Time series prediction is an important issue in a wide range of areas. There are various real world processes whose states vary continuously, and those processes may have influenc...
This paper proposes an approach to classification of adjacent segments of a time series as being either of classes. We use a hierarchical model that consists of a feature extract...
We tackle the problem of real-time statistical analysis of functional magnetic resonance imaging (fMRI) data. In a recent paper, we proposed an incremental algorithm based on the e...
Alexis Roche, Philippe Pinel, Stanislas Dehaene, J...
Multivariate time series (MTS) datasets are common in various multimedia, medical and financial applications. We propose a similarity measure for MTS datasets, Eros (Extended Fro...
The process of finding representative shape patterns from sparse datasets is a challenging task: especially for non-rigid objects, shape deformations through time can produce very...
Stefano Maludrottu, Hany Sallam, Carlo S. Regazzon...