Table 1:
VGG-16 Architecture. For this study, block 6 is removed and features are extracted after the final max pooling layer.
| Block | Layer | Size | Filter Size |
|---|---|---|---|
|
| |||
| 1 | Convolution-1 | 224×224×64 | 3×3 |
| Convolution-2 | 224×224×64 | 3×3 | |
| Max pooling | 112×112×64 | - | |
|
| |||
| 2 | Convolution-1 | 112×112×128 | 3×3 |
| Convolution-2 | 112×112×128 | 3×3 | |
| Max pooling | 56×56×128 | - | |
|
| |||
| 3 | Convolution-1 | 56×56×256 | 3×3 |
| Convolution-2 | 56×56×256 | 3×3 | |
| Convolution-3 | 56×56×256 | 3×3 | |
| Max pooling | 28×28×256 | - | |
|
| |||
| 4 | Convolution-1 | 28×28×512 | 3×3 |
| Convolution-2 | 28×28×512 | 3×3 | |
| Convolution-3 | 28×28×512 | 3×3 | |
| Max pooling | 14×14×512 | - | |
|
| |||
| 5 | Convolution-1 | 14×14×512 | 3×3 |
| Convolution-2 | 14×14×512 | 3×3 | |
| Convolution-3 | 14×14×512 | 3×3 | |
| Max pooling | 7×7×512 | - | |
|
| |||
| 6 | Flatten | 25,088 | |
| Dense | 4,096 | ||
| Dense | 4,096 | ||
| Dense | 1,000 | ||