br><i>year={2025},</i><br><i>publisher={Public Library of Science}</i><br><i>}</i><br><br>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

本数据集为受白叶枯病（Bacterial Leaf Blight, BLB）侵染的稻田无人机（Unmanned Aerial Vehicle, UAV）数据集，附带采用ResNet-101作为骨干网络的U-Net架构代码，可用于模型训练与分析。该数据集可通过以下Google Drive链接获取：https://drive.google.com/drive/folders/17mCuj35euNjwNEIEqNqM_bJqNdHLuXwL?usp=sharing。若您在研究中使用本代码或数据集，请引用如下文献：
@article{logavitool2025field,
title={基于无人机多光谱成像与深度学习框架的稻田白叶枯病田间尺度检测},
author={Logavitool, Guntaga and Horanont, Teerayut and Thapa, Aakash and Intarat, Kritchayan and Wuttiwong, Kanok-on},
journal={公共科学图书馆·综合（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) 基于无人机多光谱成像与深度学习框架的稻田白叶枯病田间尺度检测. 公共科学图书馆·综合, 20(1): e0314535. https://doi.org/10.1371/journal.pone.0314535