In the era of the Internet of Things (IoT), an enormous amount of sensing devices collect
and/or generate various sensory data over time for a wide range of fields and applications …

Deep learning, more specifically deep convolutional neural networks, is fast becoming a
popular choice for computer vision-based automated pavement distress detection. While …

For the first time, U-Net is adopted to detect the concrete cracks in the present study. Focal
loss function is selected as the evaluation function, and the Adam algorithm is applied for …

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

Research on damage detection of road surfaces using image processing techniques has
been actively conducted. This study makes three contributions to address road damage …

Abstract Machine learning can produce promising results when sufficient training data are
available; however, infrastructure inspections typically do not provide sufficient training data …

Research on damage detection of road surfaces using image processing techniques has
been actively conducted, achieving considerably high detection accuracies. Many studies …

In recent years, applying deep learning (DL) to assess structural damages has gained
growing popularity in vision‐based structural health monitoring (SHM). However, both data …

Modern smartphones are equipped with various sensors along with on-board storage,
computing and communication capabilities. Owing to these features, they can become an …

Deep learning (DL) has demonstrated great performance in various applications on
powerful computers and servers. Recently, with the advancement of more powerful mobile …