U-Net with Asymmetric Convolution Blocks for Road Traffic Noise Attenuation in Seismic Data
Author:
Affiliation:
1. Hainan Institute of Zhejiang University, Sanya 572024, China
2. School of Geosciences, China University of Petroleum (East China), Qingdao 266580, China
3. Advanced Technology Institute of Zhejiang University, Hangzhou 310027, China
Abstract
Funder
Hainan Provincial Natural Science Foundation of China
Hainan Provincial Joint Project of Sanya Yazhou Bay Science and Technology City
Hainan institute Foundation of Zhejiang University
Publisher
MDPI AG
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Link
https://www.mdpi.com/2076-3417/13/8/4751/pdf
Reference39 articles.
1. Seismic random noise suppression by using deep residual U-Net;Zhong;J. Pet. Sci. Eng.,2022
2. Seismic signal denoising and decomposition using deep neural networks;Zhu;IEEE Trans. Geosci. Remote Sens.,2019
3. Chirtu, M.A., and Radoi, A. (2022, January 13–15). Seismic Signal Denoising using U-Net in the Time-Frequency Domain. Proceedings of the 45th IEEE International Conference on Telecommunications and Signal Processing (TSP), Prague, Czech Republic.
4. Sun, L., Qiu, X., Wang, Y., and Wang, C. (2023). Seismic Periodic Noise Attenuation Based on Sparse Representation Using a Noise Dictionary. Appl. Sci., 13.
5. Guo, J., and Lin, D. (2003). SEG Technical Program Expanded Abstracts 2003, Society of Exploration Geophysicists.
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