We focus on credal nets, which are graphical models that generalise Bayesian nets to imprecise probability. We replace the notion of strong independence commonly used in credal ne...
Gert de Cooman, Filip Hermans, Alessandro Antonucc...
We propose new robust classification algorithms for planar and spatial curves subjected to affine transformations. Our motivation comes from the problems in computer image recognit...
This article presents a novel scale- and rotation-invariant detector and descriptor, coined SURF (Speeded-Up Robust Features). SURF approximates or even outperforms previously pro...
Herbert Bay, Andreas Ess, Tinne Tuytelaars, Luc J....
In this article, we describe a new method of extracting information from signals, called functional dissipation, that proves to be very effective for enhancing classification of h...
D. Napoletani, Daniele C. Struppa, T. Sauer, V. Mo...
Abstract: This paper presents a novel approach for object classification and pose estimation which employs spherical light field rendering to generate virtual views based on synthe...