Abstract Convolutional Neural Networks (CNN) have immense potential to solve a broad
range of computer vision problems. It has achieved encouraging results in numerous …

With recent advances in non-contact sensing technology such as cameras, unmanned aerial
and ground vehicles, the structural health monitoring (SHM) community has witnessed a …

This paper aims to improve automation in brick segmentation and crack detection of
masonry walls through image-based techniques and machine learning. Initially, a large …

Alcoholism changes the structure of brain. Several somatic marker hypothesis network-
related regions are known to be damaged in chronic alcoholism. Neuroimaging approach …

Masonry structures dominate cultural heritage sites worldwide. Public authorities ought to
preserve and safeguard such structures for future generations. However, precise evaluation …

The automated interpretation of rock structure can improve the efficiency, accuracy, and
consistency of the geological risk assessment of tunnel face. Because of the high …

In recent years deep-learning techniques have been developed and applied to inspect
cracks in RC structures. The accuracy of these techniques leads to believe that they may …

In order to solve the damage caused by the concrete structure, which leads to the reduction
of the life of infrastructure, endangers the safety of pedestrians, and has a serious impact on …

The historical buildings of a nation are the tangible signs of its history and culture. Their
preservation deserves considerable attention, being of primary importance from a historical …

Bridge crack detection is essential to ensure bridge safety. The introduction of deep learning
technology has made it possible to detect bridge cracks automatically and accurately. In this …