Leveraging Unlabeled Data for Emotion Recognition With Enhanced Collaborative Semi-Supervised Learning
One of the major obstacles that has to be faced when applying automatic emotion recognition to realistic human-machine interaction systems is the scarcity of labeled data for training a robust model. Motivated by this concern, this paper seeks to utmost exploit unlabeled data that are pervasively av...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2018-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8345573/ |