Project-AgML/CoLeaf_nutritional_deficiency_classification

CoLeaf Nutritional Deficiency Classification

A dataset for classification of nutritional deficiencies in coffee leaves. The dataset contains 902 images across 9 classes: boron-B, calcium-Ca, healthy, iron-Fe, magnesium-Mg, manganese-Mn, nitrogen-N, phosphorus-P, potasium-K.
Images per class:

• boron-B: 101
• calcium-Ca: 162
• healthy: 6
• iron-Fe: 65
• magnesium-Mg: 79
• manganese-Mn: 83
• nitrogen-N: 64
• phosphorus-P: 246
• potasium-K: 96

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

Citation

@article{tuesta2023coleaf,
  title={CoLeaf-DB: Peruvian coffee leaf images dataset for coffee leaf nutritional deficiencies detection and classification},
  author={Tuesta-Monteza, Victor A and Mejia-Cabrera, Heber I and Arcila-Diaz, Juan},
  journal={Data in Brief},
  volume={48},
  pages={109226},
  year={2023},
  publisher={Elsevier}
}

Tuesta-Monteza, Víctor A; Mejia-Cabrera, Heber I.; Arcila-Diaz, Juan (2023), “CoLeaf DATASET”, Mendeley Data, V2, doi: 10.17632/brfgw46wzb.2