Artificial neural networks and their application in damage detection of masonry structures

Abstract

In order to ensure the durability of masonry structures, prevent their deterioration and serious damage, it is necessary to carry out regular inspections of the condition of building elements. Determining the condition of masonry structures is most often done manually, by visual inspection, which is a time-consuming process, the quality of which largely depends on subjective feeling. As there is an increasing need for automated data processing and work processes today, in recent years there has been an increasing application of artificial intelligence in the process of segmentation and damage detection in masonry structures using Artificial Neural Networks (ANNs). The aim of this paper is to carry out a detailed analysis of the application of artificial intelligence in the segmentation of masonry elements and the detection of damage to masonry structures through a review and analysis of papers published in the literature.