We propose an Isometric Self-Organizing Map (ISOSOM) method for nonlinear dimensionality reduction, which integrates a Self-Organizing Map model and an ISOMAP dimension reduction ...
We propose modeling images and related visual objects as bags of pixels or sets of vectors. For instance, gray scale images are modeled as a collection or bag of (X, Y, I) pixel v...
We develop a supervised dimensionality reduction method, called Lorentzian Discriminant Projection (LDP), for feature extraction and classification. Our method represents the str...
In recent years analysis of complexity of learning Gaussian mixture models from sampled data has received significant attention in computational machine learning and theory commun...
A novel method for robust super-resolution offace images is proposed in this paper. Face super-resolution is a particular interest in video surveillance where face images have typ...