摘要
为提升江河流域水面漂浮垃圾的治理效率,文中以无人机低空遥感技术为基础,借助计算机视觉技术,尤其是卷积神经网络在智能识别中的检测效率和准确性方面的优势,探究了基于无人机低空遥感图像的水面漂浮垃圾识别系统的实现与应用,有效地权衡了系统识别精度和性能,为治污管理和执法提供了依据。
In order to improve the management efficiency of floating garbage on the water surface of river basins,this paper is based on the low-altitude remote sensing technology of drone,with the help of computer vision technology,especially the advantages of convolutional neural networks in the detection efficiency and accuracy of intelligent identification,and explores the implementation and application of the floating garbage identification system based on drone low-altitude remote sensing images.The system effectively weighs the recognition accuracy and performance,and provides a basis for pollution management and law enforcement.
作者
林汤权
LIN Tangquan(Fujian Vocational College of Bioengineering,Fuzhou 350007,China)
出处
《移动信息》
2024年第5期306-308,共3页
MOBILE INFORMATION
基金
2022年福建省中青年教师教育科研项目:基于无人机低空遥感影像的河道垃圾智能识别方法的研究(JAT220636)。
关键词
无人机
漂浮垃圾
卷积神经网络
目标识别系统
Unmanned Aerial Vehicle
Floating garbage
Convolutional neural network
Target identification system