计算机应用与软件2024，Vol.41Issue(12)：255-260,302,7.DOI:10.3969/j.issn.1000-386x.2024.12.036
一种改进的YOLOv5视频火焰实时检测算法
AN IMPROVED YOLOV5 VIDEO REAL-TIME FLAME DETECTION ALGORITHM
摘要
Abstract
For indoor and outdoor fire prevention,many present algorithms for small target fire detection are lack of accuracy,and can not detect in real time,so an improved YOLOv5 algorithm is proposed.The algorithm widened the number of head layers and introduced selayer layer to accelerate the convergence of classification detection and get more abundant sampling information.The accuracy of the improved algorithm was greatly improved.After the optimization of video stream,the flame could be detected in real time.The experimental results show that the accuracy rate of the improved YOLOv5 model reaches 80.4%,the recall rate reaches 91.3%,and the detection speed reaches 44 frames per second.关键词
卷积神经网络/小目标检测/视频流优化Key words
Convolutional neural network/Small target detection/Video stream optimization分类
信息技术与安全科学引用本文复制引用
张智,冯双文..一种改进的YOLOv5视频火焰实时检测算法[J].计算机应用与软件,2024,41(12):255-260,302,7.基金项目
国家自然科学基金项目(61673304) （61673304）
国家社会科学基金重大计划项目(11&ZD189). （11&ZD189）
