On the Variants of SVM Methods Applied to GPR Data to Classify Tack Coat Characteristics in French Pavements: Two Experimental Case Studies-Reference-Cited by-同舟云学术

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On the Variants of SVM Methods Applied to GPR Data to Classify Tack Coat Characteristics in French Pavements: Two Experimental Case Studies

Published:2023-07-05 Issue: Volume: Page:
ISSN:
Container-title:2023 12th International Workshop on Advanced Ground Penetrating Radar (IWAGPR)
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Author:

Andreoli Grégory¹,Ihamouten Amine²,Nguyen Mai Lan²,Fargier Yannick³,Fauchard Cyrille⁴,Simonin Jean-Michel²,Buliuk Viktoriia⁵,Souriou David⁶,Dérobert Xavier⁵

Affiliation:

1. AAn/ENDSUM, Angers Cerema,France

2. Nantes Gustave Eiffel University,MAST/LAMES,France

3. Bron Gustave Eiffel University,GERS/RRO,France

4. Rouen Cerema,DGI/ENDSUM,France

5. Nantes Gustave Eiffel University,GERS/GeoEND,France

6. Nantes - FI-NDT Gustave Eiffel University,MAST/LAMES,France

Funder

French National Research Agency

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10328967/10328962/10329070.pdf?arnumber=10329070

Reference6 articles.

1. Modelling ground penetrating radar by GprMax

2. Performance assessment of SVM-based classification techniques for the detection of artificial debondings within pavement structures from stepped-frequency A-scan radar data;todkar;NDT & E International,2009

3. The use of machine learning method to classify electromagnetic characteristics of pavement tack coat

4. Numerical parametric study to classify and estimate pavement characteristics using GPR and machine learning methods;andreoli;1st Data Science and Pavement Symposium,0

5. Time Delay and Permittivity Estimation by Ground-Penetrating Radar With Support Vector Regression

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