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Fig. 2 | Plant Methods

Fig. 2

From: Classification of multi-year and multi-variety pumpkin seeds using hyperspectral imaging technology and three-dimensional convolutional neural network

Fig. 2

Model structure diagram of PA-3DCNN. The model consisted of 2 double convolution and pooling structures, the position attention module, fully connected layers, etc. Conv3D referred to the three-dimensional convolution operation. C1–C4 referred to the first to fourth convolutional layers. M1–M2 referred to the first and second pooling layers. A–E, S were the code names of the feature maps in the position attention module. Before @ was the number of feature maps, after which was the size of the feature map. Specific details were described in the paper

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Plant Methods

ISSN: 1746-4811