We advance new active object recognition algorithms that classify rigid objects and estimate their pose from intensity images. Our algorithms automatically detect if the class or p...
—This paper presents a novel probabilistic approach to hierarchical, exemplar-based shape matching. No feature correspondence is needed among exemplars, just a suitable pairwise ...
This paper introduces design principles for modular Bayesian fusion systems which can (i) cope with large quantities of heterogeneous information and (ii) can adapt to changing co...
Gregor Pavlin, Patrick de Oude, Marinus Maris, Jan...
We study the problem of statistical model checking of probabilistic systems for PCTL unbounded until property P1p(ϕ1 U ϕ2) (where 1 ∈ {<, ≤, >, ≥}) using the computa...
Ru He, Paul Jennings, Samik Basu, Arka P. Ghosh, H...
Aggregating statistical representations of classes is an important task for current trends in scaling up learning and recognition, or for addressing them in distributed infrastruc...