TABLE II.

DCNN with eight layers of convolution

Layer	Type Input/Output	Dimensions	Filter Dimensions
0	Input	51 × 51 × 1
1	Conv	48 × 48 × 64	4 × 4 × 1 × 64
2	Conv	46 × 46 × 64	3 × 3 × 64 × 64
3	Conv	44 × 44 × 64	3 × 3 × 64 × 64
4	Max-Pooling	22 × 22 × 64	2 × 2
5	Conv	20 × 20 × 128	3 × 3 × 64 × 128
6	Conv	18 × 18 × 128	3 × 3 × 128 × 128
7	Conv	16 × 16 × 128	3 × 3 × 128 × 128
8	Max-Pooling	8 × 8 × 128	2 × 2
9	Conv	6 × 6 × 512	3 × 3 × 128 × 512
10	Conv	4 × 4 × 512	3 × 3 × 512 × 512
11	Max-Pooling	2 × 2 × 512	2 × 2
12	Full	512	–
13	Dropout	–	–
14	Full	128	–
15	Dropout	–	–
16	Full	2	–
17	LogSoftmax	–	–