| --- |
| configs: |
| - config_name: default |
| default: true |
| features: |
| - name: image |
| dtype: image |
| - name: annotation |
| dtype: |
| image: |
| mode: L |
| license: cc-by-4.0 |
| task_categories: |
| - image-segmentation |
| size_categories: |
| - n<1K |
| --- |
| |
| # Sorghum Weed Segmentation |
|
|
| A dataset for semantic segmentation of weeds in a sorghum plot. The dataset contains 252 images with pixel-level mask annotations. In the masks, 0 is the background, 1 is sorghum, 2 is grass, and 3 is broadleaf weed. |
|
|
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{justina2024sorghumweeddataset_classification, |
| title={SorghumWeedDataset\_Classification and SorghumWeedDataset\_Segmentation datasets for classification, detection, and segmentation in deep learning}, |
| author={Justina, Michael J and Thenmozhi, M}, |
| journal={Data in brief}, |
| volume={52}, |
| pages={109935}, |
| year={2024}, |
| publisher={Elsevier} |
| } |
| ``` |
|
|
| Michael, Justina; M, Thenmozhi (2023), “SorghumWeedDataset_Segmentation”, Mendeley Data, V1, doi: 10.17632/y9bmtf4xmr.1 |
