Table 1 Network structure of the proposed CNN-based classification model
Layer | Configuration |
|---|---|
Conv | 7 × 7, 64, Stride = 2 |
Norm | Batch normalization |
Pool | 3 × 3 Max pooling, Stride = 2 |
RA-Conv_2 | \(\left[ \begin{gathered} 3 \times 3,\;\;64 \hfill \\ 3 \times 3,\;\;64 \hfill \\ \end{gathered} \right] \times 2\) |
RA-Conv_3 | \(\left[ \begin{gathered} 3 \times 3,\;128 \hfill \\ 3 \times 3,\;128 \hfill \\ \end{gathered} \right] \times 3\) |
RA-Conv_5 | \(\left[ \begin{gathered} 3 \times 3,\;\;256 \hfill \\ 3 \times 3,\;\;256 \hfill \\ \end{gathered} \right] \times 5\) |
RA-Conv_2 | \(\left[ \begin{gathered} 3 \times 3,\;\;512 \hfill \\ 3 \times 3,\;\;512 \hfill \\ \end{gathered} \right] \times 2\) |
Global average pooling (GAP) | |
Softmax | |