We present a tutorial survey on some recent approaches to unsupervised machine learning in the context of statistical pattern recognition. In statistical PR, there are two classica...
Abstract. We present an approach for blindly decomposing an observed random vector x into f(As) where f is a diagonal function i.e. f = f1 × . . . × fm with one-dimensional funct...
— We introduce in this paper methods for finding mutually corresponding dependent components from two different but related data sets in an unsupervised (blind) manner. The basi...
—This paper introduces a new representation of hand motions for tracking and recognizing hand-finger gestures in an image sequence. A human hand has many joints, for example our ...
Statistical shape analysis techniques commonly employed in the medical imaging community, such as Active Shape Models or Active Appearance Models, rely on Principal Component Anal...
Mauricio Reyes, Marius George Linguraru, Kostas Ma...
—In this paper, a new model that can ultimately create its own set of perceptual features is proposed. Using a bidirectional associative memory (BAM)-inspired architecture, the r...
This paper introduces a novel technique for palmprint recognition on the transform domain, based on combining principle component analysis (PCA) and Fourier domain. Principal Comp...
Moussadek Laadjel, Ahmed Bouridane, Fatih Kurugoll...
Abstract. Topic models are a discrete analogue to principle component analysis and independent component analysis that model topic at the word level within a document. They have ma...
In this paper, we introduce a method for estimating the statistically distinct neural responses in an sequence of functional magnetic resonance images (fMRI). The crux of our meth...
Computer Vision Center and Autonomous University of Barcelona,
Homepage
José M. Álvarez received his B.Sc. degree in Telecommunications (2000), as well as his M.Sc. degree in Telecommunications (2005) from La Salle School of Engineering at Ramon Llu...