Abstract Industry 4.0 (I4. 0) is the fourth industrial revolution and a synonym for intelligent
manufacturing. It drives the convergence of several cutting-edge technologies to provoke …

Intelligent algorithms can empower the development of smart manufacturing, since they can
provide optimal solutions for detection, analysis, prediction and optimization. In recent ten …

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 …

This article presents the results of research with the main goal of identifying possible
applications of edge computing (EC) in industry. This study used the methodology of …

Automatic vision-based inspection systems have played a key role in product quality
assessment for decades through the segmentation, detection, and classification of defects …

With the grid-connected application of renewable energy sources such as wind and
photovoltaic power, the nonlinearity and fluctuation of load data makes load forecasting …

The use of the deep learning approach in the textile industry for the purpose of defect
detection has become an increasing trend in the past 20 years. The majority of publications …

In this article we present a model of new deep learning composition for remote ship
detection. Proposed architecture is composed of newly developed derivatives of ResNet …

Fabric defect detection plays an important role in quality control. The traditional manual
detection method is inefficient and costly, therefore many deep learning algorithms have …

The productivity of textile industry is positively correlated with the efficiency of fabric defect
detection. Traditional manual detection methods have gradually been replaced by deep …