We study learning scenarios in which multiple learners are involved and “nature” imposes some constraints that force the predictions of these learners to behave coherently. Thi...
The automated detection and tracking of humans in computer vision necessitates improved modeling of the human skin appearance. In this paper we propose a Bayesian network approach...
Ira Cohen, Nicu Sebe, Theo Gevers, Thomas S. Huang
In this paper we present a collaborative system designed to develop problem solving skills in learners through problemcentric exercises. This system is part of a data collection s...
Abstract Relational rule learning algorithms are typically designed to construct classification and prediction rules. However, relational rule learning can be adapted also to subgr...
In this paper we propose an automatic mechanism for annotating XML documents. This mechanism relies on a simple data model whose main features are: (1) a modeling of XML documents ...