In this paper we describe a new framework for the tracking of closed curves described through implicit surface modeling. The approach proposed here enables a continuous tracking al...
Traditionally, machine learning algorithms have been evaluated in applications where assumptions can be reliably made about class priors and/or misclassification costs. In this pa...
Previous algorithms for learning lexicographic preference models (LPMs) produce a "best guess" LPM that is consistent with the observations. Our approach is more democra...
Fusun Yaman, Thomas J. Walsh, Michael L. Littman, ...
In this paper, a new framework for the tracking of closed curves is described. The proposed approach, formalized through an optimal control technique, enables a continuous trackin...
Bayesian networks (BNs) are used to represent and ef ciently compute with multi-variate probability distributions in a wide range of disciplines. One of the main approaches to per...