摘要
传统依靠人工经验的作物病害识别方式难以适应大规模种植环境,迫切需要寻求新的解决方案。近年来,人工智能技术在许多领域取得了丰硕成果,在作物病害识别领域也取得较好的效果。为深入了解人工智能技术在作物病害识别领域中的研究现状,该文主要从传统的机器学习方法和深度学习方法2个角度分析人工智能技术在作物病害识别领域的研究进展,主要包括这2种方法的技术理论、主要工作流程、应用现状及优缺点,同时展望了人工智能技术在未来作物病害识别领域的发展趋势。
Traditional crop disease identification methods that rely on manual experience are not completely suitable for large-scale growing environments,and it is an urgent to find new solutions.In recent years,with the fruitful achievements of artificial intelligence(AI)technologies in many fields,it has been used in crop disease identification and achieved exciting progresses.In order to gain an in-depth understanding of the progresses of AI in crop disease identification tasks,this paper mainly analyzes the application of AI in crop disease identification from two perspectives:conventional machine learning methods and deep learning methods.The technical theory of these methods,main workflow,application status,advantages and disadvantages of the two methods are also investigated respectively.The trend of crop disease identification in the future is also foreseen at the same time.
作者
周长建
宋佳
向文胜
Zhou Changjian;Song Jia;Xiang Wensheng(High-performance Computing and Artificial Intelligence Research Center,Northeast Agricultural University,Harbin 150030,Heilongjiang Province,China;Key Laboratory of Agricultural Microbiology in Heilongjiang Province,Northeast Agricultural University,Harbin 150030,Heilongjiang Province,China;State Key Laboratory for Biology of Plant Diseases and Insect Pests,Institute of Plant Protection,Chinese Academy of Agricultural Sciences,Beijing 100193,China)
出处
《植物保护学报》
CAS
CSCD
北大核心
2022年第1期316-324,共9页
Journal of Plant Protection
基金
国家自然科学基金(32030090)。
关键词
植物保护
病害识别
人工智能
机器学习
plant protection
disease identification
artificial intelligence
machine learning
