Datasets:
File size: 1,376 Bytes
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dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': cracked
'1': crushed
'2': no_buds
'3': no_damage
'4': single_damaged_buds
'5': two_buds
splits:
- name: train
num_bytes: 2301208454
num_examples: 153
download_size: 2301235850
dataset_size: 2301208454
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
task_categories:
- image-classification
size_categories:
- n<1K
---
# Sugarcane Damage Usa
A dataset for classification of sugarcane damage. The dataset contains 153 images across 6 classes: cracked, crushed, no_buds, no_damage, single_damaged_buds, two_buds.
Images per class:
- cracked: 24
- crushed: 24
- no_buds: 21
- no_damage: 36
- single_damaged_buds: 24
- two_buds: 24
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
## Citation
```bibtex
@ARTICLE{8412587,
author={Alencastre-Miranda, Moises and Davidson, Joseph R. and Johnson, Richard M. and Waguespack, Herman and Krebs, Hermano Igo},
journal={IEEE Robotics and Automation Letters},
title={Robotics for Sugarcane Cultivation: Analysis of Billet Quality using Computer Vision},
year={2018},
volume={3},
number={4},
pages={3828-3835},
doi={10.1109/LRA.2018.2856999}
}
``` |