Vehicle Type Classification

Vehicle type classification aims to automatically identify different types of vehicles from various data sources, such as images and audio recordings, for applications in traffic management and autonomous driving. Current research focuses on improving accuracy and efficiency using deep learning models like convolutional neural networks (CNNs) and transformers, often incorporating techniques like multi-task learning, self-supervised learning, and data augmentation to address challenges posed by noisy data and diverse visual conditions. These advancements are crucial for enhancing intelligent transportation systems, enabling more accurate traffic monitoring, and improving the safety and efficiency of autonomous vehicles.