Application and performance comparison of YOLOv5 in industrial vision inspection

As a deep learning industrial vision inspection algorithm, YOLOv5 has strong industrial inspection capabilities. This paper mainly studies the advantages and characteristics of YOLOv5 in industrial inspection, especially its application in object recognition and defect detection, and compares and analyzes the performance of YOLOv5 with other traditional target detection algorithms. The experimental verification of the detection project shows that YOLOv5 has advantages in detection speed and accuracy, which provides a new idea for the research of industrial vision inspection.