Project-AgML/EfficientMaize_classification

Efficientmaize Classification

A dataset for quality classification of maize. The dataset contains raw and augmented versions.
The raw dataset contains 4,846 images.
Images per class:

• Bad: 2,211
• Good: 2,635

The augmented dataset contains 28,899 images.
Images per class:

• Bad: 13,246
• Good: 15,653

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

Citation

@article{asante2024efficientmaize,
  title={EfficientMaize: A lightweight dataset for maize classification on resource-constrained devices},
  author={Asante, Emmanuel and Appiah, Obed and Appiahene, Peter and Adu, Kwabena},
  journal={Data in Brief},
  volume={54},
  pages={110261},
  year={2024},
  publisher={Elsevier}
}

Asante, Emmanuel ; Appiah, Obed; APPIAHENE, PETER (2023), “Lightweight Dataset for Maize Classification on Resource-Constrained Devices”, Mendeley Data, V2, doi: 10.17632/r6vvm5jkh6.2