Research Article
Improving Accuracy of Lung Nodule Classification Using Deep Learning with Focal Loss
Table 1
Detailed configuration of the proposed deep convolutional neural network architecture.
| | # | Type | Input | Kernel | Output |
| | 1 | Convolutional | | | | | 2 | Convolutional | | | | | 3 | Convolutional | | | | | 4 | Max pooling | | | |
| | 5 | Convolutional | | | | | 6 | Convolutional | | | | | 7 | Convolutional | | | | | 8 | Max pooling | | | |
| | 9 | Convolutional | | | | | 10 | Convolutional | | | | | 11 | Convolutional | | | | | 12 | Max pooling | | | |
| | 13 | Fully connected | | N/A | 512 |
| | 14 | Dropout | 512 | N/A | 512 |
| | 15 | Fully connected | 512 | N/A | 2 |
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