Machine learning-based novelty detection for faulty wafer detection in semiconductor manufacturing.
Dongil KimPilsung KangSungzoon ChoHyoungjoo LeeSeungyong DohPublished in: Expert Syst. Appl. (2012)
Keyphrases
- semiconductor manufacturing
- novelty detection
- machine learning
- anomaly detection
- process control
- text filtering
- discrete event simulation
- data mining
- feature selection
- computer vision
- production system
- detection algorithm
- active learning
- concept drift
- unsupervised learning
- detection method
- information extraction
- support vector machine
- pattern recognition
- real time
- high resolution
- data analysis
- sentence level
- bayesian networks
- artificial intelligence
- support vector data description