CNN Based Approach for Traffic Sign Recognition System

Machine Learning (ML) involves making a machine able to learn and take decisions on real-life problems by working with an efficient set of algorithms. The generated ML models find application in different areas research management. One such field, automotive technology, employs enabled commercialized advanced driver assistance systems (ADAS) which include traffic sign recognition as part. With the increasing demand for intelligence vehicles, advent self-driving cars, it is extremely necessary detect recognize signs automatically through computer technology. For this, neural networks can be applied analyzing images cognitive decision autonomous vehicles. Neural are computing act means performing ML. In this work, convolutional network (CNN) based model built accurately making, when installed driverless