Dynamics‐based cross‐domain structural damage detection through deep transfer learning-Reference-Cited by-同舟云学术

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Dynamics‐based cross‐domain structural damage detection through deep transfer learning

Published:2021-05-07 Issue:1 Volume:37 Page:24-54
ISSN:1093-9687
Container-title:Computer-Aided Civil and Infrastructure Engineering
language:en
Short-container-title:Computer aided Civil Eng

Author:

Lin Yi‐zhou¹^ORCID,Nie Zhen‐hua²³^ORCID,Ma Hong‐wei¹⁴^ORCID

Affiliation:

1. School of Environment and Civil Engineering Dongguan University of Technology Dongguan China

2. School of Mechanics and Construction Engineering Jinan University Guangzhou China

3. Key Lab of Disaster Forecast and Control in Engineering Ministry of Education Guangzhou China

4. Department of Civil Engineering Qinghai University Xining China

Publisher

Wiley

Subject

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

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/mice.12692

Reference76 articles.

1. A dynamic ensemble learning algorithm for neural networks

2. Synchrosqueezed wavelet transform-fractality model for locating, detecting, and quantifying damage in smart highrise building structures

3. A machine learning approach based on multifractal features for crack assessment of reinforced concrete shells

4. Intelligent ball screw fault diagnosis using a deep domain adaptation methodology

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1. Structural damage identification based on Wasserstein Generative Adversarial Network with gradient penalty and dynamic adversarial adaptation network;Mechanical Systems and Signal Processing;2024-12

2. Automated ultrasonic-based diagnosis of concrete compressive damage amidst temperature variations utilizing deep learning;Mechanical Systems and Signal Processing;2024-12

3. Cross-domain damage identification based on conditional adversarial domain adaptation;Engineering Structures;2024-12

4. Bridge damage location and quantification under the moving vehicle loads based on deep learning multi-objective regression;Engineering Structures;2024-12

5. Image hashing-based shallow object tracker for construction worker monitoring in scaffolding scenes;Automation in Construction;2024-10

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