Advances and Challenges in Deep Learning for Automated Welding Defect Detection: A Technical Survey
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DOI: 10.1109/access.2025.3574083
Abstract: Automated welding defect detection has emerged as a pivotal aspect of quality assurance in high-stakes industries such as aerospace, oil and gas, and construction. This paper presents a comprehensive review of state-of-the-art Deep Learning (DL)… read more here.
Keywords: detection; deep learning; welding defect; automated welding ... See more keywords
An Automatic Deep Segmentation Network for Pixel-Level Welding Defect Detection
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DOI: 10.1109/tim.2021.3127645
Abstract: Accurate welding defect location is of great significance to modern manufacturing, which could be used for accurate quality evaluation and precise repairing decision-making basis of different products. Nevertheless, accurate welding defect location is still a… read more here.
Keywords: welding defect; segmentation; segmentation network; defect detection ... See more keywords
An Explainable Laser Welding Defect Recognition Method Based on Multi-Scale Class Activation Mapping
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DOI: 10.1109/tim.2022.3148739
Abstract: Vision-based online defect recognition can provide insights for laser welding quality control systems. Although the visual signal contains richer quality information than the one-dimensional signal, the quality features contained in the visual signal are more… read more here.
Keywords: multi scale; welding defect; defect recognition; method ... See more keywords