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Automated traffic sign recognition is an important part of a driver assistance system. In this research work, algorithms are developed using Convolution Neural Network to recognize traffic signs while the camera is in motion.

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SapnaKirad03/Traffic-Sign-Classification-Using-CNN

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Traffic-Sign-Classification-Using-CNN

Automated traffic sign recognition is an important part of a driver assistance system. In this research work, algorithms are developed using Convolution Neural Network to recognize traffic signs while the camera is in motion.

Overview

In this Deep Learning project, we will build a model for the classification of traffic signs available in the image into many categories using a Convolutional neural network(CNN) and Keras library. Dataset is consists of more than 50,000 pictures of various traffic signs(speed limit, crossing, traffic signals, etc.) Around 43 different classes are present in the dataset for image classification. It contains two separate folders, train and test, where the train folder is consists of classes, and every category contains various images.

Code

https://colab.research.google.com/drive/1EH9L6z2gj1tB6BWFudk6XGHVpDLDD0-N?usp=sharing

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Automated traffic sign recognition is an important part of a driver assistance system. In this research work, algorithms are developed using Convolution Neural Network to recognize traffic signs while the camera is in motion.

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