YOLOv5s-gⁿConv: detecting personal protective equipment for workers at height.

ABSTRACT:

Introduction

Falls from height (FFH) accidents can devastate families and individuals. Currently, the best way to prevent falls from heights is to wear personal protective equipment (PPE). However, traditional manual checking methods for safety hazards are inefficient and difficult to detect and eliminate potential risks.

Methods

To better detect whether a person working at height is wearing PPE or not, this paper first applies field research and Python crawling techniques to create a dataset of people working at height, extends the dataset to 10,000 images through data enhancement (brightness, rotation, blurring, and Moica), and categorizes the dataset into a training set, a validation set, and a test set according to the ratio of 7:2:1. In this study, three improved YOLOv5

SUBMITTER: Chen H 

PROVIDER: S-EPMC10569216 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature