화학공학소재연구정보센터
학회 한국화학공학회
학술대회 2013년 가을 (10/23 ~ 10/25, 대구 EXCO)
권호 19권 2호, p.1274
발표분야 공정시스템
제목 Decision support in machine vision system for monitoring of TFT-LCD glass substrates manufacturing with data mining techniques
초록 This work presents an industrial application of a new machine vision methodology to manufacturing of TFT-LCD glass substrates. Careful observation and interpretations of the results from the methodology enable one to automatically monitor the visual quality of the products. Especially, introducing a multi-objective function in designing a classifier makes it possible to achieve a manufacturing goal. Also this presentation provides some important issues in data mining such as handling imbalanced training data and feature selection. New methods such as SMOTE (Synthetic Minority Over-sampling Technique) and PGA (Parallel genetic Algorithm) are employed to handle these issues successfully.
저자 유 준1, Ali Yousefian2
소속 1부경대, 2Seoul National Univ. Department of Bioengineering
키워드 machine vision; data mining; classification; feature selection
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