Cell Phenotype Classification Based on Joint of Texture Information and Multilayer Feature Extraction in DenseNet

Table 1

The structure details of four used DenseNet versions.

Layers	Output size	DenseNet-121		DenseNet-169		DenseNet-201		DenseNet-264
Convolution	112 × 112	7 × 7 conv., stride 2
Pooling	56 × 56	3 × 3 max pool, stride 2
Dense block (1)	56 × 56	1 × 1 conv; 3 × 3 conv	×6	1 × 1 conv; 3 × 3 conv	×6	1 × 1 conv; 3 × 3 conv	×6	1 × 1 conv; 3 × 3 conv	x6
Transition layer (1)	56 × 56	1 × 1 conv
	28 × 28	2 × 2 average pool, stride 2
Dense block (2)	28 × 28	1 × 1 conv; 3 × 3 conv	×12	1 × 1 conv; 3 × 3 conv	×12	1 × 1 conv; 3 × 3 conv	×12	1 × 1 conv; 3 × 3 conv	×12
Transition layer (2)	28 × 28	1 × 1 conv
	14 × 14	2 × 2 average pool, stride 2
Dense block (3)	14 × 14	1 × 1 conv; 3 × 3 conv	×24	1 × 1 conv; 3 × 3 conv	×32	1 × 1 conv; 3 × 3 conv	×48	1 × 1 conv; 3 × 3 conv	×64
Transition layer (3)	14 × 14	1 × 1 conv
	7 × 7	2 × 2 average pool, stride 2
Dense block (4)	7 × 7	1 × 1 conv; 3 × 3 conv	×16	1 × 1 conv; 3 × 3 conv	×32	1 × 1 conv; 3 × 3 conv	×32	1 × 1 conv; 3 × 3 conv	×48
Classification layer	1 × 1	7 × 7 global average pool
		1000D fully connected, softmax