2 citations · 3 across the 3 of their papers we have counts for
3 papers
physics.geo-ph2023★ 1 cited
A self-supervised scheme for ground roll suppression
Sixiu Liu, Claire Birnie, Andrey Bakulin +3
In recent years, self-supervised procedures have advanced the field of seismic noise attenuation, due to not requiring a massive amount of clean labeled data in the training stage,…
physics.geo-ph2023★ 2 cited
Gabor-based learnable sparse representation for self-supervised denoising
Sixiu Liu, Shijun Cheng, Tariq Alkhalifah
Traditional supervised denoising networks learn network weights through "black box" (pixel-oriented) training, which requires clean training labels. The uninterpretability nature o…
physics.geo-ph2021
The potential of self-supervised networks for random noise suppression in seismic data
Claire Birnie, Matteo Ravasi, Tariq Alkhalifah +1
Noise suppression is an essential step in any seismic processing workflow. A portion of this noise, particularly in land datasets, presents itself as random noise. In recent years,…