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
An efficient framework is proposed for the fast recovery of Bayesian network classifier. A novel algorithm, called Iterative Parent-Child learningBayesian Network Classifier (IPC-...
Abstract In this paper we present a new method for Joint Feature Selection and Classifier Learning (JFSCL) using a sparse Bayesian approach. These tasks are performed by optimizing...
A novel framework based on Bayes-based confidence measure for Multiple Classifier System fusion is proposed. Compared with ordinary Bayesian fusion, the presented approach leads t...
Classification of real-world data poses a number of challenging problems. Mismatch between classifier models and true data distributions on one hand and the use of approximate inf...