We propose a novel probabilistic framework for learning
visual models of 3D object categories by combining appearance
information and geometric constraints. Objects are
represen...
This paper introduces a new classification scheme called “open-ended texture classification.” The standard approach for texture classification is to use a closed n-class cl...
In this paper we extend previous results providing a theoretical analysis of a new Monte Carlo ensemble classifier. The framework allows us to characterize the conditions under wh...
We introduce a new stacking-like approach for multi-value classification. We apply this classification scheme using Naive Bayes, Rocchio and kNN classifiers on the well-known Reute...
The aim of this paper is to show how abduction can be used in classification tasks when we deal with incomplete data. Some classifiers, even if based on decision tree induction lik...