Table 2 Hyperparameters used in the network
Layer no. and type | Activation function used | Regularization used | No. of feature maps/nodes (L + R) | Kernel Size | Stride length | Pooling size | Pooling Stride length |
|---|---|---|---|---|---|---|---|
1 (Convolutional Layer) | Relu | L2 | 2 + 2 | (5,5) | (1,1) | (2,2) | (2,2) |
2 (Convolutional Layer) | Relu | L2 | 4 + 4 | (5,5) | (1,1) | – | – |
3 (Convolutional Layer) | Relu | L2 | 8 + 8 | (5,5) | (1,1) | – | – |
4 (Convolutional Layer) | Relu | L2 | 4 + 4 | (5,5) | (1,1) | – | – |
5 (Convolutional Layer) | Relu | L2 | 2 + 2 | (5,5) | (1,1) | – | – |
6 (Fully connected layer) | Sigmoid | L2 | 50 + 50 | – | – | – | – |
7 (Fully connected layer) | Sigmoid | L2 | 30 + 30 | – | – | – | – |
8(Fully connected layer) | Sigmoid | L2 | 6 + 6 | – | – | – | – |