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Dawei Liu
Dawei Liu
Purdue University
Verified email at stu.xjtu.edu.cn - Homepage
Title
Cited by
Cited by
Year
Poststack seismic data denoising based on 3-D convolutional neural network
D Liu, W Wang, X Wang, C Wang, J Pei, W Chen
IEEE Transactions on Geoscience and Remote Sensing 58 (3), 1598-1629, 2019
982019
Random noise suppression in seismic data: What can deep learning do?
D Liu, W Wang, W Chen, X Wang, Y Zhou, Z Shi
SEG International Exposition and Annual Meeting, SEG-2018-2998114, 2018
662018
An unsupervised deep learning method for denoising prestack random noise
D Liu, Z Deng, C Wang, X Wang, W Chen
IEEE Geoscience and Remote Sensing Letters 19, 1-5, 2020
382020
Efficient tensor completion methods for 5-D seismic data reconstruction: Low-rank tensor train and tensor ring
D Liu, MD Sacchi, W Chen
IEEE Transactions on Geoscience and Remote Sensing 60, 1-17, 2022
142022
Accelerating seismic scattered noise attenuation in offset-vector tile domain: Application of deep learning
D Liu, X Wang, X Yang, H Mao, MD Sacchi, W Chen
Geophysics 87 (5), V505-V519, 2022
112022
Should we have labels for deep learning ground roll attenuation?
D Liu, W Chen, MD Sacchi, H Wang
SEG Technical Program Expanded Abstracts 2020, 3239-3243, 2020
112020
Eliminating harmonic noise in vibroseis data through sparsity-promoted waveform modeling
D Liu, X Li, W Wang, X Wang, Z Shi, W Chen
Geophysics 87 (3), V183-V191, 2022
102022
A dictionary learning method with atom splitting for seismic footprint suppression
D Liu, L Gao, X Wang, W Chen
Geophysics 86 (6), V509-V523, 2021
102021
Random noise attenuation method for seismic data based on deep residual networks
F Zhang, D Liu, X Wang, W Chen, W Wang
International Geophysical Conference, Beijing, China, 24-27 April 2018, 1774 …, 2018
102018
Must we have labels for denoising seismic data based on deep learning?
D Liu*, Z Deng, X Wang, W Wang, Z Shi, C Wang, W Chen
SEG 2019 Workshop: Mathematical Geophysics: Traditional vs Learning, Beijing …, 2020
92020
Seismic intelligent deblending via plug and play method with blended CSGs trained deep CNN Gaussian denoiser
W Xu, Y Zhou, D Liu, X Wang, W Chen
IEEE Transactions on Geoscience and Remote Sensing 60, 1-13, 2022
62022
A convolutional neural network for seismic dip estimation
D Liu, X Wang, Z Shi, Y Zhou, W Chen
SEG Technical Program Expanded Abstracts 2019, 2634-2638, 2019
62019
Unsupervised deep learning for ground roll and scattered noise attenuation
D Liu, MD Sacchi, X Wang, W Chen
IEEE Transactions on Geoscience and Remote Sensing, 2023
52023
Attenuation of the multiple reflection-refraction in 2-d common-shot gather via random-derangement-based fx cadzow filter
Y Hu, D Liu, X Wang, Z Zhao, W Chen
IEEE Geoscience and Remote Sensing Letters 19, 1-5, 2021
52021
Unsupervised noise suppression method for depth network seismic data based on prior information constraint
C Wenchao, LIU Dawei, WEI Xinjian, W Xiaokai, C Dewu, LI Shuping, ...
Coal Geology & Exploration 49 (1), 28, 2021
52021
Improving sparse representation with deep learning: A workflow for separating strong background interference
D Liu, W Wang, X Wang, Z Shi, MD Sacchi, W Chen
Geophysics 88 (1), WA253-WA266, 2023
42023
基于地震资料有效信息约束的深度网络无监督噪声压制方法
陈文超, 刘达伟, 魏新建, 王晓凯, 陈德武, 李书平, 李冬
煤田地质与勘探 49 (1), 249-256, 2021
42021
3D seismic waveform of channels extraction by artificial intelligence
D Liu, X Wang, W Chen, Y Zhou, W Wang, Z Shi, C Wang, C Xie
SEG International Exposition and Annual Meeting, D033S077R003, 2019
42019
Improving vertical resolution of vintage seismic data by a weakly supervised method based on cycle generative adversarial network
D Liu, W Niu, X Wang, MD Sacchi, W Chen, C Wang
Geophysics 88 (6), V445-V458, 2023
32023
Accelerating seismic dip estimation with deep learning
X Wang, D Liu, W Chen
IEEE Geoscience and Remote Sensing Letters 19, 1-5, 2021
32021
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