Table 3 Classification layer model configuration
From: Deep convolutional neural network based medical image classification for disease diagnosis
| Â | Configuration | VGG16 | InceptionV3 |
|---|---|---|---|
Training parameter | Training parameter | ||
Model1 | GAPFC(4096) → FC(4096) → Softmax | 18,890,754 | 25,182,210 |
Model2 | GAP → Softmax | 1026 | 4098 |
Model3 | GAP → FC(512) → Dropout(0.5) → FC(256) → Dropout(0.5) → FC(128) → Dropout(0.5) → Softmax | 427,138 | 1,213,570 |
Model4 | GAP → FC(512) → Dropout(0.5) → Softmax | 263,682 | 1,050,114 |
Model5 | GAP → FC(512) → Dropout(0.5)→ FC(512) → Dropout(0.5) → FC(256) → Dropout(0.5) → Softmax | 657,154 | 1,443,586 |