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Authors: Murray Evans ; Jonathan N. Boyle and James Ferryman

Affiliation: University of Reading, United Kingdom

ISBN: 978-989-8425-99-7

Keyword(s): Vehicle classification, Evolutionary forests.

Related Ontology Subjects/Areas/Topics: Applications ; Classification ; Evolutionary Computation ; Object Recognition ; Pattern Recognition ; Software Engineering ; Theory and Methods

Abstract: 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.

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Paper citation in several formats:
Evans, M.; N. Boyle, J. and Ferryman, J. (2012). VEHICLE CLASSIFICATION USING EVOLUTIONARY FORESTS.In Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-8425-99-7, pages 387-393. DOI: 10.5220/0003763603870393

@conference{icpram12,
author={Murray Evans. and Jonathan N. Boyle. and James Ferryman.},
title={VEHICLE CLASSIFICATION USING EVOLUTIONARY FORESTS},
booktitle={Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2012},
pages={387-393},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003763603870393},
isbn={978-989-8425-99-7},
}

TY - CONF

JO - Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - VEHICLE CLASSIFICATION USING EVOLUTIONARY FORESTS
SN - 978-989-8425-99-7
AU - Evans, M.
AU - N. Boyle, J.
AU - Ferryman, J.
PY - 2012
SP - 387
EP - 393
DO - 10.5220/0003763603870393

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