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