The Application of Human Detection Based on YOLOv5

Abstract

Human detection has several possible applications. A well-known example is autonomous driving technology, which incorporates gender recognition and fall detection for the elderly. This study will focus on the principles of these applications, which consist primarily of locating the positions of persons inside an image. It is a crucial piece of technology that protects individuals from danger. To fix this problem, this paper employed the deep learning algorithm, mainly supervised learning, which demands a significant quantity of labeled data. Fortunately, these data sets may be collected via security and in-vehicle cameras. YOLOv5 is a famous object detection algorithm, it can train the detector to operate faster and more precisely, enabling the system to identify any potential dangers instantly, which is considered in this study. The experimental results demonstrated that the employed YOLOv5 method can detect the location of human effectively, which proved the feasibility of the method used in the study.