Datasets:
Tasks:
Image Segmentation
Modalities:
Image
Formats:
imagefolder
Languages:
English
Size:
1K - 10K
ArXiv:
Tags:
biology
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RiceSEG
Global Rice Multi-Class Segmentation Dataset (RiceSEG): A Comprehensive and Diverse High-Resolution RGB-Annotated Images for the Development and Benchmarking of Rice Segmentation Algorithms.
1.Downloads
You can find RiceSEG files in “files and versions” and download them to the specified directory.
2.Dataset Structure
The folder is divided into five countries, and each country folder has a corresponding regional subdataset, details of which can be found in the article table3.
3. Citation Information
The article is currently online at arxiv. Please cite our publication if this dataset helped your research:
@misc{zhou2025globalricemulticlasssegmentation,
title={Global Rice Multi-Class Segmentation Dataset (RiceSEG): A Comprehensive and Diverse High-Resolution RGB-Annotated Images for the Development and Benchmarking of Rice Segmentation Algorithms},
author={Junchi Zhou and Haozhou Wang and Yoichiro Kato and Tejasri Nampally and P. Rajalakshmi and M. Balram and Keisuke Katsura and Hao Lu and Yue Mu and Wanneng Yang and Yangmingrui Gao and Feng Xiao and Hongtao Chen and Yuhao Chen and Wenjuan Li and Jingwen Wang and Fenghua Yu and Jian Zhou and Wensheng Wang and Xiaochun Hu and Yuanzhu Yang and Yanfeng Ding and Wei Guo and Shouyang Liu},
year={2025},
eprint={2504.02880},
archivePrefix={arXiv},
primaryClass={eess.IV},
url={https://arxiv.org/abs/2504.02880},
}
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