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Abstract

Summary

Image-to-image translation using GANs have successfully been applied to a wide variety of problems, from mundane implementations to turn horses into zebras, to stunning synthetic media deepfakes. We explore its application in geophysics as a cost-reduction tool, and demonstrate its potential in 3D field data. We show it can be used to learn the mapping between different data flavours of interest in modern data processing workflows: acoustic/elastic for full-waveform inversion and geophone vertical-component/hydrophone-pressure for up- and down-going wavefield separation.

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/content/papers/10.3997/2214-4609.202011334
2021-10-18
2024-03-28
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References

  1. Long, J., Shelhamer, E. and Darrell, T.
    [2015] Fully convolutional networks for semantic segmentation. In: Proceedings of the IEEE conference on computer vision and pattern recognition. 3431–3440.
    [Google Scholar]
  2. Wang, L., Ouyang, W., Wang, X. and Lu, H.
    [2015] Visual tracking with fully convolutional networks. In: Proceedings of the IEEE international conference on computer vision. 3119–3127.
    [Google Scholar]
  3. Zhu, J.Y., Park, T., Isola, P. and Efros, A.A.
    [2017] Unpaired image-to-image translation using cycle-consistent adversarial networks. arXiv preprint.
    [Google Scholar]
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