Probabilistic topic models have become popular as methods for dimensionality reduction in collections of text documents or images. These models are usually treated as generative m...
Abstract. We propose a deep study on tissue modelization and classification Techniques on T1-weighted MR images. Three approaches have been taken into account to perform this valid...
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
We consider the multi-class classification problem, based on vector observation sequences, where the conditional (given class observations) probability distributions for each class...