A straightforward and efficient way to discover clustering tendencies in data using a recently proposed Maximum Variance Clustering algorithm is proposed. The approach shares the ...
Abstract. This paper deals with the problem of reconstructing a highresolution image from an incomplete set of undersampled, blurred and noisy images shifted with subpixel displace...
Javier Mateos, Miguel Vega, Rafael Molina, Aggelos...
This paper proposes to transform data scanned randomly in a well-defined space (e.g, Euclidean) along a hierarchical irregular pyramidal structure in an attempt reduce search time...
Artificial neural networks (ANN), esp. multilayer perceptrons (MLP) have been widely used in pattern recognition and classification. Nevertheless, how to incorporate a priori know...
We present feature transformations useful for exploratory data analysis or for pattern recognition. Transformations are learned from example data sets by maximizing the mutual inf...