- Tytuł:
- Sparse Bayesian learning in classifying face feature vectors
- Autorzy:
-
Momot, A.
Kawulok, M. - Powiązania:
- https://bibliotekanauki.pl/articles/333794.pdf
- Data publikacji:
- 2005
- Wydawca:
- Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
- Tematy:
-
wnioskowanie bayesowskie
rozpoznanie twarzy
supervised learning
Bayesian inference
face recognition - Opis:
- The Relevance Vector Machine (RVM), a Bayesian treatment of generalized linear model of identical functional form to the Support Vector Machine (SVM), is the recently developed machine learning framework capable of building simple models from large sets of candidate features. The paper describes the application of the RVM to a classification algorithm of face feature vectors, obtained by Eigenfaces method. Moreover, the results of the RVM classification are compared with those obtained by using both the Support Vector Machine method and the method based on the Euclidean distance.
- Źródło:
-
Journal of Medical Informatics & Technologies; 2005, 9; 151-158
1642-6037 - Pojawia się w:
- Journal of Medical Informatics & Technologies
- Dostawca treści:
- Biblioteka Nauki
Artykuł