Vehicle Classification Using Inductive Loops Sensors
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Date
Authors
Halachkin, Aliaksei
Advisor
Referee
Mark
Journal Title
Journal ISSN
Volume Title
Publisher
Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
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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.
Description
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/
Document type
Peer-reviewed
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Published version
Date of access to the full text
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en