\times 5$, obtained by using $357$ kernels of size $5 \times 5$; Layer 4 contains 201 neurons, obtained by using $10,251$ kernels of size $5 \times 5$; Layer 5 contains 10 neurons for output.

-   Structure D: Layer 1 is the input image, the size is $29 \times 29$; Layer 2 contains $17$ feature maps of size $13 \times 13$, obtained by using $17$ kernels of size $5 \times 5$; Layer 3 contains $71$ feature maps of size $5 \times 5$, obtained by using $1,207$ kernels of size $5 \times 5$; Layer 4 contains 201 neurons, obtained by using $14,271$ kernels of size $5 \times 5$; Layer 5 contains 10 neurons for output.

-   Structure E: Layer 1 is the input image, the size is $33 \times 33$; Layer 2 contains $17$ feature maps of size $5 \times 5$, obtained by using $17$ kernels of size $9 \times 9$; Layer 3 contains $71$ feature maps of size $5 \times 5$, obtained by using $1,207$ kernels of size $5 \times 5$; Layer 4 contains 201 neurons, obtained by using $14,271$ kernels of size $5 \times 5$; Layer 5 contains 10 neurons for output.

The Structure C and D were used by 