In this paper we present a probabilistic framework for tracking objects based on local dynamic segmentation. We view the segn to be a Markov labeling process and abstract it as a ...
We consider distributed estimation of a time-dependent, random state vector based on a generally nonlinear/non-Gaussian state-space model. The current state is sensed by a serial ...
In this paper we propose fully distributed trustbased policies for p2p systems to regulate the exchange of different type of services and discourage misbehaviour. In a system of p...
Abstract. This paper presents a new approach to regional myocardial contractility analysis based on inter-landmark motion (ILM) vectors and multivariate outlier detection. The prop...
In this paper we describe a method of learning hierarchical representations for describing and recognizing gestures expressed as one and two arm movements using competitive learni...