This paper reviews recent developments in deep learning-based crack segmentation
methods and investigates their performance under the impact from different image types …

Deep learning breakthrough stimulates new research trends in civil infrastructure inspection,
whereas the lack of quality-guaranteed, human-annotated, free-of-charge, and publicly …

Applying computer science techniques such as artificial intelligence (AI), deep learning (DL),
and computer vision (CV) on digital image data can help monitor and preserve cultural …

While there have been a considerable number of studies on computer vision (CV)-based
crack detection on concrete/asphalt public facilities, such as sewers and tunnels, masonry …

The generation of numerical models for masonry structures is a timely and costly procedure
since it requires the discretization of a large quantity of smaller particles. Similarly, traditional …

Structural cracks have serious repercussions on the safety, adaptability, and longevity of
structures. Therefore, assessing cracks is an important parameter when evaluating the …

In recent years, visual automatic non-destructive testing using machine vision algorithms
has been widely used in industry. This approach for detecting, classifying, and segmenting …

The integration of visible and thermal images has demonstrated the potential ability to
enhance crack segmentation accuracy. However, due to the intricate texture of masonry …

This study presents an innovative method for precise measurement and mapping of width
nephograms for blurred cracks on concrete dams. An intelligent segmentation network …

The cable system is a critical load-bearing member and a vital factor of cable-stayed
bridges; its health condition indicates the operation safety of these structures. The cable …