A Lightweight Transformer Model With High-Throughput for Image Compression in 6G-Enabled Intelligent Transportation Systems

In the 6G-enabled intelligent transportation systems (ITS), each intelligent transportation terminal needs to perform long-distance, low-latency image interaction to ensure real-time information exchange, including real-time vehicular environmental images and various vehicular media images. However, due to high computational cost and large computing resource usage, many learning-driven image compression models are difficult to deploy on intelligent transportation terminals such as edge devices a