Denoising sparker seismic data with Deep BiLSTM in fractional Fourier transform-Reference-Cited by-同舟云学术

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Denoising sparker seismic data with Deep BiLSTM in fractional Fourier transform

Published:2024-02 Issue: Volume:184 Page:105519
ISSN:0098-3004
Container-title:Computers & Geosciences
language:en
Short-container-title:Computers & Geosciences

Author:

Lee Dawoon^ORCID,Shin Sung Ryul,Yeo Eun-Min,Chung Wookeen

Funder

Korea Institute of Ocean Science and Technology

Korea Institute of Marine Science and Technology Promotion

Publisher

Elsevier BV

Reference42 articles.

1. Lateral prediction for noise attenuation by tx and fx techniques;Abma;Geophysics,1995

2. The fractional Fourier transform and time-frequency representations;Almeida;IEEE Trans. Signal Process.,1994

3. Review of deep learning: concepts, CNN architectures, challenges, applications, future directions;Alzubaidi;Journal of Big Data,2021

4. Random noise attenuation in seismic data using Hankel sparse low-rank approximation;Anvari;Comput. Geosci.,2021

5. Bidirectional recurrent neural networks for seismic event detection;Birnie;Geophysics,2022

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Deep Learning in Geophysics: Current Status, Challenges, and Future Directions;Journal of the Korean Society of Mineral and Energy Resources Engineers;2024-02-28

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