Traffic Sign Recognition and Classification Using Machine Learning and Deep Learning

The recognition and classification of traffic signs hold significant significance within intelligent transportation systems and autonomous vehicles. This task entails the precise and real-time identification and categorization of diverse traffic signs through the There are many different types of neural networks that can be used for traffic sign recognition and classification, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and deep belief networks (DBNs). The choice of which network to use depends on the specific requirements and constraints of the task. The field continues to evolve and advance, with new techniques and approaches being developed to address the challenges and limitations of this task [1].