Vehicle Classification Using Inductive Loops Sensors
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Date
2017
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Mark
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Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Abstract
This project is dedicated to the problem of vehicle classification using inductive loop sensors. Developed classifier is based on nearest neighbors and logistic regression models and achieves 94 % accuracy on classification scheme with 9 vehicle classes.
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Citation
Proceedings of the 23st Conference STUDENT EEICT 2017. s. 302-304. ISBN 978-80-214-5496-5
http://www.feec.vutbr.cz/EEICT/
http://www.feec.vutbr.cz/EEICT/
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Peer-reviewed
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en
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© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií