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Facial expression recognition: a review
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DOI：10.1007/s11042-023-15982-x.png)
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摘要
En 中文
Facial expression recognition has become a hot issue in the field of artificial intelligence. So, we collect literature on facial expression recognition. First, methods based on machine learning are introduced in detail, which include image preprocessing, feature extraction, and image classification. Then, we review deep learning methods in detail: convolutional neural networks, deep belief networks, generative adversarial networks, and recurrent neural networks. Moreover, the advantages and limitations of different facial expression recognition methods are compared. In addition, 20 commonly used facial expression datasets are collected in this paper, and the types of expressions and the number of images contained in each dataset are summarized. Finally, the current problems and future development of facial expression recognition are concluded.
Keyword:
Facial expression recognition
Machine learning
Deep learning
Expression dataset
期刊
IF:
3
论文数:
2.0W
被引数:
3.2W
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