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Architecture of the deep convolutional neural network.
| Layer | Channels In | Channels Out | Kernel Size | Padding | Stride |
|---|---|---|---|---|---|
| Conv2d | 3 | 8 | 3 × 3 | 1 × 1 | 1 × 1 |
| MaxPool2d | 8 | 8 | 3 × 3 | 0 × 0 | 3 × 3 |
| Conv2d | 8 | 16 | 3 × 3 | 1 × 1 | 1 × 1 |
| MaxPool2d | 16 | 16 | 3 × 3 | 0 × 0 | 3 × 3 |
| Conv2d | 16 | 32 | 3 × 3 | 1 × 1 | 1 × 1 |
| MaxPool2d | 32 | 32 | 3 × 3 | 0 × 0 | 3 × 3 |
| Conv2d | 32 | 64 | 3 × 3 | 1 × 1 | 1 × 1 |
| MaxPool2d | 64 | 64 | 3 × 3 | 0 × 0 | 3 × 3 |
| Conv2d | 64 | 128 | 3 × 3 | 1 × 1 | 1 × 1 |
| MaxPool2d | 128 | 128 | 3 × 3 | 0 × 0 | 3 × 3 |
| Conv2d | 128 | 2 | 1 × 1 | 0 × 0 | 1 × 1 |
