Generative kernels represent theoretically grounded tools able to increase the capabilities of generative classification through a discriminative setting. Fisher Kernel is the fi...
Manuele Bicego, Marco Cristani, Vittorio Murino, E...
Hidden Markov models (HMMs) are powerful statistical models that have found successful applications in Information Extraction (IE). In current approaches to applying HMMs to IE, a...
One important problem proposed recently in the field of web mining is website classification problem. The complexity together with the necessity to have accurate and fast algorit...
This paper proposes some Markov Random Field (MRF) models for restoration of stereo disparity maps. The main aspect is the use of confidence maps provided by the Symmetric Multipl...
Andrea Fusiello, Umberto Castellani, Vittorio Muri...
Background: One of the most powerful methods for the prediction of protein structure from sequence information alone is the iterative construction of profile-type models. Because ...