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Table 9 The DeepCryoPicker network architecture

From: DeepCryoPicker: fully automated deep neural network for single protein particle picking in cryo-EM

Layer

Type

Filters

Size

I1

Input layer

–

227 × 227 × 3

P2

Pre-processing

–

227 × 227 × 3

C3

Convolution

96

11 × 11

M4

Max-pooling

–

3 × 3

C5

Convolution

256

5 × 5

M6

Max-pooling

–

3 × 3

C7

Convolution

384

3 × 3

C8

Convolution

384

3 × 3

C9

Convolution

256

3 × 3

M10

Max-pooling

–

3 × 3

F11

Fully connected

–

1 × 4096

F12

Fully connected

–

1 × 4096

O13

Output

–

1 × 1

  1. The convolutional layer and the subsampling layer are abbreviated as C and S, respectively. C3:11 × 11 × 96 means that in the third convolutional layer (C3) is comprised of 96 feature maps, each of which has a size of 11 × 11, also. C3: @27 × 27 means that output feature maps dimensions are 27 × 27 pixels