Study of Accurate and Fast Estimation Method of Vehicle Length Based on YOLOs

Research output: Chapter in Book/Conference paperConference paper

Abstract

With the development of AIoT, Smart City Traffic Management System based on artificial intelligence and big data has gradually become an effective urban management system. Instead of raw data from sensors and cameras, some specific information, such as the length of vehicles are more expected to be gained in Smart City. In this paper, a vehicle length estimation method is proposed based on the Convolutional Neural Networks (CNN) and image processing. The vehicles will be detected by YOLOs, a CNN model for object detection. Then the approximate length of vehicles will be estimated. Experiment results verify that the vehicle length estimation based on YOLOs approach a high accuracy at low time consumption.
Original languageEnglish
Title of host publication Proceedings of 2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS)
EditorsXia Huang
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages118-121
ISBN (Print)978‐1‐7281‐6590‐5
DOIs
Publication statusPublished - 22 Mar 2020
EventIEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS) - Dailan, China
Duration: 20 Mar 202022 Mar 2020

Conference

ConferenceIEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS)
Abbreviated titleICAIIS
CountryChina
CityDailan
Period20/03/2022/03/20

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