Computer vision for SHM of civil infrastructure: From dynamic response measurement to damage detection – A review

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Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights (2021, methodology): “This is exhaustively covered in numerous review papers, 25,26,32 – 35 , 41 as indicated Sequential data or time series is a major part of many SHM systems.”
A systematic review of convolutional neural network-based structural condition assessment techniques (2021, background): “Preliminaries of Deep Learning Methods 168 Non-contact sensing techniques (Sony et al. 2019; Dabous and Feroz 2020) and computer vision 169 (Feng and Feng 2018; Spencer et al. 2019; Dick et al. 2019) have opened up a new era of next-170 generation autonomous SHM and inspection of large-scale…”
Advances in Computer Vision-Based Civil Infrastructure Inspection and Monitoring (2019, methodology): “For further information, recent reviews of dynamic monitoring applications using computer vision techniques have been provided by Ye et al. [199] and Feng and Feng [200].”
A review of computer vision–based structural health monitoring at local and global levels (2020, methodology): “Bhattacharjee and Deb85 detected and classified the cracked zones by using the displacement field obtained from DIC.”