CERES
CERES TEST Only!
  • Communities & Collections
  • Browse CERES
  • Library Staff Log In
    New user? Click here to register. Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "Wang, Zijian"

Now showing 1 - 1 of 1
Results Per Page
Sort Options
  • Loading...
    Thumbnail Image
    ItemOpen Access
    Fast personal protective equipment detection for real construction sites using deep learning approaches
    (MDPI, 2021-05-17) Wang, Zijian; Wu, Yimin; Yang, Lichao; Thirunavukarasu, Arjun; Evison, Colin; Zhao, Yifan
    The existing deep learning-based Personal Protective Equipment (PPE) detectors can only detect limited types of PPE and their performance needs to be improved, particularly for their deployment on real construction sites. This paper introduces an approach to train and evaluate eight deep learning detectors, for real application purposes, based on You Only Look Once (YOLO) architectures for six classes, including helmets with four colours, person, and vest. Meanwhile, a dedicated high-quality dataset, CHV, consisting of 1330 images, is constructed by considering real construction site background, different gestures, varied angles and distances, and multi PPE classes. The comparison result among the eight models shows that YOLO v5x has the best mAP (86.55%), and YOLO v5s has the fastest speed (52 FPS) on GPU. The detection accuracy of helmet classes on blurred faces decreases by 7%, while there is no effect on other person and vest classes. And the proposed detectors trained on the CHV dataset have a superior performance compared to other deep learning approaches on the same datasets. The novel multiclass CHV dataset is open for public use.

Quick Links

  • About our Libraries
  • Cranfield Research Support
  • Cranfield University

Useful Links

  • Accessibility Statement
  • CERES Takedown Policy

Contacts-TwitterFacebookInstagramBlogs

Cranfield Campus
Cranfield, MK43 0AL
United Kingdom
T: +44 (0) 1234 750111
  • Cranfield University at Shrivenham
  • Shrivenham, SN6 8LA
  • United Kingdom
  • Email us: researchsupport@cranfield.ac.uk for REF Compliance or Open Access queries

Cranfield University copyright © 2002-2025
Cookie settings | Privacy policy | End User Agreement | Send Feedback