| Topic (9.x) | Subtopic (9.x.y) | Mini-topic (9.x.y.z) |
|---|---|---|
| 9.6 The Backpropagation Neural Network | 9.6.1 The BP Network and Error Function | |
| 9.6.2 Layer K Weight Estimation and Updating | ||
| 9.6.3 Layer K - 1 Weight Estimation and Updating | ||
| 9.6.4 The BP Algorithm | ||
| 9.7 Convolutional Neural Network | 9.7.1 CNN Architecture | |
| 9.7.2 Input Layer | ||
| 9.7.3 Convolution Layer 1 (C1) | 9.7.3.1 2D Convolution | |
| 9.7.3.2 Stride and Padding | ||
| 9.7.3.3 Bias | ||
| 9.7.3.4 Volume Convolution in Layer C1 | ||
| 9.7.3.5 Depth of the Feature Map Volume | ||
| 9.7.3.6 ReLU Activation | ||
| 9.7.3.7 Batch Normalization | ||
| 9.7.4 Pooling or Subsampling Layer 1 (S1) | ||
| 9.7.5 Convolution Layer 2 (C2) | ||
| 9.7.6 Hyperparameters | ||
| 9.8 Implementation of CNN | 9.8.1 CNN Architecture (VGGNet Example) | |
| 9.8.2 Filters of the Convolution Layers | ||
| 9.8.3 Filters of the Fully Connected Layers | ||
| 9.8.4 Feature Maps of Convolution Layers | ||
| 9.8.5 Matlab Implementation |