Classification of Teleseismic Shear Wave Splitting Measurements: A Convolutional Neural Network Approach
Abstract Shear wave splitting (SWS) analysis is widely used to provide critical constraints on crustal and mantle structure and dynamic models. In order to obtain reliable splitting measurements, an essential step is to visually verify all the measurements to reject problematic measurements, a task...
Saved in:
Main Authors: | Yanwei Zhang, Stephen S. Gao |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2022-06-01
|
Series: | Geophysical Research Letters |
Subjects: | |
Online Access: | https://doi.org/10.1029/2021GL097101 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Neural network based classification of rock properties and seismic vulnerability
by: U. Muksin, et al.
Published: (2023-10-01) -
The Application of Three-dimensional Shear Wave Elastography in the Detection of Inguinal Lymph Node Metastasis in Gynecological Malignancies
by: Yuping Shen, et al.
Published: (2025-01-01) -
Classification of Invoice Images By Using Convolutional Neural Networks
by: Sait Ali Uymaz, et al.
Published: (2022-03-01) -
Shear Wave Velocity Prediction with Hyperparameter Optimization
by: Gebrail Bekdaş, et al.
Published: (2025-01-01) -
Detection of seismic anisotropy and azimuthally varying resonances from seismic data recorded at the Noto Peninsula using seismic interferometry and empirical mode decomposition
by: Andrés Pech-Pérez
Published: (2025-12-01)