In this paper, we proposed a neural network based scheme for performing unsupervised video object segmentation, especially for videophone or videoconferencing applications. The pr...
Anastasios D. Doulamis, Nikolaos D. Doulamis, Stef...
This paper investigates the use of the Bayesian inference for devising an unsupervised sketch rendering procedure. As likelihood model of this inference, we exploit the recent sta...
In this paper, we propose a novel unsupervised approach to query segmentation, an important task in Web search. We use a generative query model to recover a query's underlyin...
Conventional remote sensing classification techniques that model the data in each class with a multivariate Gaussian distribution are inefficient, as this assumption is generally ...
Chintan A. Shah, Manoj K. Arora, Stefan A. Robila,...
This work deals with a new technique for the estimation of the parameters and number of components in a finite mixture model. The learning procedure is performed by means of a expe...