Support vector machine in gender recognition

• Autorzy: Stawska Z. , Milczarski P.

Identyfikatory

DOI

10.22630/ISIM.2017.6.4.6

• Języki publikacji: EN

Abstrakty

EN

In the paper, Support Vector Machine (SVM) methods are discussed. The SVM algorithm is a very strong classification tool. Its capability in gender recognition in comparison with the other methods is presented here. Different sets of face features derived from the frontal facial image such as eye corners, nostrils, mouth corners etc. are taken into account. The efficiency of different sets of facial features in gender recognition using SVM method is examined.

Słowa kluczowe

EN

face identification; gender classification; face authentication; biometrics; SVM; mobile applications

• Wydawca: Wydawnictwo Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie
• Czasopismo: Information Systems in Management
• Rocznik: 2017
• Tom: Vol. 6, No. 4
• Strony: 318--329
• Opis fizyczny: Bibliogr. 45 poz., rys., tab.

Twórcy

autor

Stawska Z.

• Department of Computer Science, Faculty of Physics and Applied Informatics, University of Lodz, Poland

autor

Milczarski P.

• Department of Computer Science, Faculty of Physics and Applied Informatics, University of Lodz, Poland

Bibliografia

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Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).