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    Defect Detection in Industrial Soldering Processes Using Machine Learning: A Critical Literature Review by Luca Eisentraut, Johanna Hosch, Maksym Roytenberg, Amelie Benecke, Pascal Penava, Ricardo Buettner

    Published 2025-01-01
    “…However, current research lacks a comprehensive overview that categorizes and analyzes relevant studies based on their specific intervention points within the production process. This literature review aims to examine and evaluate research coverage along three dimensions: intervention points in the process, non-destructive testing methods, and machine learning techniques employed. …”
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    Study on the detection and suppression methods of carbon laying defects in auto fiber placement (AFP) process by Yixuan Xie, Zhiqiang Liu, Yinqi Li, Yueyue Zong

    Published 2025-02-01
    “…Considering that temperature instability on the layup surface can lead to defects, a dynamic temperature control model has been established, and the infrared lamp’s temperature rise coefficient is determined, reducing defects caused by temperature fluctuations during the layup process. The results indicate that infrared thermography technology is feasible for the detection and reduction of defects in CFRP composites.…”
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    Using Natural Language Processing and Machine Learning to Detect Online Radicalisation in the Maldivian Language, Dhivehi by Hussain Ibrahim, Ahmed Ibrahim, Michael N. Johnstone

    Published 2025-04-01
    “…This research applied Machine Learning and Natural Language Processing (NLP) to detect online radicalisation content in Dhivehi, with the incorporation of domain-specific knowledge. …”
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    EEG Peak Detection in Cognitive Conflict Processing Using Summit Navigator and Clustering-Based Ranking by Tran Hiep Dinh, Avinash Kumar Singh, Nguyen Linh Trung, Diep N. Nguyen, Chin-Teng Lin

    Published 2022-01-01
    “…This paper proposes a novel and non-parametric approach to detect prediction error negativity (PEN) in cognitive conflict processing. …”
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    Image processing‐based noise‐resilient insulator defect detection using YOLOv8x by Shagor Hasan, Md. Abdur Rahman, Md. Rashidul Islam, Animesh Sarkar Tusher

    Published 2024-12-01
    “…Abstract Accurate and efficient insulator defect detection is critical for power grid reliability, but it can be affected by the presence of noises in captured images and can be difficult to employ for real‐time operation due to the slow processing of the detection scheme. …”
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    Detection of Small-Sized Electronics Endangering Facilities Involved in Recycling Processes Using Deep Learning by Zizhen Liu, Shunki Kasugaya, Nozomu Mishima

    Published 2025-03-01
    “…Therefore, these fire-causing items should be detected and separated regardless of whether small-sized electronics recycling or other recycling processes are in use. …”
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