Perception
The future of perception research involves the integration of advanced technologies, improved data processing, and a strong emphasis on ethical considerations. These advancements are set to boost the functionality and reliability of perception systems across various fields, including autonomous vehicles and smart cities. Our team specializes in deep learning methods for object detection and image segmentation and Generative AI for creating realistic media and urban scenes. A significant focus of our study is green learning, which aims to minimize AI's environmental impact by improving energy efficiency and resource utilization and developing lightweight models. Additionally, our research explores multi-object detection and tracking using sophisticated algorithms to identify and monitor multiple objects in real-time, which is crucial for autonomous driving, robotics, and surveillance or monitoring applications. We also investigate sensor fusion techniques to combine data from various sources, enabling a comprehensive understanding of the environment and its context.
