Muhammad Akmal Hakim bin Che Mansor, Nor Ashikin Mohamad Kamal, Mohamad Hafiz bin Baharom, Muhammad Adib bin Zainol
{"title":"Emergency Vehicle Type Classification using Convolutional Neural Network","authors":"Muhammad Akmal Hakim bin Che Mansor, Nor Ashikin Mohamad Kamal, Mohamad Hafiz bin Baharom, Muhammad Adib bin Zainol","doi":"10.1109/I2CACIS52118.2021.9495899","DOIUrl":null,"url":null,"abstract":"This paper discusses the Convolutional Neural Network (CNN) applied in emergency vehicle image classification. Emergency vehicles are often found stuck in traffic congestion. It has resulted in the emergency vehicles unable to get to the scene quickly. Detecting emergency vehicles on the road can help provide a route to enable emergency vehicles to arrive more efficiently. Several methods have been used to detect the presence of these emergency vehicles on the road. Convolutional Neural Network is one of the popular classification methods nowadays. This work used VGG-16 as the pre-trained model with reduced convolutional layer and filter size. Based on the experiment, the proposed method gained an accuracy of 95%. Thus, the system has achieved the objective.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/I2CACIS52118.2021.9495899","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper discusses the Convolutional Neural Network (CNN) applied in emergency vehicle image classification. Emergency vehicles are often found stuck in traffic congestion. It has resulted in the emergency vehicles unable to get to the scene quickly. Detecting emergency vehicles on the road can help provide a route to enable emergency vehicles to arrive more efficiently. Several methods have been used to detect the presence of these emergency vehicles on the road. Convolutional Neural Network is one of the popular classification methods nowadays. This work used VGG-16 as the pre-trained model with reduced convolutional layer and filter size. Based on the experiment, the proposed method gained an accuracy of 95%. Thus, the system has achieved the objective.