Traffic Sign Detection using Yolo v5
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Published:2023-05-31
Issue:5
Volume:11
Page:2679-2683
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ISSN:2321-9653
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Container-title:International Journal for Research in Applied Science and Engineering Technology
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language:
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Short-container-title:IJRASET
Author:
Gore Shubham,Bhasin Manan,S Suchitra
Abstract
Abstract: One of the crucial areas of research in the field of advanced driver assistance systems (ADAS) is the detection and recognition of traffic signals in a real-time environment. These are specifically developed to work in real-time to improve road safety by informing the driver of various traffic signals such as speed limits, priorities, restrictions, and so on. This research paper proposes a traffic sign identification system on an Indian dataset utilizing the YOLOv5 model. This study suggests a method for detecting a particular set of 10 traffic signs. You Only Look Once (YOLO) v5 is the algorithm used to detect traffic signs, and the model parameters are trained on train sets obtained from the recently constructed dataset. The remaining images from the dataset are utilized to create a test set. When tested on the test set made from the suggested dataset, the proposed approach for detecting a particular set of traffic signs performs admirably
Publisher
International Journal for Research in Applied Science and Engineering Technology (IJRASET)
Subject
General Earth and Planetary Sciences,General Environmental Science
Cited by
2 articles.
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1. Integrated Life Saving Solution for Free Movement of Ambulance in Heavy Traffic Using YOLOV8;2024 International Conference on Communication, Computer Sciences and Engineering (IC3SE);2024-05-09
2. YOLOv8 based Traffic Signal Detection in Indian Road;2023 7th International Conference on Electronics, Materials Engineering & Nano-Technology (IEMENTech);2023-12-18