YOLOv8: Advancements and Innovations in Object Detection

The You Only Look Once (YOLO) algorithm has revolutionized object detection in computer vision. YOLOv8 is the latest iteration of this algorithm, which builds on the successes of its predecessors and introduces several new innovations. This paper provides a comprehensive survey of recent developments in YOLOv8 and discusses its potential future directions. The paper begins by describing the underlying principles of YOLOv8 and how it differs from previous versions. The paper then focuses on the advancements and innovations introduced in YOLOv8 thereby comparing the performance with other versions. We also discuss how these innovations address some of the limitations of previous YOLO versions and enhance the overall performance of the algorithm. Through extensive experimentation and evaluation on benchmark datasets, our findings reveal that YOLO v8 achieves improved accuracy compared to previous versions while maintaining competitive real-time performance. The potential applications of YOLO v8 span various domains, including scene understanding, surveillance, autonomous driving, and robotics. Finally, the paper concludes by discussing the potential future directions of YOLOv8.