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The next section describes the SCN model of related studies. Currently, there are various research methods for facial expression recognition. Considering cost and convenience, we used deep learning for this research. This time, I conducted research based on this SCN model. Because as shown in Table 1, the SCN model has higher recognition performance than conventional facial expression recognition methods for unmasked face images. And in general facial recognition problems, blurred images, or incorrect annotations of images in large-scale image datasets can make the model¡¯s training difficult. SCN can effectively suppress the over-fitting of the network to images with uncertain labeling in large-scale facial expression datasets. SCN model may be helpful in this research because masked face images may lose some facial features and thus increase their noisy labels. |
IEEE/ICACT20230035 Slide.03
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