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<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">JERA</journal-id><journal-title-group><journal-title>Journal of Electronic Research and Application</journal-title></journal-title-group><issn>2208-3502</issn><eissn>2208-3510</eissn><publisher><publisher-name>Bio-Byword Scientific Publishing Pty. Ltd.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26689/jera.v9i2.10009</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>The Application of Machine Vision in Defect Detection Systems</title><url>https://artdesignp.com/journal/JERA/9/2/10.26689/jera.v9i2.10009</url><author>ZhongPeihang,LinJiawei,WangMuling</author><pub-date pub-type="publication-year"><year>2025</year></pub-date><volume>9</volume><issue>2</issue><history><date date-type="pub"><published-time>2025-04-02</published-time></date></history><abstract>With the rapid development of computer vision technology, artificial intelligence algorithms, and high-performance computing platforms, machine vision technology has gradually shown its great potential in automated production lines, especially in defect detection. Machine vision technology can be applied in many industries such as semiconductor, automobile manufacturing, aerospace, food, and drugs, which can significantly improve detection efficiency and accuracy, reduce labor costs, improve product quality, enhance market competitiveness, and provide strong support for the arrival of Industry 4.0 era. 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