A review of computer vision–based structural health monitoring at local and global levels
Structural health monitoring at local and global levels using computer vision technologies
has gained much attention in the structural health monitoring community in research and …
has gained much attention in the structural health monitoring community in research and …
Machine learning in materials science
Traditional methods of discovering new materials, such as the empirical trial and error
method and the density functional theory (DFT)‐based method, are unable to keep pace …
method and the density functional theory (DFT)‐based method, are unable to keep pace …
Data-driven structural health monitoring and damage detection through deep learning: State-of-the-art review
Data-driven methods in structural health monitoring (SHM) is gaining popularity due to
recent technological advancements in sensors, as well as high-speed internet and cloud …
recent technological advancements in sensors, as well as high-speed internet and cloud …
State-of-the-art review on advancements of data mining in structural health monitoring
To date, data mining (DM) techniques, ie artificial intelligence, machine learning, and
statistical methods have been utilized in a remarkable number of structural health monitoring …
statistical methods have been utilized in a remarkable number of structural health monitoring …
Machine learning paradigm for structural health monitoring
Structural health diagnosis and prognosis is the goal of structural health monitoring.
Vibration-based structural health monitoring methodology has been extensively …
Vibration-based structural health monitoring methodology has been extensively …
Recent advancements in non-destructive testing techniques for structural health monitoring
Structural health monitoring (SHM) is an important aspect of the assessment of various
structures and infrastructure, which involves inspection, monitoring, and maintenance to …
structures and infrastructure, which involves inspection, monitoring, and maintenance to …
Infrared machine vision and infrared thermography with deep learning: A review
Infrared imaging-based machine vision (IRMV) is the technology used to automatically
inspect, detect, and analyse infrared images (or videos) obtained by recording the intensity …
inspect, detect, and analyse infrared images (or videos) obtained by recording the intensity …
Crack detection of concrete structures using deep convolutional neural networks optimized by enhanced chicken swarm algorithm
With the rapid increase of ageing infrastructures worldwide, effective and robust inspection
techniques are highly demanding to evaluate structural conditions and residual lifetime. The …
techniques are highly demanding to evaluate structural conditions and residual lifetime. The …
Predictive modeling of mechanical properties of silica fume-based green concrete using artificial intelligence approaches: MLPNN, ANFIS, and GEP
Silica fume (SF) is a mineral additive that is widely used in the construction industry when
producing sustainable concrete. The integration of SF in concrete as a partial replacement …
producing sustainable concrete. The integration of SF in concrete as a partial replacement …
Automatic concrete crack segmentation model based on transformer
W Wang, C Su - Automation in Construction, 2022 - Elsevier
Routine visual inspection of concrete structures is essential to maintain safe conditions.
Therefore, studies of concrete crack segmentation using deep learning methods have been …
Therefore, studies of concrete crack segmentation using deep learning methods have been …