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近年来,智慧农业已经成为研究的一大热点。研究表明,基于深度学习的图像识别技术应用于智慧农业领域,具有重大的研究意义和发展前景。综述了图像识别技术在智慧农业领域的研究现状,并对图像识别技术中的传统技术和深度学习技术分别进行了总结。分析了深度学习技术在农作物成熟度检测、病虫害检测和障碍物检测方面的研究现状,指出了目前基于深度学习的图像识别技术在智慧农业领域所存在的问题。最后,展望了未来智慧农业的研究方向。
Abstract：In recent years,intelligent agriculture had become a research hotspot.The research has showed that applying deep-learning based image recognition technology in the field of intelligent agriculture holds substan tial research significance and development prospect.The study reviews the current status of research on image recognition technology in the area of intelligent agriculture,su mmarizes the traditional technology and deep learning technology in image recognition technology.It analyzes the research progress of deep learning technology in crops maturity detection,diseases detection,pests detection and obstacle detection,and identifies the current problems of image recognition technology based on deep learning in the field of intelligent agriculture.Finally,the paper discusses the future research direction of intelligent agriculture.
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基本信息:
DOI：10.13990/j.issn1001-3679.2025.01.020
中图分类号:S126;TP18;TP391.41
引用信息:
[1]朱德明,程香平,邱伊健,等.基于深度学习的农作物图像识别技术研究进展[J].江西科学,2025,43(01):154-161.DOI:10.13990/j.issn1001-3679.2025.01.020.
基金信息:
江西省03专项及5G项目(20232ABC03A18); 江西省科学院包干制项目(2023YSBG21016); 江西省科学院新兴交叉学科培育计划项目(2022YXXJC0102)