计算机工程与应用2024，Vol.60Issue(11)：298-308,11.DOI:10.3778/j.issn.1002-8331.2307-0003
改进YOLOv5s的地下车库火焰烟雾检测方法
Improved YOLOv5s Flame and Smoke Detection Method for Underground Garage
摘要
Abstract
Aimed at the problems that the traditional underground garage fire detection is not timely and can't give detailed fire information,the target detection is difficult to detect small target smoke and flame,and the accuracy of other smoke and flame detection is low,an improved YOLOv5s underground garage smoke and flame detection algorithm is proposed.Attention mechanism is added to the last C3 module of YOLOv5s backbone network to help the network model extract the multi-scale spatial information and important features of smoke and flame more fully.The Neck part is improved to enhance the ability of feature interaction and small target smoke detection.The convolution module of backbone net-work is improved to improve the ability of smoke and flame feature extraction.WIoU(wise intersection over union)is introduced as a new bounding box loss function to enhance the generalization ability of the model.Soft NMS(soft non-maximum suppression)is introduced to enhance the detection ability of overlapping smoke and flame.Comparative exper-iments are carried out on the self-made smoke and flame data set,and the results show that the weight of the improved model is reduced by 0.2 MB,and the accuracy is improved by 6.8 percentage points,which can meet the requirements of smoke and flame detection in underground garages.关键词
烟火检测/YOLOv5s/注意力机制/小目标烟火检测Key words
smoke and fire detection/YOLOv5s/attention mechanism/small target smoke and flame detection分类
信息技术与安全科学引用本文复制引用
杜辰,王兴,董增寿,王亦雷,江忠浩..改进YOLOv5s的地下车库火焰烟雾检测方法[J].计算机工程与应用,2024,60(11):298-308,11.基金项目
山西省基础研究计划自然科学研究面上项目(202303021211205). （202303021211205）
