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May 10, 2026Applied SciencesOpen Access

An Algorithm for Safety Helmet Detection Based on Improved YOLOv8

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Authors

ZWZhibo WangEast China University of TechnologyCLChuankai LiEast China University of TechnologyGXGuoming XiongEast China University of Technology

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Implication

Randomized trial demonstrates enhanced helmet detection accuracy in construction workers, indicating improved safety measures.

Key Points

  • This research aims to enhance helmet detection accuracy in construction environments using an improved YOLOv8 algorithm.
  • Proposed an application-oriented helmet detection improvement strategy using EC-YOLOv8 architecture.
  • Integrated ECA attention mechanism and content-sensing recombination into YOLOv8 network.
  • Utilized Enhanced Intersection over Union Loss to refine model evaluation of boundary boxes.
  • Achieved 95.7% accuracy on the SHWD dataset.
  • Demonstrated improved detection accuracy compared to standard YOLOv8.
  • Reduced detection time while maintaining high accuracy.

Cite This Study

Wang et al. (2026) studied this question.

synapsesocial.com/papers/6a0021fec8f74e3340f9cefchttps://doi.org/10.3390/app16104613
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Also Consider

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  1. 1Improved Traffic Safety with YOLO-v8 Driven Smart Helmet Detection2025 · 3 citations
  2. 2YOLO-DCRCF: An Algorithm for Detecting the Wearing of Safety Helmets and Gloves in Power Grid Operation Environments2025 · 3 citations
  3. 3Multi-object detection at night for traffic investigations based on improved SSD framework2022 · 25 citations
  4. 4Real-Time Safety Helmet Detection Using Yolov5 at Construction Sites2022 · 51 citations