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Project-AgML/sunflower_disease_classification

Sunflower Disease Classification A dataset for disease classification of sunflowers. The dataset contains 2,358 images across 4 classes: Downy_mildew, Fresh_leaf, Gray_mold, Leaf_scars.Images per class: Downy_mildew: 590 Fresh_leaf: 649 Gray_mold: 470 Leaf_scars: 649 This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. Citation @article{sara2022extensive, title={An extensive sunflower dataset representation for… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/sunflower_disease_classification.

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Sunflower Disease Classification

A dataset for disease classification of sunflowers. The dataset contains 2,358 images across 4 classes: Downymildew, Freshleaf, Graymold, Leafscars. Images per class:

—Downy_mildew: 590
—Fresh_leaf: 649
—Gray_mold: 470
—Leaf_scars: 649

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

Citation

bibtex

@article{sara2022extensive,
  title={An extensive sunflower dataset representation for successful identification and classification of sunflower diseases},
  author={Sara, Umme and Rajbongshi, Aditya and Shakil, Rashiduzzaman and Akter, Bonna and Sazzad, Sadia and Uddin, Mohammad Shorif},
  journal={Data in brief},
  volume={42},
  pages={108043},
  year={2022},
  publisher={Elsevier}
}

Rajbongshi, Aditya; Sara, Umme ; Akter, Bonna ; Shakil, Rashiduzzaman ; Sazzad, Sadia (2022), “Sun Flower Fruits and Leaves dataset for Sunflower Disease Classification through Machine Learning and Deep Learning”, Mendeley Data, V1, doi: 10.17632/b83hmrzth8.1