Please use this identifier to cite or link to this item:
https://scidar.kg.ac.rs/handle/123456789/16670
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Vulović, Aleksandra | - |
dc.contributor.author | Sustersic, Tijana | - |
dc.contributor.author | Peulic, Aleksandar | - |
dc.contributor.author | Filipovic, Nenad | - |
dc.contributor.author | Rankovic, Vesna | - |
dc.date.accessioned | 2023-02-19T15:56:16Z | - |
dc.date.available | 2023-02-19T15:56:16Z | - |
dc.date.issued | 2018 | - |
dc.identifier.uri | https://scidar.kg.ac.rs/handle/123456789/16670 | - |
dc.description.abstract | Research 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.rights | info:eu-repo/semantics/openAccess | - |
dc.title | Comparison of Different Neural Network Training Algorithms with Application to Face Recognition Problem | - |
dc.type | article | - |
dc.identifier.doi | http://dx.doi.org/10.4108/eai.10-1-2018.153550 | - |
Appears in Collections: | Faculty of Engineering, Kragujevac |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
eai.10-1-2018.153550.pdf | 582.24 kB | Adobe PDF | View/Open |
Items in SCIDAR are protected by copyright, with all rights reserved, unless otherwise indicated.