Table 1.

This is the network configuration of the proposed architecture (MFFN).

Layers	Output Size	Multiple Feature Fusion Network
Input Layer	224 × 224 × 3	--
Convolution	112 × 112 × 64	filtersize: [7,7], numfilters: 64, stride 2, padding: [3,3,3,3]
BN	112 × 112 × 64	channels: 64
ReLu	112 × 112 × 64	--
Pooling	56 × 56 × 64	[3,3] max pool, stride: [2,2]
Dense Block (1)	56 × 56 × 256	[BN, ReLu, 1 × 1 conv, BN, ReLu, 3 × 3 conv] × 6
Transition Layer (1)	56 × 56 × 256	BN
	56 × 56 × 256	ReLu
	56 × 56 × 128	[1,1] conv
	28 × 28 × 128	[2,2] average pool, stride 2
Dense Block (2)	28 × 28 × 512	[BN, ReLu, 1 × 1 conv, BN, ReLu, 3 × 3 conv] × 12
Transition Layer (2)	28 × 28 × 512	BN
	28 × 28 × 512	ReLu
	28 × 28 × 256	[1,1] conv
	14 × 14 × 256	[2,2] average pool, stride 2
Classification Layer	1024 × 1	1024 × 50,176 RBM
	1500 × 1	1500 × 1024 RBM
	12 × 1	12D Fully Connected, softmax