Table 1.

Details of the CNN structure used in this research.

Block	Type	Number of neurons	Kernel size for each	Stride
		(Output layer)	Output feature map
Conv 1	Convolution	139 × 20	40	1
	BN	139 × 20	—	—
	ReLU	139 × 20	—	—
	Dropout	139 × 20	—	—
	Max-pooling	70 × 20	2	2
Conv 2	Convolution	51 × 40	20	1
	BN	51 × 40	—	—
	ReLU	51 × 40	—	—
	Dropout	51 × 40	—	—
	Max-pooling	26 × 40	2	2
Conv 3	Convolution	17 × 80	10	1
	BN	17 × 80	—	—
	ReLU	17 × 80	—	—
	Dropout	17 × 80	—	—
	Max-pooling	9 × 80	2	2
FC 1	FC	64	—	—
	ReLU	64	—	—
	Dropout	64	—	—
FC 2	FC	32	—	—
	ReLU	32	—	—
	Dropout	32	—	—
FC 3	FC	2 or 3 or 5	—	—