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Table 1 MLES-Net configuration

From: Detecting COVID-19 patients via MLES-Net deep learning models from X-Ray images

MLES-Net40

 

MLES-Net56

 

MLES-Net107

 
  

Conv7-64, stride:2

3 × 3Maxpool, stride:2

   

Input-64

Conv3 × 3

BN1

MLES

ReLU

Conv3 × 3

BN2

MLES

ReLU

Output-64

 × 3

Input-64

Conv1 × 1

BN1

MLES

ReLU

Conv3 × 3

BN2

MLES

ReLU

Conv1 × 1

BN3

MLES

ReLU

Output-256

 × 3

Input-64

Conv1 × 1

BN1

MLES

ReLU

Conv3 × 3

BN2

MLES

ReLU

Conv1 × 1

BN3

MLES

ReLU

Output-256

 × 3

  

SE Module

   

Input-128

Conv3 × 3

BN1

MLES

ReLU

Conv3 × 3

BN2

MLES

ReLU

Output-128

 × 4

Input-128

Conv1 × 1

BN1

MLES

ReLU

Conv3 × 3

BN2

MLES

ReLU

Conv1 × 1

BN3

MLES

ReLU

Output-512

 × 4

Input-128

Conv1 × 1

BN1

MLES

ReLU

Conv3 × 3

BN2

MLES

ReLU

Conv1 × 1

BN3

MLES

ReLU

Output-512

 × 4

  

SE module

   

Input-256

Conv3 × 3

BN1

MLES

ReLU

Conv3 × 3

BN2

MLES

ReLU

Output-256

 × 6

Input-256

Conv1 × 1

BN1

MLES

ReLU

Conv3 × 3

BN2

MLES

ReLU

Conv1 × 1

BN3

MLES

ReLU

Output-1024

 × 6

Input-256

Conv1 × 1

BN1

MLES

ReLU

Conv3 × 3

BN2

MLES

ReLU

Conv1 × 1

BN3

MLES

ReLU

Output-1024

 × 23

  

SE module

   

Input-512

Conv3 × 3

BN1

MLES

ReLU

Conv3 × 3

BN2

MLES

ReLU

Output-512

 × 3

Input-512

Conv1 × 1

BN1

MLES

ReLU

Conv3 × 3

BN2

MLES

ReLU

Conv1 × 1

BN3

MLES

ReLU

Output-2048

 × 3

Input-512

Conv1 × 1

BN1

MLES

ReLU

Conv3 × 3

BN2

MLES

ReLU

Conv1 × 1

BN3

MLES

ReLU

Output-2048

 × 3

  

FC, GAP, GAPFC

   
  

OUTPUT

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