Abstract. Independent component analysis (ICA) of functional magnetic resonance imaging (fMRI) data is commonly carried out under the assumption that each source may be represented...
A straight line detection algorithm is presented. The algorithm separates row and column edges from edge image using their primitive shapes. The edges are labeled, and the princip...
Sparse Component Analysis is a relatively young technique that relies upon a representation of signal occupying only a small part of a larger space. Mixtures of sparse components ...
Appearance Models (AM) are commonly used to model appearance and shape variation of objects in images. In particular, they have proven useful to detection, tracking, and synthesis...
Fernando De la Torre, Alvaro Collet, Manuel Quero,...
Principal component analysis (PCA) is a powerful fault detection and isolation method. However, the classical PCA which is based on the estimation of the sample mean and covariance...