Speech recognition is usually based on Hidden Markov Models (HMMs), which represent the temporal dynamics of speech very efficiently, and Gaussian mixture models, which do non-opt...
The problem of automatic recognition of human activities is among the most important and challenging open areas of research in Computer Vision. This paper presents a new approach ...
Arcangelo Distante, I. Gnoni, Marco Leo, Paolo Spa...
We present a new brain segmentation framework which we apply to T1-weighted magnetic resonance image segmentation. The innovation of the algorithm in comparison to the state-of-the...
Torsten Butz, Patric Hagmann, Eric Tardif, Reto Me...
We present a unified model of what was traditionally viewed as two separate tasks: data association and intensity tracking of multiple topics over time. In the data association pa...
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...