Vehicle classification using evolutionary forests

Evans, M., Boyle, J. N. ORCID: https://orcid.org/0000-0002-5785-8046 and Ferryman, J. (2012) Vehicle classification using evolutionary forests. Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1:. pp. 387-393. ISSN 2184-4313 doi: 10.5220/0003763603870393 (ISBN 9789898425997)

Abstract/Summary

Forests of decision trees are a popular tool for classification applications. This paper presents an approach to evolving the forest classifier, reducing the time spent designing the optimal tree depth and forest size. This is applied to the task of vehicle classification for purposes of verification against databases at security checkpoints, or accumulation of road usage statistics. The evolutionary approach to building the forest classifier is shown to out-perform a more typically grown forest and a baseline neural-network classifier for the vehicle classification task.