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A Real-Time Safety Helmet Wearing Detection Approach Based on CSYOLOv3
In the practical scenario of construction sites with extremely complicated working environment and numerous personnel, it is challenging to detect safety helmet wearing (SHW) in real time on the premise of ensuring high precision performance. In this paper, a novel SHW detection model on the basis of improved YOLOv3 (named CSYOLOv3) is presented to heighten the capability of target detection on the construction site. Firstly, the backbone network of darknet53 is improved by applying the crossdoi:10.3390/app10196732 fatcat:6gjqxnm5sveebidwqp2tyahhm4