Table 5.

The deep convolutional spiking neural network architectures for a CIFAR-10 dataset.

VGG9				ResNet9				ResNet11
Layer type	Kernel size	#o/p feature-maps	Stride	Layer type	Kernel size	#o/p feature-maps	Stride	Layer type	Kernel size	#o/p feature-maps	Stride
Convolution	3 × 3 × 3	64	1	Convolution	3 × 3 × 3	64	1	Convolution	3 × 3 × 3	64	1
Convolution	64 × 3 × 3	64	1	Average-pooling	2 × 2		2	Average-pooling	2 × 2		2
Average-pooling	2 × 2		2
Convolution	64 × 3 × 3	128	1	Convolution	64 × 3 × 3	128	1	Convolution	64 × 3 × 3	128	1
Convolution	128 × 3 × 3	128	1	Convolution	128 × 3 × 3	128	1	Convolution	128 × 3 × 3	128	1
Average-pooling	2 × 2		2	Skip convolution	64 × 1 × 1	128	1	Skip convolution	64 × 1 × 1	128	1
Convolution	128 × 3 × 3	256	1	Convolution	128 × 3 × 3	256	1	Convolution	128 × 3 × 3	256	1
Convolution	256 × 3 × 3	256	1	Convolution	256 × 3 × 3	256	2	Convolution	256 × 3 × 3	256	2
Convolution	256 × 3 × 3	256	1	Skip connection	128 × 1 × 1	256	2	Skip convolution	128 × 1 × 1	256	2
Average-pooling	2 × 2		2
				Convolution	256 × 3 × 3	512	1	Convolution	256 × 3 × 3	512	1
				Convolution	512 × 3 × 3	512	2	Convolution	512 × 3 × 3	512	1
				Skip convolution	256 × 1 × 1	512	2	Skip convolution	512 × 1 × 1	512	1
								Convolution	512 × 3 × 3	512	1
								Convolution	512 × 3 × 3	512	2
								Skip convolution	512 × 1 × 1	512	2
Fully-connected		1024		Fully-connected		1024		Fully-connected		1024
Output		10		Output		10		Output		10