Research Overview of YOLO Series Object Detection Algorithms Based on Deep Learning

In the rapid development of deep learning, YOLO, as the first popular single-stage object detection model, has sparked an innovative storm in the computer vision community with its remarkable architecture and innovative concepts, marking a significant leap forward in object detection technology. Today, it is not only regarded as a milestone in this field but also sets an unparalleled example in the pursuit of the perfect fusion of detection speed and accuracy. YOLO has been widely applied in various fields such as agriculture, industry, pedestrian detection, and more. This research project will first introduce traditional object detection methods, then analyze object detection based on deep learning, and subsequently elaborate on the fundamental concepts of YOLO. It will systematically sort through the YOLO family and its significant improvements. Finally, based on different improvement strategies or application scenarios, the YOLO algorithm will be systematically classified and summarized.