Research on Safety Helmet Detection Method Based on YOLOv11
Abstract：The article trains a safety helmet detection model based on the YOLOv11 algorithm and verifies its superiority in accuracy, model size, and real-time performance compared to other models in the same series through experiments. The results show that the model's mAP reaches 93.6%, and the detection time for a single image is only 2.6 ms. This method can efficiently, accurately, and in real-time detect safety helmets of personnel at engineering sites.
Keywords：Deep LearningObject DetectionEngineering ManagementYOLO Algorithm
Publication Date：2025-08-25
Pages：3( 25-27 )