CIB-SE-YOLOv8: Optimized YOLOv8 for Real-Time Safety Equipment Detection on Construction Sites

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Liu, Xiaoyi, Du, Ruina, Tan, Lianghao, Xu, Junran, Chen, Chen, Jiang, Huangqi, Aldwais, Saleh
Format: Preprint
Published: 2024
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866929562760249344
author Liu, Xiaoyi
Du, Ruina
Tan, Lianghao
Xu, Junran
Chen, Chen
Jiang, Huangqi
Aldwais, Saleh
author_facet Liu, Xiaoyi
Du, Ruina
Tan, Lianghao
Xu, Junran
Chen, Chen
Jiang, Huangqi
Aldwais, Saleh
contents Ensuring safety on construction sites is critical, with helmets playing a key role in reducing injuries. Traditional safety checks are labor-intensive and often insufficient. This study presents a computer vision-based solution using YOLO for real-time helmet detection, leveraging the SHEL5K dataset. Our proposed CIB-SE-YOLOv8 model incorporates SE attention mechanisms and modified C2f blocks, enhancing detection accuracy and efficiency. This model offers a more effective solution for promoting safety compliance on construction sites.
format Preprint
id arxiv_https___arxiv_org_abs_2410_20699
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle CIB-SE-YOLOv8: Optimized YOLOv8 for Real-Time Safety Equipment Detection on Construction Sites
Liu, Xiaoyi
Du, Ruina
Tan, Lianghao
Xu, Junran
Chen, Chen
Jiang, Huangqi
Aldwais, Saleh
Computer Vision and Pattern Recognition
Ensuring safety on construction sites is critical, with helmets playing a key role in reducing injuries. Traditional safety checks are labor-intensive and often insufficient. This study presents a computer vision-based solution using YOLO for real-time helmet detection, leveraging the SHEL5K dataset. Our proposed CIB-SE-YOLOv8 model incorporates SE attention mechanisms and modified C2f blocks, enhancing detection accuracy and efficiency. This model offers a more effective solution for promoting safety compliance on construction sites.
title CIB-SE-YOLOv8: Optimized YOLOv8 for Real-Time Safety Equipment Detection on Construction Sites
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2410.20699