This paper proposes the use of constructive ordinals as mistake bounds in the on-line learning model. This approach elegantly generalizes the applicability of the on-line mistake ...
If sufficient attention is not paid to the information models on which Learning Platforms are based the ability to deliver rich functionality is hindered. This paper describes the...
We present a face recognition system able to identify people from a single non-frontal image in an arbitrary pose. The key component of the system is a novel pose correction techni...
Jean-Yves Guillemaut, Josef Kittler, Mohammad Sade...
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...
: In Bayesian identification an ID source is in conflict with the other ID sources, if both provide substantially different, reliable information on a tracked object. After discuss...