Automated computer-vision-based defect detection has received much attention with the
increasing surface quality assurance demands for the industrial manufacturing of flat steels …

The computer-vision-based surface defect detection of metal planar materials is a research
hotspot in the field of metallurgical industry. The high standard of planar surface quality in …

Quality control is a fundamental component of many manufacturing processes, especially
those involving casting or welding. However, manual quality control procedures are often …

Automatic recognition method for hot-rolled steel strip surface defects is important to the
steel surface inspection system. In order to improve the recognition rate, a new, simple, yet …

Automatic localization of defects in metal castings is a challenging task, owing to the rare
occurrence and variation in appearance of defects. Convolutional neural networks (CNN) …

For a typical surface automated visual inspection (AVI) instrument of planar materials, defect
classification is an indispensable part after defect detection, which acts as a crucial …

Automatic defect detection on hot-rolled steel surface is challenging owing to its localization
on a large surface, variation in appearance, and their rare occurrences. It is difficult to detect …

A convolutional neural network (CNN) is proposed to learn multiple useful feature
representations for a classification from low level (raw pixels) to high level (object) …

For defect detection in nonperiodical pattern images, such as printed circuit boards or
integrated circuit dies found in the electronic industry, template matching could be the only …

Quality management is a fundamental component of a manufacturing process. In this paper,
we propose a promising learning-based approach for automatic defect detection based on …