Improved Network for Face Recognition Based on Feature Super Resolution Method
文献类型：期刊论文
| 作者 | Ling-Yi Xu ; Zoran Gajic
|
| 刊名 | International Journal of Automation and Computing
 |
| 出版日期 | 2021 |
| 卷号 | 18期号:6页码:915-925 |
| 关键词 | Face recognition feature super resolution multiple-branch network deep learning convolutional neural networks |
| ISSN号 | 1476-8186 |
| DOI | 10.1007/s11633-021-1309-9 |
| 英文摘要 | Low-resolution face images can be found in many practical applications. For example, faces captured from surveillance videos are typically in small sizes. Existing face recognition deep networks, trained on high-resolution images, perform poorly in recognizing low-resolution faces. In this work, an improved multi-branch network is proposed by combining ResNet and feature super-resolution modules. ResNet is for recognizing high-resolution facial images and extracting features from both high- and low-resolution images. Feature super-resolution modules are inserted before the classifier of ResNet for low-resolution facial images. They are used to increase feature resolution. The proposed method is effective and simple. Experimental results show that the recognition accuracy for high-resolution face images is high, and the recognition accuracy for low-resolution face images is improved. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/46098]  |
| 专题 | 自动化研究所_学术期刊_International Journal of Automation and Computing |
| 作者单位 | Department of Electrical & Computer Engineering, Rutgers, The State University of New Jersey, Piscataway 08854, USA |
| 推荐引用方式 GB/T 7714 | Ling-Yi Xu,Zoran Gajic. Improved Network for Face Recognition Based on Feature Super Resolution Method[J]. International Journal of Automation and Computing,2021,18(6):915-925. |
| APA | Ling-Yi Xu,&Zoran Gajic.(2021).Improved Network for Face Recognition Based on Feature Super Resolution Method.International Journal of Automation and Computing,18(6),915-925. |
| MLA | Ling-Yi Xu,et al."Improved Network for Face Recognition Based on Feature Super Resolution Method".International Journal of Automation and Computing 18.6(2021):915-925. |
入库方式： OAI收割
来源：自动化研究所
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