东华大学学报（英文版）2025，Vol.42Issue(4)：417-424,8.DOI:10.19884/j.1672-5220.202406015
DrownACB-YOLO:一种用于游泳池溺水检测的改进YOLO算法
DrownACB-YOLO:an Improved YOLO for Drowning Detection in Swimming Pools
曾小雅 1许武军 2张修念3
作者信息
- 1. 东华大学信息科学与技术学院,上海 201620
- 2. 东华大学信息科学与技术学院,上海 201620||东华大学数字化纺织服装技术教育部工程研究中心,上海 201620
- 3. 联仁健康医疗大数据科技股份有限公司,上海 201200
- 折叠
摘要
Abstract
With the rise in drowning accidents in swimming pools,the demand for the precision and speed in artificial intelligence(AI)drowning detection methods has become increasingly crucial.Here,an improved YOLO-based method,named DrownACB-YOLO,for drowning detection in swimming pools is proposed.Since existing methods focus on the drowned state,a transition label is added to the original dataset to provide timely alerts.Following this expanded dataset,two improvements are implemented in the original YOLOv5.Firstly,the spatial pyramid pooling(SPP)module and the default upsampling operator are replaced by the atrous spatial pyramid pooling(ASPP)module and the content-aware reassembly of feature(CARAFE)module,respectively.Secondly,the cross stage partial bottleneck with three convolutions(C3)module at the end of the backbone is replaced with the bottleneck transformer(BotNet)module.The results of comparison experiments demonstrate that DrownACB-YOLO performs better than other models.关键词
溺水检测/YOLO算法/空洞空间金字塔池化/内容感知特征重组Key words
drowning detection/YOLO/atrous spatial pyramid pooling(ASPP)/content-aware reassembly of feature(CARAFE)分类
信息技术与安全科学引用本文复制引用
曾小雅,许武军,张修念..DrownACB-YOLO:一种用于游泳池溺水检测的改进YOLO算法[J].东华大学学报（英文版）,2025,42(4):417-424,8.
