Object Detection YOLO Algorithms and Their Industrial Applications: Overview and Comparative Analysis

Deep-learning-based object detection algorithms play a pivotal role in various domains, including face detection, automatic driving, monitoring security, and industrial production. Compared with the traditional object detection algorithms and the two-stage object detection algorithms, the YOLO (You Only Look Once) series improved the detection speed and accuracy. In addition, the YOLO series of object detection algorithms are widely used in the industrial fields due to their real-time and high-precision characteristics. This work summarizes the main versions of YOLO series algorithms as well as their main improving measures. Furthermore, the following is the analysis of the industrial application fields and some application examples of YOLO series algorithms. Furthermore, this work summarizes the general improvement measures for the industrial applications of the YOLO series algorithms. As for the comparison of these algorithms, this work implements the basic tests for the industrial application performance on different datasets. Finally, the development directions and challenges for YOLO series algorithms are pointed out.