deep-nir-fruit

https://github.com/dataset-ninja/deep-nir-fruit

Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

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CITATION.cff file
Found CITATION.cff file
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codemeta.json file
Found codemeta.json file
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.zenodo.json file
Found .zenodo.json file
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DOI references
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Academic publication links
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Academic email domains
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Institutional organization owner
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JOSS paper metadata
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Scientific vocabulary similarity
Low similarity (1.4%) to scientific vocabulary

Last synced: 6 months ago · JSON representation ·

Repository

Basic Info

Host: GitHub
Owner: dataset-ninja
License: other
Language: Python
Default Branch: main
Size: 19.4 MB

Statistics

Stars: 0
Watchers: 1
Forks: 0
Open Issues: 0
Releases: 0

Created over 2 years ago · Last pushed 6 months ago

Metadata Files

Readme License Citation

README.md

deepNIR: Dataset for Generating Synthetic near-infrared (NIR) Images and Improved Fruit Detection System Using Deep Learning Techniques

deepNIR Fruit Detection is a dataset for object detection and unsupervised learning tasks.

Owner

Name: dataset-ninja
Login: dataset-ninja
Kind: organization

Repositories: 1
Profile: https://github.com/dataset-ninja

Citation (CITATION.md)

If you make use of the deepNIR data, please cite the following reference:

```bibtex
@dataset{inkyu_sa_2022_6324489,
  author       = {Inkyu Sa and
                  Jong Yoon Lim and
                  Ho Seok Ahn},
  title        = {{deepNIR: Dataset for generating synthetic NIR 
                   images and improved fruit detection system using
                   deep learning techniques}},
  month        = mar,
  year         = 2022,
  publisher    = {Zenodo},
  version      = {0.1},
  doi          = {10.5281/zenodo.6324489},
  url          = {https://doi.org/10.5281/zenodo.6324489}
}
```

[Source](https://zenodo.org/record/6324489/export/hx)

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Dependencies

requirements.txt pypi

ecosyste.ms

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Open Source Science