We investigate the problem of acoustic modeling in which prior language-specific knowledge and transcribed data are unavailable. We present an unsupervised model that simultaneou...
We present here some applications of the Minimum Message Length (MML) principle to spatially correlated data. Discrete valued Markov Random Fields are used to model spatial correl...
This work takes place in the context of hierarchical stochastic models for the resolution of discrete inverse problems from low level vision. Some of these models lie on the nodes...
This paper deals with the problem of statistical unsupervised fusion of dependent sensors with its potential applications to multisensor image segmentation. On the one hand, Bayes...
In the present paper we propose a method for fast segmentation of ultrasound data. It is based on setting up a model depending on user input. We apply a matching scheme in order t...