Comparative Analysis of YOLO Models for Autonomous Vehicle Perception

This paper provides a comparative analysis of YOLO-NAS and YOLOv8 models for object detection in autonomous vehicles, a crucial task for safe navigation. The study's value lies in its practical evaluation using a custom dataset and its focus on comparing the performance of these specific, relatively new, deep learning models. The findings offer insights into training time and accuracy, which are critical considerations for researchers and developers in the field.