The detection of product defects is essential in quality control in manufacturing. This study
surveys stateoftheart deep-learning methods in defect detection. First, we classify the defects …

Due to the advances in the digitalization process of the manufacturing industry and the
resulting available data, there is tremendous progress and large interest in integrating …

Surface defect detection is very important to guarantee the quality of ceramic tiles
production. At present, this process is usually performed manually in the ceramic tile …

Ceramic tiles are widely used in the construction field. In actual production, the difficulty in
extracting texture ceramic tile features and the small size of defects lead to low detection …

Automatic defect detection on the steel surface is a challenging task in computer vision,
owing to miscellaneous patterns of the defects, low contrast between the defect and …

Defect detection and classification of ceramic tile surface defects occurred in firing units are
usually performed by human observations in most factories. In this paper, an automatic …

Purpose The purpose of this paper is to focus on the design and development of computer-
aided fabric defect detection and classification employing advanced learning algorithm …

Titanium-coated surfaces are prone to tiny defects such as very small cracks, which are not
easily observable by the naked eye or optical microscopy. In this study, two new …

The vial, a bottle known to store the drug, should be controlled to meet the requirements of
the standard dimension. Due to problems with a visual inspection, there is a need to develop …

Automatic strip steel surface defect detection is a difficult mission, as a result of the
imbalanced class distributions caused by the sparse distribution of abnormal samples. The …