Analysis of target detection algorithms at different stages

Abstract

Target detection as a part of computer vision occupies an important position in the field of recognition. It has seen significant improvements in algorithm performance at every stage. You only look Once (YOLO), for example, seems to have the greatest advantage as a target detection model. It is clear that it only needs to be viewed once to identify the class and location of objects in an image. As YOLO continues to improve, it exhibits even faster and more accurate recognition. This paper discusses the features and advantages shown by the different target detection algorithms at each stage. From the analysis results, YOLO shows more advantages in object detection. YOLO detection is fast and can process streaming video in real-time. Also, the number of false background detections is less than half compared to other algorithms while showing good generalization.