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Semi-supervised Emotion Recognition using Inconsistently Annotated Data

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Academic year: 2021

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Figure

Fig. 1: Workflow of the proposed expression recognition method.
TABLE I: Comparison of average classification accuracy for different combinations of self-training (ST) and sample weight assignment (SW)
TABLE III: Cross-dataset accuracy for seven expression classes. Note that we utilized the test dataset as the unlabeled data.
Fig. 2: Classification examples from AffectNet dataset.
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