BIM has been playing a pivotal role during the last decade in bringing in revolutionary and
systematic changes, especially for the design and construction stages in bridge engineering; …

Computer vision-based crack analysis for civil infrastructure has become popular to
automatically process inspection imaging data for crack detection, localisation and …

The challenge of the research work presented in the paper is to combine the growing
interest in monitoring the health condition of existing bridge heritage through systematic and …

The spatial characteristics of cracks are significant indicators to assess and evaluate the
health of existing buildings and infrastructures. However, the current manual crack …

Computer‐vision and deep‐learning techniques are being increasingly applied to inspect,
monitor, and assess infrastructure conditions including detection of cracks. Traditional vision …

The current bridge maintenance practice generally involves manual visual inspection, which
is highly subjective and unreliable. A technique that can automatically detect defects, for …

The application of deep architectures inspired by the fields of artificial intelligence and
computer vision has made a significant impact on the task of crack detection. As the number …

Fully convolutional network is a powerful tool for per-pixel semantic segmentation/detection.
However, it is problematic when coping with crack detection using partially accurate ground …

The non-destructive evaluation (NDE) of civil infrastructure has been an active area of
research in recent decades. The traditional inspection of civil infrastructure mostly relies on …

The detection of cracks in concrete structures is a pivotal aspect in assessing structural
robustness. Current inspection methods are subjective, relying on the inspector's experience …