CNN application in face recognition
Authors:
- Stanisław Osowski,
- Krzysztof Siwek
Abstract
The paper presents application of the convolutional neural network (CNN) in face recognition. The CNN is regarded nowadays as the most efficient tool in image analysis. This technique was applied to recognition of two databases of faces: the own base containing 68 classes of very different variants of face composition (grey images) and 244 classes of color face images represented as RGB images (MUCT data base). This paper will compare different solutions of classifiers applied in CNN, autoencoder and the traditional approach relying on classical feature generation methods and application of support vector machine classifier. The numerical results of experiments performed on the face image database will be presented and discussed.
- Record ID
- WUTa15d6b29b2fe49a68bdbf7a54222e1ae
- Author
- Journal series
- Przegląd Elektrotechniczny, ISSN 0033-2097
- Issue year
- 2020
- Vol
- 96
- Pages
- 142-145
- Publication size in sheets
- 0.50
- ASJC Classification
- DOI
- DOI:10.15199/48.2020.03.31 Opening in a new tab
- Language
- (en) English
- Score (nominal)
- 70
- Score source
- journalList
- Score
- = 70.0, 02-05-2022, ArticleFromJournal
- Publication indicators
- = 1; = 0; : 2018 = 0.434; : 2013 (2 years) = 0.000
- Uniform Resource Identifier
- https://repo.pw.edu.pl/info/article/WUTa15d6b29b2fe49a68bdbf7a54222e1ae/
- URN
urn:pw-repo:WUTa15d6b29b2fe49a68bdbf7a54222e1ae
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or PerishOpening in a new tab system.