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Table 10 Architecture of RN

From: Reverse active learning based atrous DenseNet for pathological image classification

Layer

Type

Kernel size & number

1

C

3×3,16

2

MP

2×2

3

C

3×3,32

4

MP

2×2

5

C

3×3,64

6

MP

2×2

7

C

3×3,64

8

MP

2×2

9

C

3×3,128

10

MP

2×2

11

C

3×3,128

12

AP

7×7

13

FC

256

14

FC

4

  1. Pipeline consists of convolution layer(C), max pooling layer(MP), average pooling layer(AP) and fully-connected layer(FC)
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BMC Bioinformatics

ISSN: 1471-2105

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