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The potential of self-supervised networks for random noise suppression in sei…
Noise suppression is an essential step in many seismic processing workflows. A portion of this noise, particularly in land datasets, presents itself as random noise. In recent years, neural networks have been successfully used to denoise seismic data in a supervised fashion. However, supervised learning always comes with the often unachievable requirement of having noisy-clean data pairs for tr…
- Edisi
- Vol.2, December 2021
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 13 hlm PDF, 7.813 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
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