A deep residual neural network for semiconductor defect classification in imbalanced scanning electron microscope datasets.
Francisco López de la RosaJosé L. Gómez-SirventRafael MoralesRoberto Sánchez-ReolidAntonio Fernández-CaballeroPublished in: Appl. Soft Comput. (2022)
Keyphrases
- scanning electron microscope
- neural network
- defect classification
- imbalanced datasets
- imbalanced data
- pattern recognition
- artificial neural networks
- neural network model
- fault diagnosis
- data sets
- benchmark datasets
- back propagation
- radial basis function
- support vector
- class imbalanced
- sampling methods
- genetic algorithm
- fermentation process
- neural network is trained
- gallium arsenide
- binary classification problems
- training dataset
- training algorithm
- class distribution
- neural nets
- recurrent neural networks
- training data