Automatically detecting surface defects from images is an essential capability in
manufacturing applications. Traditional image processing techniques are useful in solving a …

Quality inspection and defect detection remain critical challenges across diverse industrial
applications. Driven by advancements in Deep Learning, Convolutional Neural Networks …

Tiny defect detection (TDD) which aims to perform the quality control of printed circuit boards
(PCBs) is a basic and essential task in the production of most electronic products. Though …

Quality control is one of the industrial tasks most susceptible to be improved by
implementing technological innovations. As an innovative technology, machine vision …

Casting is the main backbone of the manufacturing industry in which liquefied metal is put
into the desired shape of mold for the resha** of metal. Hence, casting defect analysis is …

In recent years, with the rapid development of deep learning, computer vision technology
based on convolutional neural network (CNN) is widely used in industrial fields. At present …

As manifestations of Industry 4.0. become visible across various applications, one key and
opportune area of development are quality inspection processes and defect detection. Over …

Manual or traditional industrial product inspection and defect-recognition models have some
limitations, including process complexity, time-consuming, error-prone, and expensiveness …

At present, automobiles have become a common means of transportation, but with the
increase of vehicles, safety issues have gradually emerged. Therefore, the assembly …

Automated assessment of car damage is a major challenge in the auto repair and damage
assessment industries. The domain has several application areas, ranging from car …