Table 7.

Layer structure of the LeNet-5 “deep learning” CNN employed in this investigation. Sizes refer to pixels for layers 1–7, variables for layers 8–10

Layers	Type	Parameters
		Image
1	Input	3-tensor (size 1 × 28 × 28)
2	Convolution	3-tensor (size 10 × 25 × 25)
3	Ramp	3-tensor (size 10 × 25 × 25)
4	Pooling	3-tensor (size 10 × 12 × 12)
5	Convolution	3-tensor (size 20 × 9 × 9)
6	Ramp	3-tensor (size 20 × 9 × 9)
7	Pooling	3-tensor (size 20 × 4 × 4)
8	Flatten	Vector (size 320)
9	Linear	Vector (size 2)
10	Output	Vector (size 2)