• Laser & Optoelectronics Progress
  • Vol. 59, Issue 24, 2410005 (2022)
Lisha Meng, Xianzhao Yang*, and Huikang Liu
Author Affiliations
  • Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education, School of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan 430081, Hubei, China
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    DOI: 10.3788/LOP202259.2410005 Cite this Article Set citation alerts
    Lisha Meng, Xianzhao Yang, Huikang Liu. Algorithm on Mushroom Image Classification Based on CA-EfficientNetV2[J]. Laser & Optoelectronics Progress, 2022, 59(24): 2410005 Copy Citation Text show less
    MBConv module
    Fig. 1. MBConv module
    Fused-MBConv module
    Fig. 2. Fused-MBConv module
    CA module flowchart
    Fig. 3. CA module flowchart
    Overall framework of the improved EfficientNetV2 network model
    Fig. 4. Overall framework of the improved EfficientNetV2 network model
    Internal structure diagram of main modules of improved EfficientNetV2
    Fig. 5. Internal structure diagram of main modules of improved EfficientNetV2
    Data enhancement results. (a) Original picture; (b) random resize; (c) padding; (d) random rotation; (e) color jitter; (f) random crop
    Fig. 6. Data enhancement results. (a) Original picture; (b) random resize; (c) padding; (d) random rotation; (e) color jitter; (f) random crop
    Accuracy comparison curve of EfficientNetV2 and other networks
    Fig. 7. Accuracy comparison curve of EfficientNetV2 and other networks
    Loss function comparison curve of EfficientNetV2 and other networks
    Fig. 8. Loss function comparison curve of EfficientNetV2 and other networks
    Accuracy comparison curve of EfficientNetV2 network before and after improvement
    Fig. 9. Accuracy comparison curve of EfficientNetV2 network before and after improvement
    Loss function comparison curve of NetworkNetV2 network before and after improvement
    Fig. 10. Loss function comparison curve of NetworkNetV2 network before and after improvement
    Comparison of image visualization results. (a) Input; (b) EfficientNetV2; (c) CA- EfficientNetV2
    Fig. 11. Comparison of image visualization results. (a) Input; (b) EfficientNetV2; (c) CA- EfficientNetV2
    StageOperatorStrideChannelsLayers
    0Conv3×32241
    1Fused-MBConv1,k3×31242
    2Fused-MBConv4,k3×32484
    3Fused-MBConv4,k3×32644
    4MBConv4,k3×3,SE0.2521286
    5MBConv6,k3×3,SE0.2511609
    6MBConv6,k3×3,SE0.25227215
    7Conv1×1&Pooling&FC17921
    Table 1. EfficientNetV2-S structure table
    Experimental parameterScene setting
    Activation functionSiLU/Sigmoid
    Learning initial rate0.01
    Learning decayl rate0.01
    Drop_connect_rate0.2
    Loss functionCross entropy
    Momentum0.9
    Weight_decay1×10-4
    OptimizationSGD
    Batch size32
    Number of iterations150
    Dropout rate0.2
    Activation functionSoftmax
    Table 2. Experimental parameter settings
    StageKernel size /pooling sizeOutput
    Input224×224×3
    Conv3×3112×112×24
    Fused-MBConv3×3112×112×24
    Fused-MBConv3×356×56×48
    Fused-MBConv3×328×28×64
    MBConv3×314×14×128
    MBConv3×314×14×160
    MBConv3×37×7×272
    Ave-pooling3×37×7×272
    Softmax1×11×1×9
    Table 3. Structural parameters of improved EfficientNetV2 model
    ModelAccuracy
    ResNet5086.7
    RegNet91.9
    EfficientNetV293.8
    CA-EfficientNetV296.8
    Table 4. Comparison of classification accuracy for different models
    Lisha Meng, Xianzhao Yang, Huikang Liu. Algorithm on Mushroom Image Classification Based on CA-EfficientNetV2[J]. Laser & Optoelectronics Progress, 2022, 59(24): 2410005
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