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| Content Provider | PubMed Central |
|---|---|
| Author | Wang, Rong |
| Copyright Year | 2015 |
| Abstract | In real-world applications, the image of faces varies with illumination, facial expression, and poses. It seems that more training samples are able to reveal possible images of the faces. Though minimum squared error classification (MSEC) is a widely used method, its applications on face recognition usually suffer from the problem of a limited number of training samples. In this paper, we improve MSEC by using the mirror faces as virtual training samples. We obtained the mirror faces generated from original training samples and put these two kinds of samples into a new set. The face recognition experiments show that our method does obtain high accuracy performance in classification. |
| Related Links | http://dx.doi.org/10.1155/2015/842084 |
| Starting Page | 842084 |
| File Format | |
| ISSN | 23566140 |
| e-ISSN | 1537744X |
| Journal | The Scientific World Journal |
| Volume Number | 2015 |
| Language | English |
| Publisher | Hindawi Publishing Corporation |
| Publisher Date | 2015-01-01 |
| Access Restriction | Open |
| Rights Holder | Hindawi Publishing Corporation |
| Subject Keyword | Biochemistry, Genetics and Molecular Biology(all) Environmental Science(all) Medicine(all) Research in Higher Education |
| Content Type | Text |
| Resource Type | Article |
| Subject | Medicine Biochemistry, Genetics and Molecular Biology Environmental Science |
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