Computational Analysis and Deep Learning for Medical Care. Группа авторов
Читать онлайн книгу.
smaller than VGG.
Table 1.5 Various parameters of VGG-16.
| Layer name | Input size | Filter size | Window size | # Filters | Stride/Padding | Output size | # Feature maps | # Parameters |
| Conv 1 | 224 × 224 | 3 × 3 | - | 64 | 1/1 | 224 × 224 | 64 | 1,792 |
| Conv 2 | 224 × 224 | 3 × 3 | - | 64 | 1/1 | 224 × 224 | 64 | 36,928 |
| Max-pooling 1 | 224 × 224 | - | 2 × 2 | - | 2/0 | 112 × 112 | 64 | 0 |
| Conv 3 | 112 × 112 | 3 × 3 | - | 128 | 1/1 | 112 × 112 | 128 | 73,856 |
| Conv 4 | 112 × 112 | 3 × 3 | - | 128 | 1/1 | 112 × 112 | 128 | 147,584 |
| Max-pooling 2 | 112 × 112 | - | 2 × 2 | - | 2/0 | 56 × 56 | 128 | 0 |
| Conv 5 | 56 × 56 | 3 × 3 | - | 256 | 1/1 | 56 × 56 | 256 | 295,168 |
| Conv 6 | 56 × 56 | 3 × 3 | - | 256 | 1/1 | 56 × 56 | 256 | 590,080 |
| Conv 7 | 56 × 56 | 3 × 3 | - | 256 | 1/1 | 56 × 56 | 256 | 590,080 |
| Max-pooling 3 | 56 × 56 | - | 2 × 2 | - | 2/0 | 28 × 28 | 256 | 0 |
| Conv 8 | 28 × 28 | 3 × 3 | - | 512 | 1/1 | 28 × 28 | 512 | 1,180,160 |
| Conv 9 | 28 × 28 | 3 × 3 | - | 512 | 1/1 | 28 × 28 | 512 | 2,359,808 |
| Conv 10 | 28 × 28 | 3 × 3 | - | 512 | 1/1 | 28 × 28 | 512 | 2,359,808 |
| Max-pooling 4 | 28 × 28 | - | 2 × 2 | - | 2/0 | 14 × 14 | 512 | 0 |
| Conv 11 | 14 × 14 | 3 × 3 | - | 512 | 1/1 | 14 × 14 | 512 | 2,359,808 |
| Conv 12 | 14 × 14 | 3 × 3 | - | 512 | 1/1 | 14 × 14 | 512 | 2,359,808 |
| Conv 13 | 14 × 14 | 3 × 3 | - | 512 | 1/1 | 14 × 14 | 512 | 2,359,808 |
| Max-pooling 5 | 14 × 14 | - | 2 × 2 | - | 2/0 | 7 × 7 | 512 | 0 |
| Fully connected 1 | 4,096 neurons |
|