To ensure the safety and the serviceability of civil infrastructure it is essential to visually
inspect and assess its physical and functional condition. This review paper presents the …

This survey presents an in-depth overview of the last 25 years of research within the field of
image-based automation of Closed-Circuit Television (CCTV) and Sewer Scanner and …

This paper proposes a customized convolutional neural network for crack detection in
concrete structures. The proposed method is compared to four existing deep learning …

Clients are increasingly looking for fast and effective means to quickly and frequently survey
and communicate the condition of their buildings so that essential repairs and maintenance …

The municipal drainage system is a key component of every modern city's infrastructure.
However, as the drainage system ages its pipes gradually deteriorate at rates that vary …

Crack detection has vital importance for structural health monitoring and inspection of
buildings. The task is challenging for computer vision methods as cracks have only low-level …

Cracks are an important indicator reflecting the safety status of infrastructures. This paper
presents an automatic crack detection and classification methodology for subway tunnel …

Surveys for assessing the condition of sewer pipeline systems are mainly based on video
surveillance or CCTV, which is a time-consuming process that relies heavily on human labor …

Conventional deep-learning-based inspection methods for sewer pipeline defects neglect
the complex inner environment of pipelines (eg, fog and motion blur) and real-time …

Neuro-fuzzy systems (NFS) can explicitly represent and model the input–output
relationships of complex problems and non-linear systems, like those inherent in real-world …