Convolutional Neural Networks

A convolutional Neural Network is a Deep Learning network used to pick up features from the image. Initially, they take the input images and then find out the lines, gradients, shapes, and borders from the image. 

Then further, Convolutional Layers help in processing the outputs to capture eyes, faces, etc. CNN contains many convolutional layers assembled on top of each other, each one competent of recognizing more sophisticated shapes. With two or three convolutional layers it is viable to recognize handwritten digits and with 25 layers it is possible to differentiate human faces.

We always come across incidents of accidents where drivers’ Overspeed or lack of vision leads to major accidents. In winter, the risk of road accidents has a 40-50% increase because of the traffic signs’ lack of visibility. So here in this article, we will be implementing Traffic Sign recognition using a Convolutional Neural Network. It will be very useful in Automatic Driving Vehicles.