基于迁移学习的MobileViT-CBAM鲜烟叶成熟度识别模型研究

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中图分类号：S572；S126 文献标识码：A文章编号：1007-5119（2025）02-0093-08

1.，青岛266101；2.中国农业科学院研究生院，北京100081；3.江西省烟草公司抚州市公司，江西抚州344000；4.江西省烟草公司吉安市公司，）

MobileViT-CBAM Model for Fresh Tobacco Leaf Maturity Recognition Based on Transfer Learning

ZHAO Panzhen12, WANG Songfeng1*, QI Fei³, HU Qiang³, WANG Aihual, LI Yachun4, MENG Lingfeng1, YIN Dong?, DUAN Shijiang4*, WANG Zhisheng4

(1.InstituteofTobacoResearchofChinese AcademyofAgriculturalSciences/KeyLaboratoryofTobaccoBiologyandProcesing

MinistryofAgricultureandRuralAfairs,Qingdao266101,China;2.GraduateSchoolofChineseAcademyofAgriculturalSciences

Beijing10oo81,Chia;3.FuzhoBranchofJngxiProvincialobaccoompanyuzhou34o,Jangxi,China; 4.Jaach ofJiangxiProvincial Tobacco Company,Ji'an343oo9, Jiangxi, China)

Abstract:Toestablishoreeconomicalandeientodestructiveintelligentrecogitionthnologyfortobaccleafmaturitya lightweight network modelMobileVi-CBAMonmobile devices was constructed.Firstly,adatasetwasbuiltbycolecting imagesof the middle andupper leaves of‘Yunyan87withdiferent maturity.The CBAMatentionmechanismmodule wasintroduced into the MobileViTstructuretancethefatureexpresioabilityoffreshtobaccoleafmaturitymages.econdlyteginalactiation function Swish wasreplaced with thesmoother SMUfunction tohelpthemodelconverge faster.Finaly,transferlearning was employedtoimprovethetrainingeficiencyandgeneralizationabilityof temodelandachievetheclasificatiooffreshtobacoleaf maturity in complex field environment.Results showed that MobileViT-CBAM exhibited an accuracy of 9 2 . 8 1 % inmaturity clasificationoffreshtbacoeaves,wichissignificantlysperiortotemodelsofG16,ResNet4,VisionTrasforin Transformer,MobileNetV2,andMobileViT.TheproposedMobileVi-CBAMmodelcaneectivelyidentifythematurityegreeof tobacco leaves,providing technical support for the visual system of inteligent tobacco harvesting equipment.

(eywords: maturity of tobacco fresh leaf; lightweight; classfication model; attention mechanism

适宜的鲜烟叶成熟度是保证烟叶烘烤质量的必要条件，直接影响烤后烟叶的外观、评吸及香气品质[1-2]。（剩余18309字）