Table 1 MobileNet body architecture27.
From: Automated stomata detection in oil palm with convolutional neural network
Type/stride | Filter shape | Input size |
|---|---|---|
Conv/s2 | 3 × 3 × 3 × 32 | 224 × 224 × 3 |
Conv dw/s1 | 3 × 3 × 32 dw | 112 × 112 × 32 |
Conv/s1 | 1 × 1 × 32 × 64 | 112 × 112 × 32 |
Conv dw/s2 | 3 × 3 × 64 dw | 112 × 112 × 64 |
Conv/s1 | 1 × 1 × 64 × 128 | 56 × 56 × 64 |
Conv dw/s1 | 3 × 3 × 128 dw | 56 × 56 × 128 |
Conv/s1 | 1 × 1 × 128 × 128 | 56 × 56 × 128 |
Conv dw/s2 | 3 × 3 × 128 dw | 56 × 56 × 128 |
Conv/s1 | 1 × 1 × 128 × 256 | 28 × 28 × 128 |
Conv dw/s1 | 3 × 3 × 256 dw | 28 × 28 × 256 |
Conv/s1 | 1 × 1 × 256 × 256 | 28 × 28 × 256 |
Conv dw/s2 | 3 × 3 × 256 dw | 28 × 28 × 256 |
Conv/s1 | 1 × 1 × 256 × 512 | 14 × 14 × 256 |
\(5\times \genfrac{}{}{0pt}{}{Conv dw/s1 }{Conv/s1}\) | 3 × 3 × 512 dw | 14 × 14 × 512 |
1 × 1 × 512 × 512 | 14 × 14 × 512 | |
Conv dw/s2 | 3 × 3 × 512 dw | 14 × 14 × 512 |
Conv/s1 | 1 × 1 × 512 × 1024 | 7 × 7 × 512 |
Conv dw/s2 | 3 × 3 × 1024 dw | 7 × 7 × 1024 |
Conv/s1 | 1 × 1 × 1024 × 1024 | 7 × 7 × 1024 |
Avg Pool/s1 | Pool 7 × 7 | 7 × 7 × 1024 |
FC /s1 | 1024 × 1000 | 1 × 1 × 1024 |
Softmax /s1 | Classifier | 1 × 1 × 1000 |
