Thesis Details

Deskriptor pro identifikaci osoby podle obličeje

Master's Thesis Student: Coufal Tomáš Academic Year: 2018/2019 Supervisor: Goldmann Tomáš, Ing.
English title
Descriptor for Identification of a Person by the Face
Language
Czech
Abstract

Thesis provides an overview and discussion of current findings in the field of biometrics. In particular, it focuses on facial recognition subject. Special attention is payed to convolutional neural networks and capsule networks. Thesis then lists current approaches and state-of-the-art implementations. Based on these findings it provides insight into engineering a very own solution based of CapsNet architecture. Moreover, thesis discussed advantages and capabilitied of capsule neural networks for identification of a person by its face.

Keywords

face, recognition, identification, neural network, convolution, capsule, CapsNet

Department
Department of Intelligent Systems FIT BUT
Degree Programme
Information Technology, Field of Study Bioinformatics and Biocomputing
Files
Status
defended, grade A
Date
20 June 2019
Reviewer
Orság Filip, Ing., Ph.D.
Committee
Sekanina Lukáš, prof. Ing., Ph.D. (DCSY FIT BUT), předseda
Grégr Matěj, Ing., Ph.D. (DIFS FIT BUT), člen
Holík Lukáš, doc. Mgr., Ph.D. (DITS FIT BUT), člen
Martínek Tomáš, doc. Ing., Ph.D. (DCSY FIT BUT), člen
Matoušek Radomil, doc. Ing., Ph.D. (IACS FME BUT), člen
Ryšavý Ondřej, doc. Ing., Ph.D. (DIFS FIT BUT), člen
Citation
COUFAL, Tomáš. Deskriptor pro identifikaci osoby podle obličeje. Brno, 2019. Master's Thesis. Brno University of Technology, Faculty of Information Technology. 2019-06-20. Supervised by Goldmann Tomáš. Available from: https://www.fit.vut.cz/study/thesis/21775/
BibTeX 
@mastersthesis{FITMT21775,
    author = "Tom\'{a}\v{s} Coufal",
    type = "Master's thesis",
    title = "Deskriptor pro identifikaci osoby podle obli\v{c}eje",
    school = "Brno University of Technology, Faculty of Information Technology",
    year = 2019,
    location = "Brno, CZ",
    language = "czech",
    url = "https://www.fit.vut.cz/study/thesis/21775/"
}

Theses

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