2 datasets found
  1. h

    FractalDB-1k

    • huggingface.co
    Updated Apr 24, 2024
    + more versions
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    Plat (2024). FractalDB-1k [Dataset]. https://huggingface.co/datasets/p1atdev/FractalDB-1k
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 24, 2024
    Authors
    Plat
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    FractalDB 1k

    FractalDB 1k dataset from Pre-training without Natural Images. Original repo | Project page | arXiv

      Citing
    

    @article{KataokaIJCV2022, author={Kataoka, Hirokatsu and Okayasu, Kazushige and Matsumoto, Asato and Yamagata, Eisuke and Yamada, Ryosuke and Inoue, Nakamasa and Nakamura, Akio and Satoh, Yutaka}, title={Pre-training without Natural Images}, article={International Journal on Computer Vision (IJCV)}, year={2022}, }… See the full description on the dataset page: https://huggingface.co/datasets/p1atdev/FractalDB-1k.

  2. Z

    ANNs pre-trained on Retinal Waves

    • data.niaid.nih.gov
    • zenodo.org
    Updated Nov 17, 2023
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    Cappell, Benjamin (2023). ANNs pre-trained on Retinal Waves [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_7779519
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    Dataset updated
    Nov 17, 2023
    Dataset provided by
    Cappell, Benjamin
    Stoll, Andreas
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Different Artificial Neural Networks (saved weights), some only pre-trained either on rwave-1024 or rwave-4096 or FractalDB1000 datasets; some fine-tuned or trained from scratch (pt_none_ft... or pt_ft... or ...scratch...) on CIFAR10/100 or ImageNet1k. Retinal Waves for Pre-Training Artificial Neural Networks Mimicking Real Prenatal Development - see https://github.com/BennyCa/ReWaRD for filter visualization and further fine-tuning possibilities Pre-training and fine-tuning was conducted using the codebase https://github.com/hirokatsukataoka16/FractalDB-Pretrained-ResNet-PyTorch

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Email
Click to copy link
Link copied
Close
Cite
Plat (2024). FractalDB-1k [Dataset]. https://huggingface.co/datasets/p1atdev/FractalDB-1k

FractalDB-1k

FractalDB 1k

p1atdev/FractalDB-1k

Explore at:
20 scholarly articles cite this dataset (View in Google Scholar)
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Apr 24, 2024
Authors
Plat
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

FractalDB 1k

FractalDB 1k dataset from Pre-training without Natural Images. Original repo | Project page | arXiv

  Citing

@article{KataokaIJCV2022, author={Kataoka, Hirokatsu and Okayasu, Kazushige and Matsumoto, Asato and Yamagata, Eisuke and Yamada, Ryosuke and Inoue, Nakamasa and Nakamura, Akio and Satoh, Yutaka}, title={Pre-training without Natural Images}, article={International Journal on Computer Vision (IJCV)}, year={2022}, }… See the full description on the dataset page: https://huggingface.co/datasets/p1atdev/FractalDB-1k.

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