mineral-image-5k
MineralImage5k: A benchmark for zero-shot raw mineral visual recognition and description
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
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✓codemeta.json file
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✓.zenodo.json file
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○Scientific vocabulary similarity
Low similarity (1.2%) to scientific vocabulary
Last synced: 6 months ago
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Repository
MineralImage5k: A benchmark for zero-shot raw mineral visual recognition and description
Basic Info
- Host: GitHub
- Owner: dataset-ninja
- License: other
- Language: Python
- Default Branch: main
- Size: 10.5 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Created about 2 years ago
· Last pushed 7 months ago
Metadata Files
Readme
License
Citation
README.md
MineralImage5k: A Benchmark for Zero-Shot Raw Mineral Visual Recognition and Description
MineralImage5k is a dataset for object detection, semantic segmentation, and classification 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 MineralImage5k data, please cite the following reference:
``` bibtex
@dataset{MineralImage5k,
author={Sergey Nesteruk and Julia Agafonova and Igor Pavlov and Maxim Gerasimov and Nikolay Latyshev and Denis Dimitrov and Andrey Kuznetsov and Artur Kadurin and Pavel Plechov},
title={MineralImage5k: A Benchmark for Zero-Shot Raw Mineral Visual Recognition and Description},
year={2023},
url={https://github.com/ai-forever/mineral-recognition}
}
```
[Source](https://github.com/ai-forever/mineral-recognition)
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