We address the issue of classifying complex data. We focus on three main sources of complexity, namely, the high dimensionality of the observed data, the dependencies between these...
Reaching movements require the brain to generate motor commands that rely on an internal model of the task's dynamics. Here we consider the errors that subjects make early in...
In this paper, we describe the development of a virtual human to be used for training applications in the field of cardiac emergencies. The system integrates AI techniques for sim...
In the paper we combine a Bayesian Network model for encoding forensic evidence during a given time interval with a Hidden Markov Model (EBN-HMM) for tracking and predicting the de...
Olivier Y. de Vel, Nianjun Liu, Terry Caelli, Tib&...
This paper presents a Named Entity Recognition (NER) method dedicated to process speech transcriptions. The main principle behind this method is to collect in an unsupervised way ...