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- sx/:
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- synthetic data, high resolution without noise, size = (256, 256)
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- nx2/:
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- synthetic data, low resolution data with some random noise, size = (128, 128)
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-
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- field/:
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- three field seismic data, the size is avaliable from their name,
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- such as "lulia_592x400.dat", its size is (592, 400).
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-
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-
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-
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- Citation
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- If you find this work useful in your research, please consider citing:
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-
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- @ARTICLE{deep2021li,
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- author={Li, Jintao and Wu, Xinming and Hu, Zhanxuan},
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- journal={IEEE Transactions on Geoscience and Remote Sensing},
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- title={Deep Learning for Simultaneous Seismic Image Super-Resolution and Denoising},
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- year={2021},
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- volume={},
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- number={},
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- pages={1-11},
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- doi={10.1109/TGRS.2021.3057857}
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- }
 
 
 
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+ sx/:
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+ synthetic data, high resolution without noise, size = (256, 256)
3
+ nx2/:
4
+ synthetic data, low resolution data with some random noise, size = (128, 128)
5
+
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+ field/:
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+ three field seismic data, the size is avaliable from their name,
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+ such as "lulia_592x400.dat", its size is (592, 400).
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+
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+
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+
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+ Citation
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+ If you find this work useful in your research, please consider citing:
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+
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+ @ARTICLE{deep2021li,
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+ author={Li, Jintao and Wu, Xinming and Hu, Zhanxuan},
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+ journal={IEEE Transactions on Geoscience and Remote Sensing},
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+ title={Deep Learning for Simultaneous Seismic Image Super-Resolution and Denoising},
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+ year={2021},
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+ volume={},
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+ number={},
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+ pages={1-11},
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+ doi={10.1109/TGRS.2021.3057857}
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+ }
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+
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+ Additional information can be found at https://github.com/LukasMosser/seismic-datasets