Highly sensitive terahertz non‐destructive testing technology for stone relics deterioration prediction using SVM-based machine learning models

Highly sensitive terahertz non‐destructive testing technology for stone relics deterioration prediction using SVM-based machine learning models

Abstract The hollowing deterioration of stone relics required effective non-destructive testing (NDT) methods for their timely restoration and maintenance. To this end, a new NDT method based on terahertz (THz) technology by using support vector machine (SVM)-based machine learning models was develo...

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Bibliographic Details
Main Authors: Tianhua Meng, Rong Huang, Yuhe Lu, Hongmei Liu, Jianguang Ren, Guozhong Zhao, Weidong Hu
Format: Article
Language:English
Published: SpringerOpen 2021-02-01
Series:Heritage Science
Subjects:
Stone cultural relics
Yungang Grottoes
Terahertz spectral
LS-SVM
Linear kernel function
Online Access:https://doi.org/10.1186/s40494-021-00502-7

Internet

https://doi.org/10.1186/s40494-021-00502-7

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