Table 4.

Description of VGG 16 architecture (C—convolutional layer, P—Max pooling, FC—fully connected).

Layer	Type	Feature Map	Size	Kernel Size	Stride	Activation Function
Input	Image	1	$224\times 224\times 1$	-	-	-
1	$2\times C$	96	$224\times 224\times 64$	$3\times 3$	1	ReLU
	P	64	$112\times 112\times 64$	$3\times 3$	2	-
3	$2\times C$	128	$112\times 112\times 128$	$3\times 3$	1	ReLU
	P	256	$56\times 56\times 128$	$3\times 3$	2	-
5	$2\times C$	256	$56\times 56\times 256$	$3\times 3$	1	ReLU
	P	384	$28\times 28\times 256$	$3\times 3$	2	ReLU
7	$3\times C$	512	$28\times 28\times 512$	$3\times 3$	1	ReLU
	P	256	$14\times 14\times 512$	$3\times 3$	2	-
10	$3\times C$	512	$14\times 14\times 512$	$3\times 3$	1	ReLU
	P	512	$7\times 7\times 512$	$3\times 3$	2	-
13	FC	-	25,088	-	-	ReLU
14	FC	-	4096	-	-	ReLU
15	FC	-	4096	-	-	ReLU
Output	FC	-	4	-	-	Softmax