Poster abstract: A machine learning approach for vehicle classification using passive infrared and ultrasonic sensors

Ehsan Ullah Warriach, Christian G. Claudel

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

This article describes the implementation of four different machine learning techniques for vehicle classification in a dual ultrasonic/passive infrared traffic flow sensors. Using k-NN, Naive Bayes, SVM and KNN-SVM algorithms, we show that KNN-SVM significantly outperforms other algorithms in terms of classification accuracy. We also show that some of these algorithms could run in real time on the prototype system. Copyright © 2013 ACM.
Original languageEnglish (US)
Title of host publicationProceedings of the 12th international conference on Information processing in sensor networks - IPSN '13
PublisherAssociation for Computing Machinery (ACM)
Pages333-334
Number of pages2
ISBN (Print)9781450319591
DOIs
StatePublished - 2013

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