https://github.com/jh-yi/DND-SB

https://github.com/jh-yi/DND-SB

Last synced: 7 days ago
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• Host: GitHub
• URL: https://github.com/jh-yi/DND-SB
• Owner: jh-yi
• License: mit
• Created: 2020-10-16T15:43:46.000Z (about 4 years ago)
• Default Branch: main
• Last Pushed: 2020-10-20T20:33:54.000Z (about 4 years ago)
• Last Synced: 2024-08-02T15:33:50.073Z (3 months ago)
• Language: Python
• Size: 40 KB
• Stars: 5
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# DND-SB

We present the Deep Nutrient Deficiency for Sugar Beet (DND-SB) dataset, which contains 5648 RGB images of sugar beet captured over the whole growth period in 2019  at the long term fertilizerexperiment (LTFE) Dikopshof near Bonn. The images were annotated with seven types of fertilizer treatments. The dataset is used for image classification and domain adaptation.

## Download

[dataset](https://zenodo.org/record/4106221#.X42FmXUzbd6)   

## Cite

If you find this dataset useful for your research, please cite our [paper](https://doi.org/10.3390/s20205893):

```

@article{yi2020deep,  

    title={Deep Learning for Non-Invasive Diagnosis of Nutrient Deficiencies in Sugar Beet Using RGB Images},  

    author={Yi, Jinhui and Krusenbaum, Lukas and Unger, Paula and Hüging, Hubert and Seidel, Sabine J and Schaaf, Gabriel and Gall, Juergen},  

    journal={Sensors},  

    volume={20},  

    pages={5893},  

    year={2020},  

}  

```

## License

This dataset follows Creative Commons Attribution Non Commercial Share Alike 4.0 Internation License.