Improving Object Detection and Classification for Autonomous Vehicle in Adverse Weather Conditions

In this research, we address the challenge of detecting vehicles in inclement weather using a YOLO-based algorithm. By applying CNNs, we intend to improve vehicle recognition in difficult conditions including fog and rain, enhancing the safety as well as efficiency of autonomous vehicles. This research lays the groundwork for robust perception systems that can confidently navigate challenging weather scenarios.