Accurate noise level estimation is essential to assure good performance of noise reduction filters. Noise contaminating raw images is typically modeled as additive white and Gauss...
Angelo Bosco, Arcangelo Bruna, D. Giacalone, Sebas...
We introduce the notion of restricted Bayes optimal classifiers. These classifiers attempt to combine the flexibility of the generative approach to classification with the high ac...
This work exploits several machine-learning techniques to address the problem of image-quality prediction of synthetic aperture sonar (SAS) imagery. The objective is to predict th...
We propose a new method for detecting activation in functional magnetic resonance imaging (fMRI) data. We project the fMRI time series on a low-dimensional subspace spanned by wave...
We consider the task of under-determined reverberant audio source separation. We model the contribution of each source to all mixture channels in the time-frequency domain as a ze...