When using Learning Object Repositories, it is interesting to have mechanisms to select the more adequate objects for each student. For this kind of adaptation, it is important to...
Cristina Carmona, Gladys Castillo, Eva Millá...
Abstract— In this paper we consider the problem of sensorimotor coordination in a Bayesian framework. To this end we introduce a novel kind of Dynamic Bayesian Network serving as...
Ruben Coen Cagli, Paolo Napoletano, Paolo Coraggio...
Hidden Markov models are a powerful technique to model and classify temporal sequences, such as in speech and gesture recognition. However, defining these models is still an art: ...
A method is presented for the analysis of dynamic positron emission tomography (PET) data using sparse Bayesian learning. Parameters are estimated in a compartmental framework usin...
Jyh-Ying Peng, John A. D. Aston, R. N. Gunn, Cheng...
Abstract--We present a novel tracking method for effectively tracking objects in structured environments. The tracking method finds applications in security surveillance, traffic m...