Autonomous Vehicle Perception

Autonomous vehicle perception focuses on enabling self-driving cars to accurately understand their surroundings using various sensors like cameras, lidar, and radar. Current research emphasizes improving robustness in challenging conditions (e.g., adverse weather, low light) through techniques like image enhancement, sensor fusion (e.g., combining camera and lidar data), and the development of more resilient deep learning models (e.g., using novel activation functions or transformer architectures). This field is crucial for ensuring the safety and reliability of autonomous vehicles, driving advancements in computer vision, sensor technology, and the development of trustworthy AI systems for real-world applications.