CNN application in face recognition

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.

Author Stanisław Osowski (FoEE / ITEEMIS)
Stanisław Osowski,,
- The Institute of the Theory of Electrical Engineering, Measurement and Information Systems
, Krzysztof Siwek (FoEE / ITEEMIS)
Krzysztof Siwek,,
- The Institute of the Theory of Electrical Engineering, Measurement and Information Systems
Journal seriesPrzegląd Elektrotechniczny, ISSN 0033-2097
Issue year2020
Vol96
Pages142-145
Publication size in sheets0.5
ASJC Classification2208 Electrical and Electronic Engineering
DOIDOI:10.15199/48.2020.03.31
Languageen angielski
Score (nominal)20
Score sourcejournalList
ScoreMinisterial score = 20.0, 29-06-2020, ArticleFromJournal
Publication indicators Scopus Citations = 0; Scopus SNIP (Source Normalised Impact per Paper): 2018 = 0.434; WoS Impact Factor: 2013 = 0.0 (2)
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