In this paper, we investigate the use of the watershed transformation for integrating spatial and spectral information in the process of endmember extraction for spectral unmixing...
Principal component analyses (PCA) has been widely used in reduction of the dimensionality of datasets, classification, feature extraction, etc. It has been combined with many oth...
Feature subset selection, applied as a pre-processing step to machine learning, is valuable in dimensionality reduction, eliminating irrelevant data and improving classifier perfo...
We present two methods using mixtures of linear subspaces for face detection in gray level images. One method uses a mixture of factor analyzers to concurrently perform clustering...
Ming-Hsuan Yang, Narendra Ahuja, David J. Kriegman
Abstract—Many practical applications require the reconstruction of images from irregularly sampled data. The spline formalism offers an attractive framework for solving this prob...
Oleksii Vyacheslav Morozov, Michael Unser, Patrick...