Steel surface defect recognition is an important part of industrial product surface defect
detection, which has attracted more and more attention in recent years. In the development …

Retired electric-vehicle lithium-ion battery (EV-LIB) packs pose severe environmental
hazards. Efficient recovery of these spent batteries is a significant way to achieve closed …

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 …

Deep learning-based algorithms have been widely employed to build reliable steel surface
defect detection systems, which are important for manufacturing. The performance of deep …

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 …

Unsupervised anomaly detection in real industrial scenarios is challenging since the small
amount of defect-free images contain limited discriminative information, and anomaly …

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 …

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 …

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 …