基于树莓派和深度学习的茶叶病虫害识别系统
Tea Disease and Pest Recognition System Based on Raspberry Pi and Deep Learning
吴鹏 1刘金兰1
作者信息
- 1. 信阳农林学院,河南 信阳 464000
- 折叠
摘要
为了解决传统茶叶病虫害识别方法存在识别效率低和人工成本高的问题,提出一种基于树莓派和深度学习的茶叶病虫害识别系统.通过将树莓派的便捷性和深度学习的强大特征提取能力相结合,成功克服了传统方法的局限性,实现了对茶叶病虫害的高效准确识别.结果表明,该系统可以针对三种常见的茶叶病虫害进行识别,识别率为90%以上,为茶叶病虫害的精准识别提供了高效可行的解决方案.
Abstract
In order to address the issues of low recognition efficiency and high labor costs associated with traditional methods for identifying tea diseases and pests,a tea disease and pest recognition system based on Raspberry Pi and Deep Learning is proposed.This method combines the convenience of Raspberry Pi with the powerful feature extraction capabilities of Deep Learning,successfully overcoming the limitation of traditional methods and achieving efficient and accurate recognition of tea diseases and pests.The results show that the system can identify three common tea pests and diseases with a recognition rate of over 90%,providing an efficient and feasible solution for accurate identification of tea diseases and pests.
关键词
树莓派/深度学习/病虫害识别Key words
Raspberry Pi/Deep Learning/recognition of tea disease and pest引用本文复制引用
基金项目
信阳农林学院青年教师科研基金(QN2021058)
河南省科技攻关计划(222102210300)
出版年
2024
国家科技期刊平台
NSTL
维普
万方数据