Chang Ouk Kim

Chang Ouk Kim

Yonsei University

Professor

Department of Information and Industrial engineering

Research Area

  • #Computer science
  • #Artificial intelligence
  • #Fault detection and isolation
  • #Data mining
  • #Feature extraction
  • #Engineering
  • #Semiconductor device modeling
  • #Electronic engineering
  • #Wafer
  • #Support vector machine

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Related papers to
‘ Computer science ‘ : 12

  • An Incremental Clustering-Based Fault Detection Algorithm for Class-Imbalanced Process Data

    2015/08

    1.0 Impact Factor

    27 citations

    Jueun Kwak, Taehyung Lee, Chang Ouk Kim

    DOI : 10.1109/TSM.2015.2445380

    • #Computer science
    • #Data mining
    • #Cluster analysis
    • #Support vector machine
    • #Fault detection and isolation
    • #Statistical classification
    • #Standard algorithms
    • #Correlation clustering
    • #CURE data clustering algorithm
    • #Canopy clustering algorithm

All papers authored by
‘ Chang Ouk Kim ’ : 21

  • A Convolutional Neural Network for Fault Classification and Diagnosis in Semiconductor Manufacturing Processes

    2017/05
    IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING

    1.3 Impact Factor

    244 citations

    Ki Bum Lee, Sejune Cheon, Chang Ouk Kim

    DOI : 10.1109/TSM.2017.2676245

    • #Engineering
    • #Artificial intelligence
    • #Electronic engineering
    • #Artificial neural network
    • #Feature extraction
    • #Convolutional neural network
    • #Fault detection and isolation
    • #Black box
    • #Deep learning
    • #Semiconductor device fabrication
    • #Semiconductor device modeling

Related papers to
‘ Computer science ‘ : 12

  • An Incremental Clustering-Based Fault Detection Algorithm for Class-Imbalanced Process Data

    2015/08
    IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING

    1.0 Impact Factor

    27 citations

    Jueun Kwak, Taehyung Lee, Chang Ouk Kim

    DOI : 10.1109/TSM.2015.2445380

    • #Computer science
    • #Data mining
    • #Cluster analysis
    • #Support vector machine
    • #Fault detection and isolation
    • #Statistical classification
    • #Standard algorithms
    • #Correlation clustering
    • #CURE data clustering algorithm
    • #Canopy clustering algorithm
  • Performance of Machine Learning Algorithms for Class-Imbalanced Process Fault Detection Problems

    2016/11
    IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING

    1.1 Impact Factor

    21 citations

    Taehyung Lee, Ki Bum Lee, Chang Ouk Kim

    DOI : 10.1109/TSM.2016.2602226

    • #Computer science
    • #Artificial intelligence
    • #Algorithm
    • #Data mining
    • #Machine learning
    • #Sampling (statistics)
    • #Support vector machine
    • #Fault detection and isolation
    • #Boosting (machine learning)
    • #Type I and type II errors
    • #Semiconductor device fabrication
    • #Semiconductor device modeling
    • #Computational learning theory

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Contact information

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All papers authored by
‘ Chang Ouk Kim ’ : 21

  • A Convolutional Neural Network for Fault Classification and Diagnosis in Semiconductor Manufacturing Processes

    2017/05
    IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING

    1.3 Impact Factor

    244 citations

    Ki Bum Lee, Sejune Cheon, Chang Ouk Kim

    DOI : 10.1109/TSM.2017.2676245

    • #Engineering
    • #Artificial intelligence
    • #Electronic engineering
    • #Artificial neural network
    • #Feature extraction
    • #Convolutional neural network
    • #Fault detection and isolation
    • #Black box
    • #Deep learning
    • #Semiconductor device fabrication
    • #Semiconductor device modeling
  • Convolutional Neural Network for Wafer Surface Defect Classification and the Detection of Unknown Defect Class

    2019/03
    IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING

    2.0 Impact Factor

    64 citations

    Sejune Cheon, Hankang Lee, Chang Ouk Kim, Seok Hyung Lee

    DOI : 10.1109/TSM.2019.2902657

    • #Materials science
    • #Artificial intelligence
    • #Electronic engineering
    • #Pattern recognition
    • #Wafer
    • #Feature extraction
    • #Convolutional neural network
    • #Deep learning
    • #Semiconductor device modeling
    • #Feature extraction algorithm

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