Table 3.

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

Layer	Type	Feature Map	Size	Kernel Size	Stride	Activation Function
Input	Image	1	$227\times 227\times 1$	-	-	-
1	C	96	$55\times 55\times 96$	$11\times 11$	4	ReLU
	P	96	$27\times 27\times 96$	$3\times 3$	2	-
2	C	256	$27\times 27\times 256$	$5\times 5$	1	ReLU
	P	256	$13\times 13\times 256$	$3\times 3$	2	-
3	C	384	$13\times 13\times 384$	$3\times 3$	1	ReLU
4	C	384	$13\times 13\times 384$	$3\times 3$	1	ReLU
5	C	256	$13\times 13\times 256$	$3\times 3$	1	ReLU
	P	256	$6\times 6\times 256$	$3\times 3$	2	-
6	FC	-	9216	-	-	ReLU
7	FC	-	4096	-	-	ReLU
8	FC	-	4096	-	-	ReLU
Output	FC	-	4	-	-	Softmax