Isolated Word Recognition Using Low Dimensional Features and Kernel Based Classification.
Navnath S. NeheRaghunath S. HolambePublished in: ARTCom (2009)
Keyphrases
- low dimensional
- classification accuracy
- feature space
- feature representation
- feature vectors
- feature set
- feature extraction
- support vector machine
- classification models
- classification method
- support vector
- feature analysis
- extracted features
- svm classifier
- pattern recognition
- support vector machine svm
- classification process
- machine learning
- high dimensional
- feature values
- svm classification
- benchmark datasets
- decision trees
- discriminative features
- extracting features
- class labels
- image features
- classification algorithm
- multiple features
- high dimensionality
- multiple kernel learning
- image classification
- feature selection algorithms
- feature subset
- pattern classification
- kernel methods
- supervised learning
- dimensionality reduction
- multi category
- textural features
- mercer kernel
- eeg signals
- input space
- dimension reduction
- machine learning algorithms
- principal component analysis
- data points
- similarity measure
- feature selection