A Review on YOLOv8 and Its Advancements

Object detection is a crucial task in computer vision that has its application in various fields like robotics, medical imaging, surveillance systems, and autonomous vehicles. The newest version of the YOLO model, YOLOv8 is an advanced real-time object detection framework, which has attracted the attention of the research community. Of all the popular object identification methods and machine-learning models such as Faster RCNN, SSD, and RetinaNet, YOLO is the most popularly known method in terms of accuracy, speed, and efficiency. This research study provides an analysis of YOLO v8 by highlighting its innovative features, improvements, applicability in different environments, and a detailed comparison of its performance metrics to other versions and models.