A recognition and novelty detection approach based on Curvelet transform, nonlinear PCA and SVM with application to indicator diagram diagnosis.
Kun FengZhinong JiangWei HeBo MaPublished in: Expert Syst. Appl. (2011)
Keyphrases
- novelty detection
- recognition rate
- principal component analysis
- feature extraction
- support vector
- kernel pca
- support vector machine svm
- support vector machine
- text filtering
- curvelet transform
- object recognition
- pattern recognition
- face recognition
- image analysis
- wavelet transform
- training set
- feature space
- unsupervised learning
- recognition algorithm
- feature selection
- data sets