[HTML][HTML] Artificial intelligence and smart vision for building and construction 4.0: Machine and deep learning methods and applications

SK Baduge, S Thilakarathna, JS Perera… - Automation in …, 2022 - Elsevier
This article presents a state-of-the-art review of the applications of Artificial Intelligence (AI),
Machine Learning (ML), and Deep Learning (DL) in building and construction industry 4.0 in …

Review on the new development of vibration-based damage identification for civil engineering structures: 2010–2019

R Hou, Y Xia - Journal of Sound and Vibration, 2021 - Elsevier
Structural damage identification has received considerable attention during the past
decades. Although several reviews have been presented, some new developments have …

Self-supervised learning for electroencephalography

MH Rafiei, LV Gauthier, H Adeli… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Decades of research have shown machine learning superiority in discovering highly
nonlinear patterns embedded in electroencephalography (EEG) records compared with …

[HTML][HTML] Deep learning in the construction industry: A review of present status and future innovations

TD Akinosho, LO Oyedele, M Bilal, AO Ajayi… - Journal of Building …, 2020 - Elsevier
The construction industry is known to be overwhelmed with resource planning, risk
management and logistic challenges which often result in design defects, project delivery …

Review of bridge structural health monitoring aided by big data and artificial intelligence: From condition assessment to damage detection

L Sun, Z Shang, Y Xia, S Bhowmick… - Journal of Structural …, 2020 - ascelibrary.org
Structural health monitoring (SHM) techniques have been widely used in long-span bridges.
However, due to limitations of computational ability and data analysis methods, the …

Machine learning algorithms in civil structural health monitoring: A systematic review

M Flah, I Nunez, W Ben Chaabene… - Archives of computational …, 2021 - Springer
Abstract Applications of Machine Learning (ML) algorithms in Structural Health Monitoring
(SHM) have become of great interest in recent years owing to their superior ability to detect …

Integrated structural health monitoring in bridge engineering

Z He, W Li, H Salehi, H Zhang, H Zhou, P Jiao - Automation in construction, 2022 - Elsevier
Integrated structural health monitoring (SHM) uses the mechanism analysis, monitoring
technology and data analytics to diagnose the classification, location and significance of …

Efficient training of physics‐informed neural networks via importance sampling

MA Nabian, RJ Gladstone… - Computer‐Aided Civil and …, 2021 - Wiley Online Library
Physics‐informed neural networks (PINNs) are a class of deep neural networks that are
trained, using automatic differentiation, to compute the response of systems governed by …

Unsupervised deep learning approach using a deep auto-encoder with a one-class support vector machine to detect damage

Z Wang, YJ Cha - Structural Health Monitoring, 2021 - journals.sagepub.com
This article proposes an unsupervised deep learning–based approach to detect structural
damage. Supervised deep learning methods have been proposed in recent years, but they …

Road damage detection and classification using deep neural networks with smartphone images

H Maeda, Y Sekimoto, T Seto… - … ‐Aided Civil and …, 2018 - Wiley Online Library
Research on damage detection of road surfaces using image processing techniques has
been actively conducted. This study makes three contributions to address road damage …