A comparative example between the use of PCA and MDS for image classification.
Wilmar HernandezAlfredo MéndezOmar Flor-UndaVicente González PosadasJosé Luis Jiménez MartinOleg SergiyenkoJulio C. Rodríguez-QuiñonezMykhailo IvanovIvan Menes CamejoMarina KolendovskaPublished in: ISIE (2020)
Keyphrases
- image classification
- principal component analysis
- feature extraction
- multidimensional scaling
- principal components analysis
- svm classifier
- multi dimensional scaling
- dimensionality reduction
- image representation
- principal components
- principle component analysis
- bag of words
- face recognition
- independent component analysis
- visual features
- covariance matrix
- linear discriminant analysis
- kernel pca
- appearance based object recognition
- comparative analysis
- sparse representation
- feature space
- discriminant analysis
- low dimensional
- face images
- visual words
- negative matrix factorization
- sparse coding
- multi label
- image features
- manifold learning
- feature selection
- dimension reduction
- random projections
- class specific
- computer vision
- cluster analysis
- gabor features
- remotely sensed data
- image processing