CNN application in face recognition
Stanisław Osowski , Krzysztof Siwek
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.
|Journal series||Przegląd Elektrotechniczny, ISSN 0033-2097|
|Publication size in sheets||0.5|
|Score||= 20.0, 29-06-2020, ArticleFromJournal|
|Publication indicators||= 0; : 2018 = 0.434; : 2013 = 0.0 (2)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.