International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (CIMCA'06)
Comparison of Several Classifiers for the Detection of Polluting Smokes
Sydney Australia
November 28-December 01
ISBN: 0-7695-2731-0
D. GACQUER, Universit? de Valenciennes et du Hainaut-Cambr?sis, Cedex, France
F. DELMOTTE, Universit? de Valenciennes et du Hainaut-Cambr?sis, Cedex, France
V. DELCROIX, Universit? de Valenciennes et du Hainaut-Cambr?sis, Cedex, France
S. PIECHOWIAK, Universit? de Valenciennes et du Hainaut-Cambr?sis, Cedex, France
This paper addresses the pollution detection problem by using a camera and analyzing the pictures. A camera is used to record visual scenes around complex plants. Then several signals are computed to describe the pictures. Our aim is to detect among the various clouds if there are polluting smokes. We assume in this paper that the signals are useful to classify the clouds and that we do not need other data. In this paper two types of classifiers are studied: bayesian networks and a k-nearest neighbour classifier.
Citation:
D. GACQUER, F. DELMOTTE, V. DELCROIX, S. PIECHOWIAK, "Comparison of Several Classifiers for the Detection of Polluting Smokes," cimca, pp.146, International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (CIMCA'06), 2006