PCA Dimensionality Reduction Method for Image Classification.
Baiting ZhaoXiao DongYongcun GuoXiaofen JiaYourui HuangPublished in: Neural Process. Lett. (2022)
Keyphrases
- dimensionality reduction methods
- image classification
- principal component analysis
- dimensionality reduction
- feature extraction
- principal components analysis
- discriminant projection
- discriminant analysis
- preprocessing step
- image representation
- bag of words
- linear discriminant analysis
- fisher discriminant analysis
- random projections
- data sets
- sparse representation
- covariance matrix
- principal components
- lower dimensional
- low dimensional
- image features
- knn
- high dimensional
- multimodal data
- kernel trick
- feature space
- face recognition
- dimension reduction
- manifold learning
- high dimensional data analysis
- feature selection
- pattern recognition
- independent component analysis
- high dimensional data
- high dimensionality
- supervised dimensionality reduction
- distance measure
- svm classifier
- sparse coding
- preprocessing
- input space
- singular value decomposition
- similarity search
- kernel pca
- semi supervised
- data points
- image processing