Deep learning for automatic vision-based recognition of industrial surface defects: a survey

M Prunella, RM Scardigno, D Buongiorno… - IEEE …, 2023 - ieeexplore.ieee.org
Automatic vision-based inspection systems have played a key role in product quality
assessment for decades through the segmentation, detection, and classification of defects …

MSC-DNet: An efficient detector with multi-scale context for defect detection on strip steel surface

R Liu, M Huang, Z Gao, Z Cao, P Cao - Measurement, 2023 - Elsevier
The strip steel has been widely used in the manufacturing industry. Defects on the surface
are main factors to determine the quality of strip steel. Due to the various shapes of the …

ES-Net: Efficient scale-aware network for tiny defect detection

X Yu, W Lyu, D Zhou, C Wang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Defect detection is to locate and classify the possible defects in an image, which plays a key
role in the quality inspection link in the manufacturing process of industrial products. Defects …

A survey of real-time surface defect inspection methods based on deep learning

Y Liu, C Zhang, X Dong - Artificial Intelligence Review, 2023 - Springer
In recent years, deep learning methods have been widely used in various industrial
scenarios, promoting industrial intelligence. Real-time surface defect inspection of industrial …

Yolo-former: Marrying yolo and transformer for foreign object detection

Y Dai, W Liu, H Wang, W Xie… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The automatic detection of foreign objects between platform screen doors (PSDs) and metro
train doors significantly affects personnel and property safety and maintains the train's …

The devil is in the crack orientation: A new perspective for crack detection

Z Chen, J Zhang, Z Lai, G Zhu, Z Liu… - Proceedings of the …, 2023 - openaccess.thecvf.com
Cracks are usually curve-like structures that are the focus of many computer-vision
applications (eg, road safety inspection and surface inspection of industrial facilities). The …

A new foreground-perception cycle-consistent adversarial network for surface defect detection with limited high-noise samples

Y Wang, W Hu, L Wen, L Gao - IEEE Transactions on Industrial …, 2023 - ieeexplore.ieee.org
Surface defect detection (SDD) is critical in the smart manufacturing systems to ensure
product quality. Nevertheless, the defective samples are always insufficient, and there exists …

Etdnet: efficient transformer-based detection network for surface defect detection

H Zhou, R Yang, R Hu, C Shu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Deep learning (DL)-based surface defect detectors play a crucial role in ensuring product
quality during inspection processes. However, accurately and efficiently detecting defects …

Online visual end-to-end detection monitoring on surface defect of aluminum strip under the industrial few-shot condition

Z Ma, Y Li, M Huang, N Deng - Journal of Manufacturing Systems, 2023 - Elsevier
Surface defect detection systems based on deep learning are employed in the
manufacturing system, and their good detection performance largely relies on abundant …

Metal surface defect detection based on improved YOLOv5

C Zhou, Z Lu, Z Lv, M Meng, Y Tan, K Xia, K Liu… - Scientific Reports, 2023 - nature.com
During the production of metal material, various complex defects may come into being on
the surface, together with large amount of background texture information, causing false or …