基于神经网络的无人机农药喷洒区域智能识别  

Neural Network-Based Intelligent Recognition of Pesticide-Treated Areas for UAV Sprayers

作　　者：郑晓玲[1] 郑永钊 ZHENG Xiaoling;ZHENG Yongzhao(School of Aviation,Liming Vocational University,Quanzhou 362000,China)

机构地区：[1]黎明职业大学航空学院,福建泉州362000

出　　处：《黎明职业大学学报》2023年第2期94-101,共8页Journal of LiMing Vocational University

基　　金：福建省中青年教师教育科研项目(科技类)(JTA220716);黎明职业大学一般项目(LT202106)。

摘　　要：为了减少使用无人机(UAV)进行农药喷洒时存在的过施问题,对无人机喷洒区域的智能识别系统进行研究。该系统基于卷积神经网络模型,将航拍采集的农田图片作为样本进行训练、验证、测试,从识别率和处理时间两个方面出发对模型参数进行寻优。试验结果表明,所建立的智能识别系统的平均识别率为92.3%,单张图像平均处理时间为31 ms,可以在满足无人机硬件条件的约束下,实现对喷洒区域的智能识别。In order to reduce the over-application of pesticide,an intelligent recognition of spraying areas for UAV sprayers was modelled on a convolutional neural network,and trained,verified and tested with farmland images collected from aerial photographs.The model parameters were optimized from the aspects of recognition rates and processing time.The test results showed that the average recognition rate of the intelligent recognition system is 92.3%,and the average processing time of a single image is 31ms.The intelligent recognition of spraying areas can be realized under the constraint of the UAV hardware conditions.

关 键 词：无人机 农药喷洒 智能识别 神经网络 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]