Sixiu Liu

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3 Article
1 Conference contribution
1 Paper

Gabor-based learnable sparse representation for self-supervised denoising
Liu, S., Cheng, S. & Alkhalifah, T., 2024, (Accepted/In press) In: IEEE Transactions on Geoscience and Remote Sensing. 62, p. 1 1 p., 5903016.
Research output: Contribution to journal › Article › peer-review

Open Access
4 Scopus citations
Trace-wise coherent noise suppression via a self-supervised blind-trace deep-learning scheme
Liu, S., Birnie, C. & Alkhalifah, T., Nov 1 2023, In: Geophysics. 88, 6, p. V459-V472
Research output: Contribution to journal › Article › peer-review

Open Access
8 Scopus citations
Aiding self-supervised coherent noise suppression by the introduction of signal segmentation using blind-spot networks
Liu, S., Birnie, C., Alkhalifah, T. & Bakulin, A., Aug 15 2022, p. 2857-2861. 5 p.
Research output: Contribution to conference › Paper › peer-review
5 Scopus citations
COHERENT NOISE SUPPRESSION VIA A SELF-SUPERVISED DEEP LEARNING SCHEME
Liu, S., Birnie, C. & Alkhalifah, T., 2022, 83rd EAGE Conference and Exhibition 2022. European Association of Geoscientists and Engineers, EAGE, p. 1418-1422 5 p. (83rd EAGE Conference and Exhibition 2022; vol. 2).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
The potential of self-supervised networks for random noise suppression in seismic data
Birnie, C., Ravasi, M., Liu, S. & Alkhalifah, T. A., Nov 13 2021, In: Artificial Intelligence in Geosciences. 2, p. 47-59 13 p.
Research output: Contribution to journal › Article › peer-review
50 Scopus citations

New Findings from King Abdullah University of Science and Technology (KAUST) Update Understanding of Geophysics (Trace-wise Coherent Noise Suppression Via a Self-supervised Blind-trace Deep-learning Scheme)
Alkhalifah, T. A., Birnie, C. E. & Liu, S.
03/29/24
1 item of Media coverage
Press/Media: Press / Media

Sixiu Liu

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Collaborations and top research areas from the last five years

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Gabor-based learnable sparse representation for self-supervised denoising

Trace-wise coherent noise suppression via a self-supervised blind-trace deep-learning scheme

Aiding self-supervised coherent noise suppression by the introduction of signal segmentation using blind-spot networks

COHERENT NOISE SUPPRESSION VIA A SELF-SUPERVISED DEEP LEARNING SCHEME

The potential of self-supervised networks for random noise suppression in seismic data

New Findings from King Abdullah University of Science and Technology (KAUST) Update Understanding of Geophysics (Trace-wise Coherent Noise Suppression Via a Self-supervised Blind-trace Deep-learning Scheme)

Sixiu Liu

Fingerprint

Collaborations and top research areas from the last five years

Research output

Gabor-based learnable sparse representation for self-supervised denoising

Trace-wise coherent noise suppression via a self-supervised blind-trace deep-learning scheme

Aiding self-supervised coherent noise suppression by the introduction of signal segmentation using blind-spot networks

COHERENT NOISE SUPPRESSION VIA A SELF-SUPERVISED DEEP LEARNING SCHEME

The potential of self-supervised networks for random noise suppression in seismic data

Press/Media

New Findings from King Abdullah University of Science and Technology (KAUST) Update Understanding of Geophysics (Trace-wise Coherent Noise Suppression Via a Self-supervised Blind-trace Deep-learning Scheme)