基于改进YOLOv8算法的垂钓活动监测方法OA
A fishing behavior detection method based on an improved YOLOv8 algorithm
为实现对灌区垂钓活动的智能化精准识别,提出一种基于改进 YOLOv8 算法的垂钓活动监测方法.该方法在YOLOv8的骨干网络中添加多尺度特征融合模块(Conv-M),用来学习来自不同卷积层(Conv)的特征,同时利用自学习的权重系数对特征进行加权融合,增强网络对垂钓活动的特征提取能力.通过训练网络得到垂钓活动监测模型,实现对视频图像数据中的垂钓活动进行检测和识别.该方法相较于YOLOv8方法的查准率提高了 1.1%,查全率提高了1.4%,平均识别…查看全部>>
In order to realize the intelligent and accurate identification of fishing behavior in irrigation district,an improved CM-YOLOv8 fishing behavior detection method was proposed. This method added a multi-scale feature fusion module (Conv-M)!to the backbone network of YOLOv8 to learn features from different Conv layers. At the same time,the self-learning weight coefficient was used to weight the features,so as to enhance the ability of the network to extract f…查看全部>>
冯孟雅
安徽省淠史杭灌区管理总局科技信息中心,安徽 六安 237000
计算机与自动化
YOLOv8算法Conv-M数字灌区垂钓活动监管
YOLOv8Conv-Mdigital irrigation districtfishing behavior regulation
《江淮水利科技》 2024 (4)
46-50,5
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