Table 18 The result of the second model was initially trained using our dataset which is our W-Net model and then further trained using LISC public data
From: WBC image classification and generative models based on convolutional neural network
| Â | NE. (%) | EO. (%) | BA. (%) | LY. (%) | MO. (%) |
|---|---|---|---|---|---|
Fold-0 | 100 | 100 | 100 | 100 | 80 |
Fold-1 | 100 | 100 | 100 | 100 | 100 |
Fold-2 | 100 | 100 | 100 | 100 | 20 |
Fold-3 | 100 | 100 | 100 | 100 | 100 |
Fold-4 | 100 | 100 | 100 | 100 | 80 |
Fold-5 | 100 | 100 | 100 | 83 | 100 |
Fold-6 | 100 | 100 | 100 | 100 | 100 |
Fold-7 | 100 | 75 | 100 | 100 | 100 |
Fold-8 | 100 | 100 | 80 | 100 | 100 |
Fold-9 | 100 | 100 | 80 | 100 | 100 |
Avr. Acc. | 100 | 98 | 96 | 98 | 88 |