Automatic Vehicle Classification for Electronic Toll Collection using YOLOv3

  • Bahrin M
N/ACitations
Citations of this article
6Readers
Mendeley users who have this article in their library.

Abstract

This paper proposes the application of object detection and classification application in the area of intelligent transportation system, that is in Electronic Toll Collection (ETC) system. ETC is a cashless toll collection system, where there should be no human being involved at the toll booth anymore. Due to different toll rate applies to different type of vehicle, there is a need to have a system to detect and classify the type of vehicle passing through the toll booth. Thus, this paper proposed an automatic vehicle classification using an algorithm based on YOLOv3. The proposed model is tested and validated by extensive experiments. The result shows that the propose model manage to identify the type of vehicle in more than 92.12% accurate.

Cite

CITATION STYLE

APA

Bahrin, M. A. (2020). Automatic Vehicle Classification for Electronic Toll Collection using YOLOv3. International Journal of Advanced Trends in Computer Science and Engineering, 9(4), 5337–5342. https://doi.org/10.30534/ijatcse/2020/168942020

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free