The maintenance and lifespan of structures made of concrete depend on the early detection
and timely treatment of cracks, which can compromise the building's strength and need …

Crack formation is one of the first indicators of degradation of the concrete structure.
Therefore, they must be detected early to take the necessary precautions to avoid further …

Manual inspection of cracks on concrete surfaces requires wholesome knowledge and
depends entirely on the expertise and capabilities of the inspector. This study proposes the …

Effective crack detection is pivotal for the structural health monitoring and inspection of
buildings. This task presents a formidable challenge to computer vision techniques due to …

The objective of the study is to automate the Structural Health Monitoring and site inspection
work by developing and modeling an Artificial Neural Network with Convolutional Neural …

Convolutional Neural Networks are among the most effective algorithms for image analysis
applications. However, the accuracy of the algorithms depends on the availability of …

This paper examines the most common structural defect in concrete is surface cracking.
Building inspections are carried out to assess the stiffness and tensile strength of a building …

This study presents a CNN-based model for detecting cracks in concrete images. Even
though the model is simple and has only a few layers, it provides significant accuracy. This …

Cracking in concrete structures affects performance and is a major durability problem.
Cracks must be detected and repaired in time in order to maintain the reliability and …

This work aims at developing a machine learning-based model to detect cracks on concrete
surfaces. Such model is intended to increase the level of automation on concrete …