We propose the use of latent space models applied to local invariant features for object classification. We investigate whether using latent space models enables to learn patterns...
Florent Monay, Pedro Quelhas, Daniel Gatica-Perez,...
Graphical models such as Bayesian Networks (BNs) are being increasingly applied to various computer vision problems. One bottleneck in using BN is that learning the BN model param...
We propose an algorithm for semantic segmentation based on 3D point clouds derived from ego-motion. We motivate five simple cues designed to model specific patterns of motion and 3...
Gabriel J. Brostow, Jamie Shotton, Julien Fauqueur...
Objective: This study investigates the use of automated pattern recognition methods on magnetic resonance data with the ultimate goal to assist clinicians in the diagnosis of brai...
Jan Luts, Arend Heerschap, Johan A. K. Suykens, Sa...
The aim of this paper is to present a dissimilarity measure strategy by which a new philosophy for pattern classification pertaining to dissimilaritybased classifications (DBCs) ca...