Currently, deep learning-based visual inspection has been highly successful with the help of
supervised learning methods. However, in real industrial scenarios, the scarcity of defect …

Cracks undermine the structural health of transportation infrastructure. Machine vision-
based surface crack analysis is to process infrastructure inspection data collected by …

Objective. Computer vision-based up-to-date accurate damage classification and
localization are of decisive importance for infrastructure monitoring, safety, and the …

Anomaly detection in computer vision is the task of identifying images which deviate from a
set of normal images. A common approach is to train deep convolutional autoencoders to …

The proliferation of the e-commerce market has posed challenges to staff safety, product
quality, and operational efficiency, especially for cold chain logistics (CCL). Recently, the …

In the past years, the computer vision domain has been profoundly changed by the advent of
deep learning algorithms and data science. The defect detection problem is of outmost …

Due to the impact of the surrounding environment changes, train-induced vibration, and
human interference, damage to metro tunnel surfaces frequently occurs. Therefore …

Scanning electron microscopy (SEM) images are used to evaluate the microstructure of the
concrete, there still remains challenges as the current methods are semi-automated, non …

Ensuring product quality and integrity is paramount in the rapidly evolving landscape of
industrial manufacturing. Although effective to a certain degree, traditional quality control …

Image anomaly detection problems aim to determine whether an image is abnormal, and to
detect anomalous areas. These methods are actively used in various fields such as …