---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: mask
    dtype: image
  splits:
  - name: train
    num_bytes: 92768863
    num_examples: 125
  download_size: 92773297
  dataset_size: 92768863
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: gpl-3.0
task_categories:
- image-segmentation
size_categories:
- n<1K
---


# Sugarbeet Weed Segmentation

A dataset for semantic segmentation of Sugarbeet Weed Segmentation. The dataset contains 125 images with pixel-level mask annotations.

This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.

## Citation

```bibtex
@ARTICLE{8115245,
author={I. Sa and Z. Chen and M. Popović and R. Khanna and F. Liebisch and J. Nieto and R. Siegwart},
journal={IEEE Robotics and Automation Letters},
title={weedNet: Dense Semantic Weed Classification Using Multispectral Images and MAV for Smart Farming},
year={2018},
volume={3},
number={1},
pages={588-595},
doi={10.1109/LRA.2017.2774979},
month={Jan}
}
```

https://github.com/inkyusa/weedNet