Datasets:
File size: 1,449 Bytes
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configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: cc-by-4.0
task_categories:
- image-classification
size_categories:
- 1K<n<10K
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': clustered
'1': single
'2': undefined
splits:
- name: train
num_bytes: 42747333
num_examples: 5364
download_size: 37739572
dataset_size: 42747333
---
# Rice Seedling Classification
A dataset for image classification of Rice Seedlings. The dataset contains 5,364 images across 3 classes: clustered, single, undefined.
Images per class:
- clustered: 1,437
- single: 1,367
- undefined: 2,560
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
## Citation
```bibtex
@article{luu2024rigad,
title={RiGaD: An aerial dataset of rice seedlings for assessing germination rates and density},
author={Luu, Trong Hieu and Cao, Hoang-Long and Ngo, Quang Hieu and Nguyen, Thanh Tam and El Makrini, Ilias and Vanderborght, Bram},
journal={Data in Brief},
volume={57},
pages={111118},
year={2024},
publisher={Elsevier}
}
```
Luu, T. H., Cao, H. L., Ngo, Q. H., Nguyen, T. T., El Makrini, I., & Vanderborght, B. (2024). RiGaD: An aerial dataset of rice seedlings for assessing germination rates and density. Zenodo. https://doi.org/10.5281/zenodo.11658969 |