Abstract :

Detection And Recognition Of Traffic Signs Are Very Important And Could Potentially Be Used For Driver Assistance To Reduce Accidents And Eventually In Driverless Automobiles Also Traffic Signs Are Essential Part Of Day To Day Lives. They Contain Critical Information That Ensures The Safety Of All The People. As There Are Number Of Traffic Signs Throughout The World, It Is Almost Impossible For Human Beings To Remember Them And Identity Their Meaning Which Create Huge Traffic Accidents And Human Loss Throughout The World So It Is Important To Establish This Project That Will Remember The Traffic Signs Of All The Country Throughout The World. Traffic Signs Classification Is The Process Of Identifying Which Class A Traffic Sign Belongs To. In This Project With The Help Of Deep Learning, Different Traffic Signs Are Identified And Classified Into Different Categories Which Helps In Reducing Various Traffic Accidents And Also Reduces Human Time To Remember Different Traffic Signs. In This Project, Traffic Sign Recognition Using Convolutional Neural Network (CNN) Is Implemented, The CNN Will Be Trained By Using GTSRB Dataset Of 43 Different Classes Containing 50,000 Images Of Traffic Signs The Results Will Show 94% Accuracy. Keywords— Convolutional Neural Network, Traffic Sign Recognition, Tensor Flow, Keras.

Published:

12-11-2023

Issue:

Vol. 23 No. 11 (2023)

Page Nos:

230-234

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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