| Autor: |
Qinru YU, Guifu LU |
| Jazyk: |
čínština |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
智能科学与技术学报, Vol 3, Pp 334-341 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2096-6652 |
| DOI: |
10.11959/j.issn.2096-6652.202134 |
| Popis: |
A method which utilizes maximum correntropy criterion and locality information called collaborative representation based classifier with maximum correntropy criterion and locality constraint (CRC/MCCLC) was proposed.On the one hand, CRC/MCCLC was not only more robust to outliers than L1 norm but also could be computed efficiently using half-quadratic optimization technique because of the use of maximum correntropy criterion.On the other hand, CRC/MCCLC could obtain more discriminative information from the training samples and could lead to an approximately sparse representation because of the use of locality information.Extensive experimental results on some image databases demonstrate that CRC/MCCLC can achieve the state-of-the-art performance on these image databases. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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