Table 3.
Architectural details of the proposed MitosRes-CNN.
| Layer number | Processing unit | Input | Output | Filters | Filter size | Stride | Zero padding |
|---|---|---|---|---|---|---|---|
| Input layer | Conv2D + BatchNorm2D + Leaky ReLU | 3 × 120 × 120 | 32 × 60 × 60 | 32 | 3 × 3 | 2 | 1 |
| Block 1 | Conv2D + BatchNorm2D | 32 × 60 × 60 | 64 × 60 × 60 | 64 | 1 × 1 | 1 | 1 |
| Conv2D + BatchNorm2D | [[64 × 60 × 60] × 3 + Leaky ReLU] × 3 | 64 × 60 × 60 | 64 | 3 × 3 | 1 | 1 | |
| AvgPool2D | 64 × 60 × 60 | 64 × 30 × 30 | 64 | 3 × 3 | 2 | 1 | |
| Conv2D + BatchNorm2D + Leaky ReLU | 64 × 30 × 30 | 96 × 30 × 30 | 96 | 1 × 1 | 1 | 0 | |
| Block 1 skip connection | Conv2D + BatchNorm2D | 32 × 60 × 60 | 96 × 30x × 30 | 96 | 1 × 1 | 2 | 0 |
| Block 2 | Conv2D + BatchNorm2D | [[96 × 30 × 30] × 3 + Leaky ReLU] × 3 | 96 × 30 × 30 | 96 | 3 × 3 | 1 | 1 |
| AvgPool2D | 96 × 30 × 30 | 96 × 15 × 15 | 96 | 3 × 3 | 2 | 1 | |
| Conv2D + BatchNorm2D + Leaky ReLU | 96 × 15 × 15 | 288 × 15 × 15 | 96 | 1 × 1 | 1 | 0 | |
| Block 2 skip connection | Conv2D + BatchNorm2D | 96 × 30 × 30 | 288 × 15 × 15 | 288 | 1 × 1 | 2 | 0 |
| Block 3 | Conv2D + BatchNorm2D | [[288 × 15 × 15] × 3 + Leaky ReLU] × 2 | 288 × 15 × 15 | 288 | 3 × 3 | 1 | 1 |
| Conv2D + BatchNorm2D | [288 × 15 × 15] × 2 + Leaky ReLU | 288 × 15 × 15 | 288 | 3 × 3 | 1 | 1 | |
| AvgPool2D | 288 × 15 × 15 | 288 × 7 × 7 | 288 | 3 × 3 | 2 | 1 | |
| Conv2D + BatchNorm2D + Leaky ReLU | 288 × 7 × 7 | 512 × 7 × 7 | 512 | 3 × 3 | 1 | 1 | |
| Block 3 skip connection | Conv2D + BatchNorm2D | 288 × 15 × 15 | 512 × 7 × 7 | 512 | 1 × 1 | 2 | 0 |
| Average pooling | AdaptiveAvgPool2D (4 × 4) | ||||||
| Dropout | (p = 0.5) | ||||||
| Dense | Fully Connected | 8192 | 150 | 150 | 1 | – | – |
| Dropout | (p = 0.5) | ||||||
| Batch normalization | Batch normalization 1D | ||||||
| Dense | Fully Connected | 150 | 2 | 2 | 1 | – | – |
| Softmax | |||||||