In this paper we propose a Bayesian framework for XCS [9], called BXCS. Following [4], we use probability distributions to represent the uncertainty over the classifier estimates ...
Davide Aliprandi, Alex Mancastroppa, Matteo Matteu...
In this paper we present an approach to recognition confidence scoring and a set of techniques for integrating confidence scores into the understanding and dialogue components of ...
Timothy J. Hazen, Stephanie Seneff, Joseph Polifro...
This paper describes a new approach to combine multiple modalities and applies it to the problem of affect recognition. The problem is posed as a combination of classifiers in a p...
In this work is presented a novel approach for the classification of audio concepts in broadcast soccer videos using deep belief network (DBN), a probabilistic neural network with...
Lamberto Ballan, Alessio Bazzica, Marco Bertini, A...
Abstract--In this paper we propose a probabilistic classification algorithm with a novel Dynamic Time Warping (DTW) kernel to automatically recognize flight calls of different spec...
Theodoros Damoulas, Samuel Henry, Andrew Farnswort...