Vehicle Pattern Recognition for Car Model Prediction Using Deep Learning

This research predicts car models by using deep learning for vehicle pattern recognition. High recognition accuracy is achieved by the model's analysis of visual indicators specific to each make and model using Convolutional Neural Networks (CNNs) trained on a variety of automobile photos. Roadside surveillance systems can use this prediction model to identify suspect or unregistered vehicles, allowing automated traffic monitoring and improving road safety. The model's versatility ensures that it works well in a variety of circumstances and car models. Its incorporation into real-time monitoring improves law enforcement and traffic control, advancing intelligent transportation systems.