Intelligent Grading of Flue-cured Tobacco Based on VGG16-DenseNet Integrated Model
Aiming to achieve intelligent recognition of flue-cured tobacco leaves grade quickly and accurately,the images of front and back tobacco leaves were taken by mobile phone,and a new model(VGG16-Dense)integrated with VGG16 and DenseNet was constructed.The validity of the model was verified by using twenty-four types of front and back leaf images of cv.Cuibi-1 and Yunyan87.The model was also compared with five other network models,i.e.DenseNet121,ResNet50,AlexNet,VGG16 and GoogLeNet.The results shows that excellent values appeared in all evaluation indicators(accuracy,precision,recall,F1-score and avg-loss)of validation set for VGG16-Dense,and the evaluation indicators of test set for VGG16-Dense performed optimal compared with that of other network models.VGG16-Dense exhibited superior generalization ability and fewer misjudgments,with the accuracy,precision recall,F1-score,and avg-loss reaching 92.71%,93.07%,92.71%,92.72%,and 0.22,respectively.VGG16-DENSE network model can intelligently distinguish the grade,the front and back,and the species for flue-cured tobacco leaves at the same time.This provides a theoretical guidance for the intelligentized grading of primary flue-cured tobacco acquisition.
intelligent grading of flue-cured tobaccodeep learningintegrated with network modelSE module
国家科技期刊平台
NSTL
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