计算技术与自动化2023，Vol.42Issue(4)：81-84,4.DOI:10.16339/j.cnki.jsjsyzdh.202304014
改进YOLOV5目标检测模型的实时抽烟检测方法
Real-time Smoking Detection Method Based on Improved YOLOV5 Target Detection Model
周翔宇 1曲喜悦 2许杰 1倪文瀚1
作者信息
- 1. 华北水利水电大学,河南郑州 450045
- 2. 哈尔滨工业大学,黑龙江哈尔滨 150001
- 折叠
摘要
Abstract
Real-time detection of smoking targets is difficult to be applied in actual scenes,mainly because the cost of terminal equipment is low,and the amount of model calculation that can be carried is very limited,so it is difficult to give consideration to both accuracy and speed.In view of the above problems,this paper uses the improved YOLOV5 target de-tection model.Its bidirectional feature fusion network(FPN+PAN)is replaced by weighted bidirectional feature pyramid network(BiFPN)to enhance the feature transfer capability of the network.The experimental results show that the YOLOV5s-BiFPN target detection model after replacing the feature network has higher accuracy.The AP0.5 reached 91.7％,and the parameters,calculation and FPS of the model keeps almost constant.Which means that it meets the re-quirements of real-time smoking detection in actual scenes.关键词
实时抽烟检测/YOLOV5/特征融合/BiFPNKey words
real-time smoking detection/YOLOV5/feature fusion/BiFPN分类
信息技术与安全科学引用本文复制引用
周翔宇,曲喜悦,许杰,倪文瀚..改进YOLOV5目标检测模型的实时抽烟检测方法[J].计算技术与自动化,2023,42(4):81-84,4.
