 This paper proposes using deep learning-based classification and detection algorithms to detect vehicles in intelligent transportation systems. It uses transfer learning to improve the accuracy of existing models by fine-tuning them with datasets containing images and videos of traffic patterns. The paper finds that this approach outperforms traditional methods in terms of accuracy and execution speed. This article was authored by Anam Farid, Farhan Hussain, Kuram Khan and others.