Research review of YOLO series object detection algorithms based on deep learning
With the development of deep learning,YOLO object detection algorithm has become a research hotspot in the field of computer vision.Due to its excellent detection speed and average detection accuracy,YOLO object detection algorithm has been widely used in the field of object detection.The development of YOLO algorithm is discussed in detail.Firstly,starting from the network structure,the principle of YOLOv1-v8 algorithm is sum-marized and analyzed in detail,the loss function of YOLO algorithm,and the improvement measures of each ver-sion are summarized,and the application scenarios of YOLO algorithm are classified,which are mainly divided into three categories:agriculture,transportation and industry.Secondly,the data sets commonly used in YOLO object detection algorithms are analyzed.Finally,based on the characteristics of YOLO algorithm and the latest related literature,the future research direction of YOLO object detection algorithm is proposed.
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