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

doi:10.13304/j.nykjdb.2023.0379

Abstract

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

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

CLC Number:

TP181

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.

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.

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