江苏水利Issue(1)：21-25,5.
基于轻量化YOLOv8s模型的无人机河道漂浮物实时检测方法研究
Research on real-time detection method of floating debris in river using UAV based on lightweight YOLOv8s model
王子垚 1王梓源 1钱保如 1陆冠臣 1王海蓉1
作者信息
- 1. 江苏省骆运水利工程管理处,江苏宿迁 223800
- 折叠
摘要
Abstract
To solve the problem of identifying small floating objects in river floating object detection,an improved model combining YOLOv8s,LSKA,and AKConv is proposed.The improved model reduces the parameters of YOLOv8s from 11.1M to 8.3M,and increases mAP50 from 68.0%to 77.9%on the"Chinese Academy of Water Surface Floating Object Dataset".The results show that this method can improve detection accuracy,enhance occlusion recognition ability,make the network more adaptable to complex river environments,effectively enhance the real-time detection capability of UAV in rivers,and provide an efficient solution for water management.关键词
漂浮物识别/无人机/轻量化/实时检测/YOLOv8sKey words
floating debris identification/UAV/lightweight/real-time detection/YOLOv8s分类
信息技术与安全科学引用本文复制引用
王子垚,王梓源,钱保如,陆冠臣,王海蓉..基于轻量化YOLOv8s模型的无人机河道漂浮物实时检测方法研究[J].江苏水利,2025,(1):21-25,5.
