In this paper, it is shown how to extract a hypothesis with small risk from the ensemble of hypotheses generated by an arbitrary on-line learning algorithm run on an independent an...
The work presented in this paper is an extension of our two previous works [1, 2]. In the first paper [1], we proposed a low dimensional feature (i-vectors) extractor which is su...
Mohammed Senoussaoui, Patrick Kenny, Pierre Dumouc...
Visual action recognition is an important problem in computer vision. In this paper, we propose a new method to probabilistically model and recognize actions of articulated object...
— We make use of discrete wavelets to extract distinguishing features between normal and cancerous human breast tissue fluorescence spectra. These are then used in conjunction wi...
Bhadra Mani, C. Raghavendra Rao, P. Anantha Lakshm...
In this work, we systematically study the problem of visual event recognition in unconstrained news video sequences. We adopt the discriminative kernel-based method for which vide...