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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… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/EfficientMaize_classification.

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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

bibtex

@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