中图分类号： TN919.8；TP391.41 文献标识码： A DOI：10.16157/j.issn.0258-7998.200109 中文引用格式： 刘欣，张灿明. 基于卷积神经网络的矿井安全帽佩戴检测[J].电子技术应用，2020，46(9)：38-42，46. 英文引用格式： Liu Xin，Zhang Canming. Wearing safety helmet detection based on convolutional neural networks for mines[J]. Application of Electronic Technique，2020，46(9)：38-42，46.
Wearing safety helmet detection based on convolutional neural networks for mines
Liu Xin，Zhang Canming
Anhui Academy of Coal Science，Hefei 230001，China
Abstract： In the production of coal mines, accidents happen to workers once in a while because of absence of safety helmet. In order to establish digital safety helmet detection system, a wearing safety helmet detection model based on convolutional neural networks is proposed. Specifically, the model is based on advanced Darknet53 as model backbone, which is used to extract feature information from pictures. In addition, attention mechanism is introduced to enrich the propagation of information between features, enhancing the generalization of model. Finally, a wearing safety helmet pre-training dataset and a real mine scene dataset are built, and comprehensively comparative experiments are conducted on PyTorch platform to verify the effectiveness of the model designs, which achieves an excellent performance of 92.5 mAP on the real mine scene dataset.