基于机器学习的四旋翼植保机目标识别研究  

Research on Target Recognition of Four Rotor Plant Protection Aircraft Based on Machine Learning

作　　者：魏纯[1] 李明[2] 龙嘉川 姚敏[1] Wei Chun;Li Ming;Long Jiachuan;Yao Min(School of Electronic Information Engineering,Wuhan Donghu University,Wuhan 430212,China;Information Management Center,Air Force Early Warning Academy,Wuhan 430019,China)

机构地区：[1]武汉东湖学院电子信息工程学院,武汉430212 [2]空军预警学院信息管理中心,武汉430019

出　　处：《农机化研究》2023年第12期244-247,共4页Journal of Agricultural Mechanization Research

基　　金：湖北省教育厅科学研究计划项目(B2020241)。

摘　　要：为了提高无人植保机的目标识别能力,提升其在复杂环境下自主化作业的适应性,将机器学习算法引入到了植保机目标自主识别系统的设计上,利用神经网络学习算法和图像增强处理技术提高了识别系统的准确性。模拟植保机的作业环境,在作业区域设置了大量的作物目标,通过植保机对目标物的识别对其性能进行了测试,结果表明:植保机可以准确地识别作物目标,满足自主作业时对目标自主识别的设计需求。In order to improve the target recognition ability of unmanned plant protection machine and its adaptability to autonomous operation in complex environment,the machine learning algorithm is introduced into the design of the target autonomous recognition system of plant protection machine,and the accuracy of the recognition system is improved by using neural network learning algorithm and image enhancement processing technology.Simulate the working environment of the plant protection machine,set a large number of crop targets in the working area,and test its performance through the target recognition of the plant protection machine.The test results show that the plant protection machine can accurately identify the crop targets,so as to meet the design requirements of target independent recognition during independent operation.

关 键 词：无人植保机 四旋翼飞行器 机器学习 神经网络 目标识别 

分 类 号：S252.3[农业科学—农业机械化工程]