Research Article
[Retracted] Facial Expression Recognition Based on Convolutional Neural Network Fusion SIFT Features of Mobile Virtual Reality
Table 1
Convolutional network parameters.
| Layer | Type | Kernel size () | Stride | Output number | Output size () |
| Layer1 | Convolution | | 1 | 64 | | Layer2 | Convolution | | 1 | 128 | | Layer3 | Max pooling | | 2 | 128 | | Layer4 | Convolution | | 1 | 128 | | Layer5 | Convolution | | 1 | 128 | | Layer6 | Convolution | | 1 | 256 | | Layer7 | Max pooling | | 2 | 256 | | Layer8 | Convolution | | 1 | 256 | | Layer9 | Convolution | | 1 | 256 | | Layer10 | Average pooling | | 3 | 256 | | Layer11 | Convolution | | 1 | 512 | | Layer12 | Fully connected | — | — | — | | Output | SoftMax | — | — | — | |
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