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. 2022 Mar 8;10(3):494. doi: 10.3390/healthcare10030494

Table 5.

Summary of the optimized model.

Layer Type Kernel Attribute Number of Filters Feature Map Size
Image Input Layer 64 × 64 × 1
Main
Block 1
Convolutional Layer 3 × 3 × 1, stride 1, padding = same 32 64 × 64 × 32
Tanh Layer 64 × 64 × 32
Max-Pooling Layer 2 × 2, stride 2, no padding 64 × 64 × 32
Main
Block 2
Convolutional Layer 3 × 3 × 32, stride 1, padding = same 64 32 × 32 × 64
Tanh Layer 32 × 32 × 64
Max-Pooling Layer 2 × 2, stride 2, no padding 16 × 16 × 64
Main
Block 3
Convolutional Layer 3 × 3 × 64, stride 1, padding = same 64 16 × 16 × 64
Tanh Layer 16 × 16 × 64
Max-Pooling Layer 2 × 2, stride 2, no padding 8 × 8 × 64
Main
Block 4
Convolutional Layer 3 × 3 × 64, stride 1, padding = same 128 8 × 8 × 128
Tanh Layer 8 × 8 × 128
Max-Pooling Layer 2 × 2, stride 2, no padding 4 × 4 × 128
Main
Block 5
Convolutional Layer 3 × 3 × 128, stride 1, padding = same 256 4 × 4 × 256
Tanh Layer 4 × 4 × 256
Max-Pooling Layer 2 × 2, stride 2, no padding 2 × 2 × 256
Classification
Block
Fully Connected Layer 32
Tanh Layer
Dropout
Fully Connected Layer 3
Softmax