Deep learning for automatic vision-based recognition of industrial surface defects: a survey
Automatic vision-based inspection systems have played a key role in product quality
assessment for decades through the segmentation, detection, and classification of defects …
assessment for decades through the segmentation, detection, and classification of defects …
A Systematic Literature Review on Artificial Intelligence and Explainable Artificial Intelligence for Visual Quality Assurance in Manufacturing
R Hoffmann, C Reich - Electronics, 2023 - mdpi.com
Quality assurance (QA) plays a crucial role in manufacturing to ensure that products meet
their specifications. However, manual QA processes are costly and time-consuming, thereby …
their specifications. However, manual QA processes are costly and time-consuming, thereby …
Intraclass image augmentation for defect detection using generative adversarial neural networks
Surface defect identification based on computer vision algorithms often leads to inadequate
generalization ability due to large intraclass variation. Diversity in lighting conditions, noise …
generalization ability due to large intraclass variation. Diversity in lighting conditions, noise …
Learning Representation for Multitask Learning Through Self-supervised Auxiliary Learning
Multi-task learning is a popular machine learning approach that enables simultaneous
learning of multiple related tasks, improving algorithmic efficiency and effectiveness. In the …
learning of multiple related tasks, improving algorithmic efficiency and effectiveness. In the …
A multi-task segmentation and classification network for remote ship hull inspection
B Lin, X Dong - Ocean Engineering, 2024 - Elsevier
In contrast to manual close-up ship hull inspection methods, Remote Inspection Technology
(RIT) offers the potential to improve performance while minimising costs. Nevertheless, the …
(RIT) offers the potential to improve performance while minimising costs. Nevertheless, the …
Depth feature fusion based surface defect region identification method for steel plate manufacturing
Computers and electrical engineering have made great strides in steel plate manufacturing.
Defect recognition techniques have also evolved. However, due to the large scale of defects …
Defect recognition techniques have also evolved. However, due to the large scale of defects …
An attention-augmented convolutional neural network with focal loss for mixed-type wafer defect classification
Silicon wafer defect classification is crucial for improving fabrication and chip production.
Although deep learning methods have been successful in single-defect wafer classification …
Although deep learning methods have been successful in single-defect wafer classification …
A Unet-inspired spatial-attention transformer model for segmenting gear tooth surface defects
X Zhou, Y Zhang, Z Ren, T Mi, Z Jiang, T Yu… - Advanced Engineering …, 2024 - Elsevier
Automated vision defect detection is a crucial step in monitoring product quality in industrial
production. Despite the widespread utilization of deep learning methods for surface defect …
production. Despite the widespread utilization of deep learning methods for surface defect …
Context-aware adaptive weighted attention network for real-time surface defect segmentation
Surface defect detection is an important step in ensuring product quality in various
manufacturing industries. Existing methods have achieved significant results, but there are …
manufacturing industries. Existing methods have achieved significant results, but there are …
[HTML][HTML] ODNet: A high real-time network using orthogonal decomposition for few-shot strip steel surface defect classification
Strip steel plays a crucial role in modern industrial production, where enhancing the
accuracy and real-time capabilities of surface defect classification is essential. However …
accuracy and real-time capabilities of surface defect classification is essential. However …