Comparative Analysis of YOLOv8 and EfficientDet for Object Detection in Autonomous Vehicles

Object detection is the essential role in autonomous driving. This research examining two object detection models YOLOv8, which is effectively use for its real time performance and EfficientDet is well known for its efficiency with strong reliability. Because to its speed and reliability, YOLOv8 is mostly used in autonomous vehicles. EfficientDet is a strong rival provides better reliability, efficiency and ability of process for various self driving applications, despite being less popular for object detection tasks. This article investigate both models on variety of datasets, emphasizing the efficiency in terms of precision, recall and inference speed. Based on findings, EfficientDet is an ideal option for object identification tasks where accuracy is crucial as it higher sucess YOLOv8 in real time applications as well as outperforming it in terms of accuracy and material efficiency. Even with limited application, EfficientDet offers a lot of potential for potential implementation that require high accuracy object detection.