Study on cone yarn category recognition method based on SimAM-ResNet18 | International Journal for Simulation and Multidisciplinary Design Optimization (IJSMDO)

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Table 3

Structural parameters of the ResNet18.

Layer name	Network structure
Input layer	–
Convolutional layer	7×7,64
Pooling layer	3×3,64
Residual layer 1, 2, 3, 4	$[\begin{array}{l} 3 \times 3, 64 \\ 3 \times 3, 64 \end{array}] \times 2, [\begin{array}{l} 3 \times 3, 128 \\ 3 \times 3, 128 \end{array}] \times 2 [\begin{array}{l} 3 \times 3, 256 \\ 3 \times 3, 256 \end{array}] \times 2, [\begin{array}{l} 3 \times 3, 512 \\ 3 \times 3, 512 \end{array}] \times 2$
Pooling layer	512×7×7
Fully connected layer	512×1×1,1000

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