Facial Expression Recognition Based on Multi-dataset Neural Network
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Date
2020-04
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Referee
Mark
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Společnost pro radioelektronické inženýrství
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Abstract
Facial activity is the most powerful and natural means for understanding emotional expression for humans. Recent years, extensive efforts have been devoted to facial expression recognition by using neural networks. However, automated emotion recognition in the wild from facial images remains a challenging problem. In this paper, an effective facial expression recognition scheme is proposed. A multi-dataset neural network is developed to learn facial expression features in several different but related datasets. The novel multi-dataset network fuses the intermediate layers of a deep convolutional neural network (CNN) by using separate CNNs and a multi-dataset loss function. Experimental results performed on emotion database demonstrate that our proposed method outperforms state-of-the-art.
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Citation
Radioengineering. 2020 vol. 29, č. 1, s. 259-266. ISSN 1210-2512
https://www.radioeng.cz/fulltexts/2019/20_01_0259_0266.pdf
https://www.radioeng.cz/fulltexts/2019/20_01_0259_0266.pdf
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Peer-reviewed
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en