Jianxun-Wang / PICNNSR

Super-resolution and denoising of fluid flow using physics-informed convolutional neural networks without high-resolution labels -- parametric forward SR and boundary inference

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PICNNSR

Super-resolution and denoising of fluid flow using physics-informed convolutional neural networks without high-resolution labels -- parametric forward SR and boundary inference.

Citation

If you find this repo useful for your research, please consider to cite:

@article{gao2021super,
  title={Super-resolution and denoising of fluid flow using physics-informed convolutional neural networks without high-resolution labels},
  author={Gao, Han and Sun, Luning and Wang, Jian-Xun},
  journal={Physics of Fluids},
  volume={33},
  number={7},
  pages={073603},
  year={2021},
  publisher={AIP Publishing LLC}
  doi = {https://doi.org/10.1063/5.0054312},
}

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Super-resolution and denoising of fluid flow using physics-informed convolutional neural networks without high-resolution labels -- parametric forward SR and boundary inference

License:MIT License


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Language:C++ 97.4%Language:Python 2.6%