计算机视觉与深度学习技术在烟叶生产上的研究进展

doi:10.13304/j.nykjdb.2023.0379

中国农业科技导报 ›› 2025, Vol. 27 ›› Issue (1): 96-106.DOI: 10.13304/j.nykjdb.2023.0379

计算机视觉与深度学习技术在烟叶生产上的研究进展

邢卓冉¹(), 丁松爽², 张凯², 马明³, 郭文龙⁴, 刘旭东⁵, 时向东¹()

^1.河南农业大学，烟草行业烟草栽培重点实验室，郑州 450002
^2.河南农业大学烟草学院，郑州 450002
^3.中国烟草总公司郑州烟草研究院，郑州 450001
^4.湖南省烟草公司永州市公司，湖南永州 425000
^5.湖南省烟草公司怀化市公司麻阳苗族自治县分公司，湖南麻阳 419400

收稿日期:2023-05-16 接受日期:2023-08-01 出版日期:2025-01-15 发布日期:2025-01-21
通讯作者: 时向东
作者简介:邢卓冉E-mail：1024540693@qq.com；
基金资助:
国家自然科学基金项目(32101851);永州阳明雪茄烟综合研究与开发项目(yz2022KJ01)

Research Progress of Deep Learning and Computer Vision in Tobacco Leaf Production

Zhuoran XING¹(), Songshuang DING², Kai ZHANG², Ming MA³, Wenlong GUO⁴, Xudong LIU⁵, Xiangdong SHI¹()

^1.Key Laboratory of Tobacco Cultivation in Tobacco Industry，Henan Agricultural University，Zhengzhou 450002，China
^2.Tobacco College，Henan Agricultural University，Zhengzhou 450002，China
^3.Zhengzhou Tobacco Research Institute，China National Tobacco Corporation，Zhengzhou 450001，China
^4.Yongzhou Tobacco Company of Hunan Province，Hunan Yongzhou 425000，China
^5.Mayang Miao Autonomous County Branch of Huaihua Tobacco Company of Hunan Province，Hunan Mayang 419400，China

Received:2023-05-16 Accepted:2023-08-01 Online:2025-01-15 Published:2025-01-21
Contact: Xiangdong SHI

摘要/Abstract

摘要：

计算机视觉与深度学习技术在众多场景（如物体识别，图像分类）取得了显著进展，近年来这项技术在烟叶生产中展现出广泛的应用空间与发展潜力。综述了计算机视觉与深度学习技术在烟叶生产上的应用现状，重点讨论了其在解决烟叶病害识别、烟叶采收调制、烟叶分级等问题方面的方法。通过分析不同的算法及其在烟叶生产关键阶段的运用，并考虑这项技术在烟叶生产领域所面临的挑战与发展方向，为智能化烟叶生产提供理论支持和参考。

关键词: 计算机视觉, 深度学习, 卷积神经网络, 烟草, 应用

Abstract:

Significant progress has been made in computer vision and deep learning technologies in various scenarios，such as object recognition and image classification，and showed extensive applicability and development potential in tobacco production in recent years. The current state of applications of computer vision and deep learning technologies in tobacco production were reviewed，with a particular focus on their methods and means to solve problems in tobacco disease recognition，tobacco harvesting and curing， and tobacco grading. By analyzing different algorithms and their application in key stages of tobacco production，and considering the challenges and development directions this technology faces in the field of tobacco production，theoretical support and references were provided for intelligent tobacco production.

Key words: computer vision, deep learning, convolution neural network, tobacco, application

中图分类号:

TP181

邢卓冉, 丁松爽, 张凯, 马明, 郭文龙, 刘旭东, 时向东. 计算机视觉与深度学习技术在烟叶生产上的研究进展[J]. 中国农业科技导报, 2025, 27(1): 96-106.

Zhuoran XING, Songshuang DING, Kai ZHANG, Ming MA, Wenlong GUO, Xudong LIU, Xiangdong SHI. Research Progress of Deep Learning and Computer Vision in Tobacco Leaf Production[J]. Journal of Agricultural Science and Technology, 2025, 27(1): 96-106.

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计算机视觉与深度学习技术在烟叶生产上的研究进展

Research Progress of Deep Learning and Computer Vision in Tobacco Leaf Production

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