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Automatic defect classification of TFT-LCD panels using machine learning

机译:使用机器学习自动缺陷TFT-LCD面板的分类

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Defect classification in the liquid crystal display (LCD) manufacturing process is one of the most crucial issues for quality control. To resolve this constraint, an automatic defect classification (ADC) method based on machine learning is proposed. Key features of LCD micro-defects are defined and extracted, and support vector machine is used for classification. The classification performance is presented through several experimental results.
机译:液晶显示器(LCD)制造过程中的缺陷分类是质量控制最重要的问题之一。为了解决此约束,提出了一种基于机器学习的自动缺陷分类(ADC)方法。 LCD微缺陷的关键特征是定义和提取的,支持向量机用于分类。分类性能通过几种实验结果提出。

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