Traffic Sign Recognition System

+91-7667918914 iarjset@gmail.com 0 Items International Advanced Research Journal in Science, Engineering and Technology A Monthly Peer-Reviewed Multidisciplinary Journal ISSN Online 2393-8021 ISSN Print 2394-1588 Since 2014 Home About About IARJSET Aims and Scope Editorial Board Editorial Policies Publication Ethics Publication Policies Indexing and Abstracting Citation Index License Information Authors How can I publish my paper? Instructions to Authors Benefits to Authors Why Publish in IARJSET Call for Papers Check my Paper status Publication Fee Details Publication Fee Mode FAQs Author Testimonials Reviewers Topics Peer Review Current Issue & Archives Indexing FAQ’s Contact Select Page Traffic Sign Recognition System Shubham Arya, Vishal Kumar Singh

Abstract: Automatic detection, recognition and audio output of traffic signs is vital and might actually be utilized for driver help to decrease mishaps and ultimately in driverless cars. In this paper, Deep Convolutional Neural Network (CNN) is utilized to foster an Autonomous Traffic and Road Sign location and acknowledgment framework. The proposed framework works progressively distinguishing and perceiving traffic sign pictures. The commitment of this paper is additionally a recently evolved information base of 43 diverse traffic signs gathered from irregular street sides in India. The pictures were taken from various points and including different boundaries and conditions. A sum of 40000+ pictures were gathered to frame the data set which we named Indian Traffic and Road Signs. The CNN engineering was utilized with shifting boundaries to accomplish the best acknowledgment rates. Test results show that the proposed CNN engineering accomplished a precision of 98%, in this manner higher than those accomplished in comparative past investigations Downloads: | DOI: 10.17148/IARJSET.2021.81139 How to Cite: [1] Shubham Arya, Vishal Kumar Singh, "Traffic Sign Recognition System," International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: IARJSET.2021.81139 Copy Citation Call for Papers Rapid Publication 24/7 April 2026 Submission: eMail paper now Notification: Immediate Publication: Immediately with eCertificates Frequency: Monthly Downloads Paper Format Copyright Form   Submit to iarjset@gmail.com or editor@iarjset.com   Submit My Paper Author CenterHow can I publish my paper? Publication Fee Why Publish in IARJSET Benefits to Authors Guidelines to Authors FAQs (Frequently Asked Questions) Author Testimonials IARJSET ManagementAims and Scope Call for Papers Editorial Board DOI and Crossref Publication Ethics Editorial Policies Publication Policies Subscription / Librarian Conference Special Issue Info ArchivesCurrent Issue & Archives Conference Special Issue Copyright © 2026 IARJSET This work is licensed under a Creative Commons Attribution 4.0 International License. Open chat