Improving face detection
Inhaltsverzeichnis
Referenz
Machado, P., Correia, J., Romero, J.: Improving face detection. In: Moraglio, A., Silva, S., Krawiec, K., Machado, P., Cotta, C. (eds.) EuroGP 2012. LNCS, vol. 7244, pp. 73–84. Springer, Heidelberg (2012)
DOI
http://dx.doi.org/10.1007/978-3-642-29139-5_7
Abstract
A novel Genetic Programming approach for the improvement of the performance of classifier systems through the synthesis of new training instances is presented. The approach relies on the ability of the Genetic Programming engine to identify and exploit shortcomings of classifier systems, and generate instances that are misclassified by them. The addition of these instances to the training set has the potential to improve classifier’s performance. The experimental results attained with face detection classifiers are presented and discussed. Overall they indicate the success of the approach.
Extended Abstract
Bibtex
@Inbook{Machado2012,
author="Machado, Penousal and Correia, Jo{\~a}o and Romero, Juan",
editor="Moraglio, Alberto and Silva, Sara and Krawiec, Krzysztof and Machado, Penousal and Cotta, Carlos",
title="Improving Face Detection",
bookTitle="Genetic Programming: 15th European Conference, EuroGP 2012, M{\'a}laga, Spain, April 11-13, 2012. Proceedings",
year="2012",
publisher="Springer Berlin Heidelberg",
address="Berlin, Heidelberg",
pages="73--84",
isbn="978-3-642-29139-5",
doi="10.1007/978-3-642-29139-5_7",
url="http://dx.doi.org/10.1007/978-3-642-29139-5_7 http://de.evo-art.org/index.php?title=Improving_face_detection"
}
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