Over the last several years, a new probabilistic representation for 3-d volumetric modeling has been developed. The main purpose of the model is to detect deviations from the norm...
: In this work we introduce an iterative method that deforms brain models built from tomographic images. The deformation is used for normalization purposes: individual models are d...
The modeling of high level semantic events from low level sensor signals is important in order to understand distributed phenomena. For such content-modeling purposes, transformat...
We explore some presynaptic mechanisms of the calyx of Held synapse through a stochastic model. The model, drawn from a kinetic approach developed in literature, exploits process c...
Andrea Bracciali, Marcello Brunelli, Enrico Catald...
Abstract. We discuss a case study for the hospital scenario where workflow model components are distributed across various computers or devices (e.g. mobile phones, PDAs, sensors, ...