Traffic Sign Classification

Authors : Koushik Reddy Parukola

Volume/Issue : Volume 6 - 2021, Issue 6 - June

Google Scholar :

Scribd :

Traffic Sign Recognition is an intelligent system built based on computer vision and neural networks for detecting, classifying and recognizing traffic signs. This system is so accurate in detecting the signs given as it is trained using the power of deep learning. This system requires huge amount of data for good and accurate output. In this system there are 43 classes of traffic signs with thousands of images, and this system is pre trained using convolutional neural networks (CNN) which has accuracy above 90% in detecting images. After training the system images will be given using the camera as input, which are further preprocessed in different ways which are then passed to the convolutional neural network for detection. The final result is given to the user with the accuracy above 95% along with the name of the sign with the help of data classes the data classes.

Keywords : Traffic Sign Detection, Deep Learning, Computer Vision, Convolutional Neural Network, Numpy, Keras, Tensorflow.


Paper Submission Last Date
31 - October - 2021

Paper Review Notification
In 1-2 Days

Paper Publishing
In 2-3 Days

Never miss an update from Papermashup

Get notified about the latest tutorials and downloads.

Subscribe by Email

Get alerts directly into your inbox after each post and stay updated.

Subscribe by RSS

Add our RSS to your feedreader to get regular updates from us.