Table 5 The result of accuracy, precision, recall, F1-score on average and the number of layers for all experiments
From: WBC image classification and generative models based on convolutional neural network
Network | Acc. (%) | Prec. (%) | Rec. (%) | F1. (%) | # of layers |
|---|---|---|---|---|---|
W-Net | 97 | 97 | 97 | 97 | 3 |
W-Net-SVM | 95 | 97 | 95 | 96 | 3 |
AlexNet | 84 | 94 | 84 | 85 | 8 |
VGGNet | 44 | 67 | 44 | 42 | 16 |
ResNet50 | 51 | 60 | 51 | 43 | 50 |
ResNet18 | 79 | 81 | 78 | 77 | 18 |
RNN | 83 | 86 | 85 | 85 | – |