From: Detecting COVID-19 patients via MLES-Net deep learning models from X-Ray images
MLES-Net40 | Â | MLES-Net56 | Â | MLES-Net107 | Â |
---|---|---|---|---|---|
 |  | 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 |  |  |  |