Skip to main content
. 2020 May 5;20(9):2639. doi: 10.3390/s20092639

Figure 1.

Figure 1

Framework of the proposed method. A SE-ResNet-50 model [21], which was pre-trained on VGGFace2 data [22] for face identification, is fine-tuned with AffectNet data [5] for facial recognition using weighted-cluster loss. Before the fine-tuning phase, we add one more fully connected layer to the model while froze the three first stages of the pre-trained model to save computing power. The weighted-cluster loss is used at the output layer to update model parameters. Best view in color.