Table 2 Network structure of the proposed method. The basic block is engaged from ResNet18 [20]
From: Using deep learning to predict the outcome of live birth from more than 10,000 embryo data
Layer | Filter Size | Output Size |
|---|---|---|
Conv1_x | 7 × 7, 64 3 × 3, 64 3 × 3, 128, stride 2 | 224 × 224 224 × 224 112 × 112 |
Conv2_x | \(\left[\begin{array}{c}3\times 3,128\\ {}3\times 3,128\end{array}\right]\times 3\) 3 × 3, 256, stride 2 | 112 × 112 56 × 56 |
Conv3_x | \(\left[\begin{array}{c}3\times 3,256\\ {}3\times 3,256\end{array}\right]\times 3\) 3 × 3, 512, stride 2 | 56 × 56 28 × 28 |
Conv4_x | \(\left[\begin{array}{c}3\times 3,512\\ {}3\times 3,512\end{array}\right]\times 3\) 3 × 3, 1024, stride 2 | 28 × 28 14 × 14 |
Conv5_x | \(\left[\begin{array}{c}3\times 3,1024\\ {}3\times 3,1024\end{array}\right]\times 3\) 3 × 3, 2048, stride 2 | 14 × 14 7 × 7 |
Conv6_x | \(\left[\begin{array}{c}3\times 3,2048\\ {}3\times 3,2048\end{array}\right]\times 2\) 3 × 3, 2048 | 7 × 7 5 × 5 |
Conv7_x | \(\left[\begin{array}{c}3\times 3,2048\\ {}3\times 3,2048\end{array}\right]\times 2\) 3 × 3, 2048 | 5 × 5 3 × 3 |
Fc1 | Max pool 3 × 3 2048-d fc | 1 × 1 |