Research and model training of helmet recognition algorithm based on deep learning

被引：0

作者：

Zeng J. ^{[1
]}

Wen B. ^{[1
]}

Liang Z. ^{[1
]}

机构：

[1] Guangdong Power Grid Co., Ltd., Guangzhou

来源：

Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | 2021年 / 49卷 / 21期

关键词：

Deep learning; Model training; Safety helmet; YOLO3; algorithm;

D O I：

10.19783/j.cnki.pspc.210104

中图分类号：

学科分类号：

摘要：

There is a problem of workers who don't wear safety helmets as required as well as non-operating personnel entering a job site by mistake. Thus a deep learning-based safety helmet and voice recognition intelligent terminal algorithm is designed. First, for the detection of helmets, we use a human body key point detection model and a YOLO3 algorithm based on deep learning. The video file obtained by the smart camera is first used to extract the images of the on-site personnel using the human body key point model, and then the YOLO3 algorithm is applied to detect the situation of the on-site workers wearing helmets and send out warning messages for those who do not wear the helmet correctly. Finally, the practicality of the proposed model is verified through model training. © 2021 Power System Protection and Control Press.

引用

页码：107 / 112

页数：5

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