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Characteristics of ten convolutional neural networks used in this study.
| Network | Depth | Parameters (106) | Input Layer Size | Output Layer Size |
|---|---|---|---|---|
| AlexNet | 8 | 61.0 | 60-by-60 | 2-by-1 |
| VGG-16 | 16 | 138 | 60-by-60 | 2-by-1 |
| VGG-19 | 19 | 144 | 60-by-60 | 2-by-1 |
| SqueezeNet | 18 | 1.24 | 60-by-60 | 2-by-1 |
| GoogleNet | 22 | 7 | 60-by-60 | 2-by-1 |
| MobileNet-V2 | 53 | 3.5 | 60-by-60 | 2-by-1 |
| ResNet-18 | 18 | 11.7 | 60-by-60 | 2-by-1 |
| ResNet-50 | 50 | 25.6 | 60-by-60 | 2-by-1 |
| ResNet-101 | 101 | 44.6 | 60-by-60 | 2-by-1 |
| Xception | 71 | 22.9 | 60-by-60 | 2-by-1 |
