Vehicle Detection

Vehicle detection, aiming to accurately identify and locate vehicles in images or sensor data, is crucial for applications like autonomous driving and intelligent transportation systems. Current research emphasizes improving detection accuracy and robustness under challenging conditions (e.g., poor lighting, occlusion) using various deep learning architectures, including YOLO variants, transformers, and multimodal fusion methods that integrate data from cameras and LiDAR. These advancements are driving progress in real-time object detection, enhancing safety and efficiency in traffic management and autonomous vehicle navigation.