Research Article
Lip Print Recognition Algorithm Based on Convolutional Network
Table 1
Information of all network layers.
| Network layer | Name | Dimensions | Channel number | Step length | Activation function |
| C1 | Convolution layer | | 8 | 1 | ReLU | M1 | Pool layer | | 8 | 2 | —— | C2 | Convolution layer | | 32 | 1 | ReLU | M2 | Pool layer | | 32 | 2 | —— | C3 | Convolution layer | | 64 | 1 | ReLU | M3 | Pool layer | | 64 | 2 | —— | C4 | Convolution layer | | 128 | 1 | ReLU | C5 | Convolution layer | | 128 | 1 | ReLU | M4 | Pool layer | | 128 | 2 | —— | C6 | Convolution layer | | 64 | 1 | ReLU | M5 | Pool layer | | 64 | 2 | —— | FC1 | Fully connected layer | 3136 nodes | ReLU | FC2 | Fully connected layer | 2048 nodes | ReLU | FC3 | Fully connected layer | 2048 nodes | ReLU | Softmax | Output layer | 40 nodes | —— |
|
|