Deep learning-based welding image recognition: A comprehensive review
The reliability and accuracy of welding image recognition (WIR) is critical, which can largely
improve domain experts' insight of the welding system. To ensure its performance, deep …
improve domain experts' insight of the welding system. To ensure its performance, deep …
A state-of-the-art survey of welding radiographic image analysis: challenges, technologies and applications
Welding radiographic image analysis (WRIA) is a key technology for welding automated non-
destructive testing. Although there already exist some valuable surveys on WRIA, they do …
destructive testing. Although there already exist some valuable surveys on WRIA, they do …
Defect-aware transformer network for intelligent visual surface defect detection
Surface defect detection plays an increasing role in intelligent manufacturing and product
life-cycle management, such as quality inspection, process monitoring, and preventive …
life-cycle management, such as quality inspection, process monitoring, and preventive …
Automated categorization of multiclass welding defects using the x-ray image augmentation and convolutional neural network
The detection of weld defects by using X-rays is an important task in the industry. It requires
trained specialists with the expertise to conduct a timely inspection, which is costly and …
trained specialists with the expertise to conduct a timely inspection, which is costly and …
An expert knowledge-empowered CNN approach for welding radiographic image recognition
Non-destructive testing of welds based on the radiographic image is crucial for improving
the reliability of aerospace structural components. The deep learning method represented …
the reliability of aerospace structural components. The deep learning method represented …
Welding defects classification through a Convolutional Neural Network
This letter presents a Convolutional Neural Network (CNN), named WelDeNet, customized
to classify welding defects, such as lack of penetration (LP), cracks (CR), porosity (PO) and …
to classify welding defects, such as lack of penetration (LP), cracks (CR), porosity (PO) and …
[HTML][HTML] Review on machine learning based welding quality improvement
Artificial intelligence technology is rapidly developing with the improvement of computer
performance and the development of various algorithms, and research using artificial …
performance and the development of various algorithms, and research using artificial …
Deep learning enriched automation in damage detection for sustainable operation in pipelines with welding defects under varying embedment conditions
Welded joints in metallic pipelines and other structures are used to connect metallic
structures. Welding defects, such as cracks and lack of fusion, are vulnerable to initiating …
structures. Welding defects, such as cracks and lack of fusion, are vulnerable to initiating …
Deep learning-based weld defect classification using VGG16 transfer learning adaptive fine-tuning
S Kumaresan, KSJ Aultrin, SS Kumar… - International Journal on …, 2023 - Springer
Welding is a vital joining process; however, occurrences of weld defects often degrade the
quality of the welded part. The risk of occurrence of a variety of defects has led to the …
quality of the welded part. The risk of occurrence of a variety of defects has led to the …
Unsupervised defect segmentation of magnetic tile based on attention enhanced flexible U-Net
X Cao, B Chen, W He - IEEE Transactions on Instrumentation …, 2022 - ieeexplore.ieee.org
Surface defect inspection is necessary for the production of magnetic tiles. Automated
inspection based on machine vision and artificial intelligence can greatly improve the …
inspection based on machine vision and artificial intelligence can greatly improve the …