Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/16670
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dc.contributor.authorVulović, Aleksandra-
dc.contributor.authorSustersic, Tijana-
dc.contributor.authorPeulic, Aleksandar-
dc.contributor.authorFilipovic, Nenad-
dc.contributor.authorRankovic, Vesna-
dc.date.accessioned2023-02-19T15:56:16Z-
dc.date.available2023-02-19T15:56:16Z-
dc.date.issued2018-
dc.identifier.urihttps://scidar.kg.ac.rs/handle/123456789/16670-
dc.description.abstractResearch in the field of face recognition has been popular for several decades. With advances in technology,approaches to solving this problems haves changed. Main goal of this paper was to compare different training algorithms for neural networks and to apply them for face recognition as it is a nonlinear problem. Algorithm that we have used for face recognition problem was the Eigenface algorithm that belongs to the Principal Component Analysis (PCA) algorithms. Percentage of recognition for all the used training functions is above 90%.-
dc.rightsinfo:eu-repo/semantics/openAccess-
dc.titleComparison of Different Neural Network Training Algorithms with Application to Face Recognition Problem-
dc.typearticle-
dc.identifier.doihttp://dx.doi.org/10.4108/eai.10-1-2018.153550-
Appears in Collections:Faculty of Engineering, Kragujevac

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