A scalable, self‐supervised calibration and confounder removal model for opportunistic monitoring of road degradation-Reference-Cited by-同舟云学术

A scalable, self‐supervised calibration and confounder removal model for opportunistic monitoring of road degradation

Published:2022-02-16 Issue:13 Volume:37 Page:1703-1720
ISSN:1093-9687
Container-title:Computer-Aided Civil and Infrastructure Engineering
language:en
Short-container-title:Computer aided Civil Eng

Author:

Van Hauwermeiren Wout¹^ORCID,Filipan Karlo²³^ORCID,Botteldooren Dick¹^ORCID,De Coensel Bert¹²^ORCID

Affiliation:

1. WAVES Ghent University Ghent Belgium

2. Roads ASAsense BV Brugge Belgium

3. Acoustics Lab Catholic University of Croatia Zagreb Croatia

Funder

Fonds Wetenschappelijk Onderzoek

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Graphics and Computer-Aided Design,Computer Science Applications,Civil and Structural Engineering,Building and Construction

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/mice.12821

Reference49 articles.

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2. A dynamic ensemble learning algorithm for neural networks

3. Wavelet Filter Design for Pavement Roughness Analysis

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