Unsupervised Dimension Reduction for Image Classification Using Regularized Convolutional Auto-Encoder.
Chaoyang XuLing WuShiping WangPublished in: CVC (1) (2019)
Keyphrases
- dimension reduction
- image classification
- feature extraction
- unsupervised learning
- sparse coding
- principal component analysis
- high dimensional problems
- deep belief networks
- image representation
- high dimensional
- random projections
- data mining and machine learning
- singular value decomposition
- partial least squares
- bag of words
- bit rate
- high dimensional data
- linear discriminant analysis
- low dimensional
- feature space
- variable selection
- supervised learning
- preprocessing
- feature selection
- high dimensionality
- visual words
- semi supervised
- least squares
- manifold learning
- sparse representation
- discriminative information
- restricted boltzmann machine
- dimensionality reduction
- discriminant analysis
- semi supervised learning
- cluster analysis
- image features
- pattern recognition
- machine learning
- support vector machine svm
- probabilistic model
- high dimensional data analysis