Civil infrastructure (eg, buildings, roads, underground tunnels) could lose its expected
physical and functional conditions after years of operation. Timely and accurate inspection …

The prompt detection of early decay in the pavement could be an auspicious technique in
road maintenance. Admittedly, early crack detection allows preventive measures to be taken …

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 …

Annually, millions of dollars are spent to carry out defect detection in key infrastructure
including roads, bridges, and buildings. The aftermath of natural disasters like floods and …

Pavement management systems play a significant role in country's economy since road
authorities are concerned about preserving their priceless road assets for a longer time to …

With the advancement of machine learning (ML) and deep learning (DL), there is a great
opportunity to enhance the development of automatic crack detection algorithms. In this …

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

Deep learning‐based structural damage detection methods overcome the limitation of
inferior adaptability caused by extensively varying real‐world situations (eg, lighting and …

The CrackNet, an efficient architecture based on the Convolutional Neural Network (CNN),
is proposed in this article for automated pavement crack detection on 3D asphalt surfaces …

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