Detection of the low-velocity layer using a convolutional neural network on passive surface-wave data: An application in Hangzhou, China-Reference-Cited by-同舟云学术

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Detection of the low-velocity layer using a convolutional neural network on passive surface-wave data: An application in Hangzhou, China

Published:2024-08 Issue: Volume:190 Page:105663
ISSN:0098-3004
Container-title:Computers & Geosciences
language:en
Short-container-title:Computers & Geosciences

Author:

Chen Xinhua,Xia Jianghai^ORCID,Pang Jingyin,Zhou Changjiang

Publisher

Elsevier BV

Reference42 articles.

1. Space and time spectra of stationary stochastic waves, with special reference to micro-tremors;Aki;Bull. Earthq. Res. Inst.,1957

2. Magnetic anomalies characterization: deep learning and explainability;Cárdenas;Comput. Geosci.,2022

3. Semi-supervised surface wave tomography with wasserstein cycle-consistent GAN: method and application to southern California plate boundary region;Cai;J. Geophys. Res. Solid Earth,2022

4. Ambient noise tomography of the Lipari volcanic island (Southern Italy) from a dense nodal array;Calò;Geophys. Res. Lett.,2023

5. Using ambient noise tomography and MAPS for high resolution stratigraphic identification in Hangzhou urban area;Chen;J. Appl. Geophys.,2021

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