Research Article
Remote Sensing Image Water Body Recognition Algorithm Based on Deep Convolution Generating Network and Combined Features
Table 4
Initialization settings of water body identification model parameters.
| Number of input layer nodes (feature dimension) | 64 | Number of output layer nodes | 2 (water and nonwater) | Generate model () | Learning rate | 0.005 | Momentum | 0.9 | Discriminant model () | Learning rate | 0.005 | Momentum | 0.9 | Number of iterations | 1000 | Activation function | tanh | Classification function | SoftMax | Convolution kernel size | 5 | Pool layer filter size | 2 | Number of neurons in full connection layer | 1024 |
|
|