Can I read Detection Algorithm of Safety Helmet Wearing Based on Deep Learning on EtoBox?

Detection Algorithm of Safety Helmet Wearing Based on Deep Learning by Li Huang; Qiaobo Fu; Meiling He; Du Jiang; Zhiqiang Hao is a Computer Science article available to read on EtoBox.

What is Detection Algorithm of Safety Helmet Wearing Based on Deep Learning about?

## Abstract In the production and construction of industry, safety accidents caused by unsafe behaviors of staff often occur. In a complex construction site scene, due to improper operations by personnel, huge safety risks will be buried in the entire production process. The use of deep learning algorithms to replace manual monitoring of site safety regulations is a powerful guarantee for sticking to the line of safety in production. First, the improved YOLO v3 algorithm is used to output the predicted anchor box of the target object, and then pixel feature statistics are performed on the anchor box, and the weight coefficients are respectively multiplied to output the confidence of the standard wearing of the helmet in each predicted anchor box area, according to the empirical threshold determine whether workers meet the standards for wearing helmets. Experimental results show that the helmet wearing detection algorithm based on deep learning in this paper increases the feature map scale, optimizes the prior dimensional algorithm of specific helmet dataset, and improves the loss function, and then combines image processing pixel feature statistics to accurately detect whether the

Who reads Detection Algorithm of Safety Helmet Wearing Based on Deep Learning?

Author

Li Huang; Qiaobo Fu; Meiling He; Du Jiang; Zhiqiang Hao

Publisher

Wiley

Published

2021

Language

EN

Field

Computer Science (Physical Sciences)