中国农学通报2025，Vol.41Issue(34)：157-164,8.
基于深度学习的雪茄茄衣智能分级模型构建与优选
Construction and Screening of Intelligent Grading Model of Cigar Leaves Based on Deep Learning
摘要
Abstract
This study aims to address the challenges in the cigar leaf grading process in China,where the lack of mature intelligent grading methods has led to a reliance on manual operations,resulting in inefficiency and inconsistent standards.The goal is to ensure the quality of cigar leaf products.The'FX-01'variety,the main cultivar in Longyan,Fujian,was used as the research material,and a dataset of 8637 images covering nine commonly used acquisition grades was collected.Five state-of-the-art deep learning models(Swin,ViT,ResNet,Beit and ConvNext)were employed to develop intelligent grading models for upper,middle,and lower leaves,respectively.The results showed that all models met the requirements for daily response speed,with the ConvNext and ViT models achieving the best performance on the middle leaf test set,with an average accuracy of 93.3%.These findings demonstrate the feasibility of deep learning-based image technology in the intelligent grading of cigar wrapper leaves and provide technical support and theoretical guidance for further system improvement and mobile deployment,laying a foundation for the automation and standardization of cigar production.关键词
雪茄/分级/图像识别/深度学习/模型构建/智能分级模型/ConvNext/视觉Transformer(ViT)Key words
cigar/grading/image recognition/deep learning/model construction/intelligent grading model/ConvNext/vision Transformer(ViT)分类
农业科技引用本文复制引用
杜超凡,汪睿琪,吴天翊,沈翠玉,沈福龙,赖日君,林晓路,马旭东,谢小芳..基于深度学习的雪茄茄衣智能分级模型构建与优选[J].中国农学通报,2025,41(34):157-164,8.基金项目
福建省烟草公司龙岩市公司科技计划项目"雪茄烟和烤烟分级智能化检测技术研究"(LK-2022Y06) （LK-2022Y06）
福建省烟草公司龙岩市公司科技计划项目"雪茄烟发酵过程的微生物作用机制及其工艺调控研究"(LK-2022Y02) （LK-2022Y02）
中国烟草总公司科技计划项目[110202201028(LS-12)]. （LS-12）
