文章詳目資料
Journal of Computers EIMEDLINEScopus
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| 篇名 | Facial Expression Recognition Based on Deep Residual Network |
|---|---|
| 卷期 | 31:2 |
| 作者 | Junsuo Qu 、 Ruijun Zhang 、 Zhiwei Zhang 、 Jeng-Shyang Pan |
| 頁次 | 012-019 |
| 關鍵字 | deep residual network 、 facial expression recognition 、 pre-processing techniques 、 softmax 、 EI 、 MEDLINE 、 Scopus |
| 出刊日期 | 202004 |
| DOI | 10.3966/199115992020043102002 |
中文摘要
英文摘要
Low accuracy of facial expression recognition for traditional methods, a facial expression recognition algorithm is proposed. Using the deep residual network model as the feature extractor, the residual block of the residual network is improved to enhance the information flow in the deep network. During training, apply some pre-processing techniques to extract only expression specific features from a face image and explore the presentation order of the samples and use softmax to classify and identify the extracted feature vectors. The experimental results show that a higher recognition rate is obtained on FER-2013.
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