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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

A fully unsupervised and highly generalized deep learning approach for random noise suppression
Omar M. Saad, Yangkang Chen
Geophysical Prospecting (2020) Vol. 69, Iss. 4, pp. 709-726
Closed Access | Times Cited: 80

Showing 26-50 of 80 citing articles:

A deep learning framework for suppressing prestack seismic random noise without noise-free labels
Han Wang, Jie Zhang
Energy Geoscience (2024) Vol. 5, Iss. 3, pp. 100297-100297
Open Access | Times Cited: 2
SigRecover: Recovering Signal from Noise in Distributed Acoustic Sensing Data Processing
Yangkang Chen
Seismological Research Letters (2024) Vol. 95, Iss. 3, pp. 1976-1985
Closed Access | Times Cited: 2
Interpretable unsupervised learning framework for multi-dimensional erratic and random noise attenuation
Liuqing Yang, Sergey Fomel, Shoudong Wang, et al.
IEEE Transactions on Geoscience and Remote Sensing (2024) Vol. 62, pp. 1-20
Closed Access | Times Cited: 2
Ground-truth-free deep learning for 3D seismic denoising and reconstruction with channel attention mechanism
Yang Cui, Juan Wu, Min Bai, et al.
Geophysics (2024) Vol. 89, Iss. 6, pp. V503-V520
Closed Access | Times Cited: 2
An effective self-supervised learning method for attenuating various types of seismic noise
Shijun Cheng, Zhiyao Cheng, Chao Jiang, et al.
Geophysics (2024) Vol. 89, Iss. 6, pp. V589-V604
Closed Access | Times Cited: 2
Removing abnormal environmental noise in nodal land seismic data using deep learning
Xiaobin Li, Qiaomu Qi, Yuyong Yang, et al.
Geophysics (2023) Vol. 89, Iss. 1, pp. WA143-WA156
Closed Access | Times Cited: 6
Fast dictionary learning for 3D simultaneous seismic data reconstruction and denoising
Juan Wu, Qingli Chen, Zhixian Gui, et al.
Journal of Applied Geophysics (2021) Vol. 194, pp. 104446-104446
Closed Access | Times Cited: 15
Residual learning with feedback for strong random noise attenuation in seismic data
Zhangquan Liao, Yong Li, Yingtian Liu, et al.
Geophysics (2022) Vol. 88, Iss. 1, pp. V45-V57
Closed Access | Times Cited: 10
Random Noise Attenuation by Self-supervised Learning from Single Seismic Data
Xiaojing Wang, Yuhan Sui, Wei Wang, et al.
Mathematical Geosciences (2022) Vol. 55, Iss. 3, pp. 401-422
Closed Access | Times Cited: 9
Diffraction denoising using self‐supervised learning
Magdalena Markovic, Reza Malehmir, Alireza Malehmir
Geophysical Prospecting (2023) Vol. 71, Iss. 7, pp. 1215-1225
Open Access | Times Cited: 5
DRR: An open-source multi-platform package for the damped rank-reduction method and its applications in seismology
Yangkang Chen, Weilin Huang, Liuqing Yang, et al.
Computers & Geosciences (2023) Vol. 180, pp. 105440-105440
Closed Access | Times Cited: 5
A U-Net Based Multi-Scale Deformable Convolution Network for Seismic Random Noise Suppression
Haixia Zhao, Y. Zhou, Tingting Bai, et al.
Remote Sensing (2023) Vol. 15, Iss. 18, pp. 4569-4569
Open Access | Times Cited: 5
Dictionary Learning for Single-Channel Passive Seismic Denoising
Yangkang Chen, Alexandros Savvaidis, Sergey Fomel
Seismological Research Letters (2023) Vol. 94, Iss. 6, pp. 2840-2851
Closed Access | Times Cited: 5
Retrieving useful signals from highly corrupted erratic noise using robust residual dictionary learning
Wei Chen, Yapo Abolé Serge Innocent Oboué, Yangkang Chen
Geophysics (2022) Vol. 88, Iss. 1, pp. WA55-WA64
Closed Access | Times Cited: 8
Seismic signal denoising using Swin-Conv-UNet
Mu Ding, Yatong Zhou, Yue Chi
Journal of Applied Geophysics (2024) Vol. 223, pp. 105355-105355
Closed Access | Times Cited: 1
Cosine Spectral Association Network for DAS VSP Data High-Precision Recovery
Jilei Sui, Zhicheng Zhong, Yanan Tian, et al.
IEEE Transactions on Geoscience and Remote Sensing (2024) Vol. 62, pp. 1-13
Closed Access | Times Cited: 1
SelfMixed: Self-supervised mixed noise attenuation for distributed acoustic sensing data
Zitai Xu, Bangyu Wu, Yisi Luo, et al.
Geophysics (2024) Vol. 89, Iss. 5, pp. V415-V436
Closed Access | Times Cited: 1
Re‐visible blind block network: An unsupervised seismic data random noise attenuation method
Jing Wang, Bangyu Wu, Hui Yang, et al.
Geophysical Prospecting (2024) Vol. 72, Iss. 7, pp. 2739-2760
Closed Access | Times Cited: 1
Self-Supervised Denoising for Distributed Acoustic Sensing Vertical Seismic Profile Data via Improved Blind Spot Network
Yuxing Zhao, Yue Li, Ning Wu, et al.
IEEE Transactions on Geoscience and Remote Sensing (2023) Vol. 61, pp. 1-15
Closed Access | Times Cited: 4
Loss functions in machine learning for seismic random noise attenuation
Hyunggu Jun, Han‐Joon Kim
Geophysical Prospecting (2023) Vol. 72, Iss. 3, pp. 978-995
Closed Access | Times Cited: 4
A Natural Images Pre-Trained Deep Learning Method for Seismic Random Noise Attenuation
Haixia Zhao, Tingting Bai, Zhiqiang Wang
Remote Sensing (2022) Vol. 14, Iss. 2, pp. 263-263
Open Access | Times Cited: 7
3-D Structural Complexity-Guided Predictive Filtering: A Comparison Between Different Non-Stationary Strategies
Chao Fu, Zhifei Gong, Lei Chen, et al.
IEEE Transactions on Geoscience and Remote Sensing (2022) Vol. 60, pp. 1-15
Closed Access | Times Cited: 7
Seismic random noise attenuation using effective and efficient dictionary learning
Zhenjie Feng
Journal of Applied Geophysics (2021) Vol. 186, pp. 104258-104258
Closed Access | Times Cited: 9
Seismic erratic noise attenuation using unsupervised anomaly detection
Woodon Jeong, Mohammed S. Almubarak, C. Tsingas
Geophysical Prospecting (2021) Vol. 69, Iss. 7, pp. 1473-1486
Closed Access | Times Cited: 9
De-noising receiver function data using the unsupervised deep learning approach
Bijayananda Dalai, Prakash Kumar, Uppala Srinu, et al.
Geophysical Journal International (2021) Vol. 229, Iss. 2, pp. 737-749
Closed Access | Times Cited: 9

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