A Drift-Compensating Novel Deep Belief Classification Network to Improve Gas Recognition of Electronic Noses.
Yutong TianJia YanYiyun ZhangTianhang YuPeiyuan WangDebo ShiShukai DuanPublished in: IEEE Access (2020)
Keyphrases
- pattern recognition
- feature extraction
- automatic recognition
- object classification
- correct recognition
- genetic algorithm
- pattern recognition tasks
- recognition accuracy
- benchmark datasets
- training samples
- image classification
- action recognition
- recognition rate
- supervised learning
- decision trees
- support vector machine
- feature vectors
- low error rates
- robust detection
- handwritten digits
- recognition process
- support vector
- visual recognition
- object recognition
- automatic classification
- concept drift
- peer to peer
- network structure
- class labels
- machine learning
- unsupervised learning
- computer networks
- network model
- activity recognition
- classification method
- decision rules
- classification accuracy
- radial basis function network
- model selection
- social networks
- feature set