YOLO-ESCA: A High-Performance Safety Helmet Standard Wearing Behavior Detection Model Based on Improved YOLOv5

• Published in: IEEE access Vol. 12; pp. 23854 - 23868
• Main Authors: Jin, Peijian, Li, Hang, Yan, Weilong, Xu, Jinrong
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Computational modeling; Convolutional neural networks; Datasets; Deep learning; Detection algorithms; Feature extraction; Head; Helmets; Object detection; Object recognition; Occupational safety; Safety; Safety helmets; Safety management; Target detection; Video transmission; YOLO

To solve the problem of workers incorrectly wearing helmets, this study proposes a standard helmet wear detection model, YOLO-ESCA based on improved YOLOv5n. This model can monitor workers' helmet wear in real time via UAVs and other means and automatically reduce video streaming detection resu...