| Autor: |
Doroz, Rafal, Orczyk, Tomasz, Wrobel, Krzysztof, Porwik, Piotr |
| Zdroj: |
Procedia Computer Science; 2024, Vol. 246, p4038-4047, 10p |
| Abstrakt: |
The article presents a new method of multibiometric Verification that has been enhanced with dynamic classifier selection based on determining their competence. The competence of a classifier is defined, taking into account the type of biometric trait and the samples analyzed. The proposed approach not only allows for adaptive selection of classifiers to specific features and samples but also increases system efficiency by more effectively utilizing models that best match the given conditions. Classifier selection occurs dynamically, which enables the system to adjust flexibly to changing conditions and leverage the strengths of individual models while mitigating their weaknesses through compensation within the committee. The effectiveness of this method has been verified through experiments, which confirmed a significant improvement in person Verification effectiveness compared to methods without dynamic classifier selection. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Supplemental Index |
| Externí odkaz: |
|
