中国农业大学学报2024，Vol.29Issue(4)：173-183,11.DOI:10.11841/j.issn.1007-4333.2024.04.15
基于群体图像识别的生菜鲜重估算方法研究
Image recognition of lettuce fresh weight through group estimation
摘要
Abstract
The lettuce fresh weight estimation through group images was researched to increase the accuracy of online feedback of lettuce information in optimal control of greenhouse climate.Based on the group and single lettuce images,the decrease of over error was investigated through cancellation of positive and negative errors based on group estimation.The influence of occlusion on estimation accuracy was quantified.The improvement of estimation accuracy was realized by introducing a novel loss function with the method of deep learning.The results showed that:1)Compared with the estimation results of lettuce images in single plant images without occlusion,the determination coefficient(R2)of lettuce fresh weight estimation based on group estimation cropping decreased 0.010 8,the normalized root mean squared error(NRMSE)increased 2.69％,and the mean absolute percentage error(MAPE)decreased 2.36％.Although the estimation was slightly lower,the occlusion of the lettuce group can be close to real production.2)Although there were occlusion issues in group estimation that led to incomplete cropping,the MAPE in group estimation with the cancellation of positive and negative errors was still 3.49％lower than that in single-lettuce estimation.Therefore,group estimation was a better way of providing feedback on lettuce yield.3)Based on a more optimized MAPE,mean squared percentage error(MSPE)of the loss function can be further decreased to 8.46％which satisfied the requirements on the estimation accuracy of a"soft sensor".Considering the reality of greenhouse lettuce production,group estimation is a better way to provide online feedback on lettuce yield to the optimal control of the greenhouse climate.Through optimization methods such as deep learning,the estimation error of lettuce yield can be decreased to within 10％.关键词
群体估算/生菜鲜重/图像识别/深度学习Key words
group estimation/lettuce fresh weight/image recognition/deep learning分类
农业科技引用本文复制引用
徐丹,李硕果,陈晶晶,崔庭源,张义,马浚诚..基于群体图像识别的生菜鲜重估算方法研究[J].中国农业大学学报,2024,29(4):173-183,11.基金项目
山东省重点研发计划项目(2022CXGC020708) （2022CXGC020708）
国家自然科学基金项目(32371998,U20A2020) （32371998,U20A2020）
现代农业产业技术体系项目(CARS-23-D02) （CARS-23-D02）
北京市设施蔬菜创新团队项目(BAIC01-2023) （BAIC01-2023）
