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Reenu Mohandas, Mark Southern, Eoin O?Connell and Martin Hayes
Deep learning based visual cognition has greatly improved the accuracy of defect detection, reducing processing times and increasing product throughput across a variety of manufacturing use cases. There is however a continuing need for rigorous procedure...
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Pavlo Maruschak, Ihor Konovalenko, Yaroslav Osadtsa, Volodymyr Medvid, Oleksandr Shovkun, Denys Baran, Halyna Kozbur and Roman Mykhailyshyn
Modern neural networks have made great strides in recognising objects in images and are widely used in defect detection. However, the output of a neural network strongly depends on both the training dataset and the conditions under which the image was ac...
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Baobao Liu, Heying Wang, Zifan Cao, Yu Wang, Lu Tao, Jingjing Yang and Kaibing Zhang
Defect detection holds significant importance in improving the overall quality of fabric manufacturing. To improve the effectiveness and accuracy of fabric defect detection, we propose the PRC-Light YOLO model for fabric defect detection and establish a ...
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Xiaochuan Jiang, Jun Wang, Ying Zhang and Shenxue Jiang
This paper reports on investigations of the air-coupled ultrasonic (ACU) method to detect common defects in solid timber panels made of Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.). The ACU technology is a non-contact method for nondestructive tim...
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Ning Li, Tianrun Ye, Zhihua Zhou, Chunming Gao and Ping Zhang
In the domain of automatic visual inspection for miniature capacitor quality control, the task of accurately detecting defects presents a formidable challenge. This challenge stems primarily from the small size and limited sample availability of defectiv...
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Shancheng Tang, Ying Zhang, Zicheng Jin, Jianhui Lu, Heng Li and Jiqing Yang
The number of defect samples on the surface of aluminum profiles is small, and the distribution of abnormal visual features is dispersed, such that the existing supervised detection methods cannot effectively detect undefined defects. At the same time, t...
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Zhendong He, Wenbin Yang, Yanjie Liu, Anping Zheng, Jie Liu, Taishan Lou and Jie Zhang
Ensuring the safety of transmission lines necessitates effective insulator defect detection. Traditional methods often need more efficiency and accuracy, particularly for tiny defects. This paper proposes an innovative insulator defect recognition method...
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Tianjie Fu, Peiyu Li, Chenke Shi and Youzhu Liu
The growing demand for high-quality steel across various industries has led to an increasing need for superior-grade steel. The quality of slab ingots is a pivotal factor influencing the final quality of steel production. However, the current level of in...
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Zahra Ameli, Shabnam Jafarpoor Nesheli and Eric N. Landis
The application of deep learning (DL) algorithms has become of great interest in recent years due to their superior performance in structural damage identification, including the detection of corrosion. There has been growing interest in the application ...
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Bata Hena, Ziang Wei, Luc Perron, Clemente Ibarra Castanedo and Xavier Maldague
Industrial radiography is a pivotal non-destructive testing (NDT) method that ensures quality and safety in a wide range of industrial sectors. Conventional human-based approaches, however, are prone to challenges in defect detection accuracy and efficie...
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