Thesis Details

Boosting a evoluční algoritmy

Bachelor's Thesis Student: Mrnuštík Michal Academic Year: 2007/2008 Supervisor: Hradiš Michal, Ing., Ph.D.
English title
Boosting and Evolution
Language
Czech
Abstract

This thesis introduces combination of the AdaBoost and the evolutionary algorithm. The evolutionary algorithm is used to find linear combination of Haar features. This linear combination creates the feature to train weak classifier for AdaBoost. There are described basics of classification, Haar features and the AdaBoost. Next there are basic information about evolutionary algorithms. Theoretical description of combination of the AdaBoost and the evolutionary algorithm is included too. Some implementation details are added too. Implementation is tested on the images as part of the system for face recognition. Results are compared with Haar features.

Keywords

boosting, adaboost, evolutionary algorithms, pattern recognition, haar features

Department
Department of Computer Graphics and Multimedia FIT BUT
Degree Programme
Information Technology
Files
Status
defended, grade A
Date
12 June 2008
Reviewer
Juránek Roman, Ing., Ph.D.
Committee
Černocký Jan, prof. Dr. Ing. (DCGM FIT BUT), předseda
Herout Adam, prof. Ing., Ph.D. (DCGM FIT BUT), člen
Lukáš Roman, Ing., Ph.D. (DIFS FIT BUT), člen
Ráček Jaroslav, RNDr., Ph.D. (FI MUNI), člen
Vojnar Tomáš, prof. Ing., Ph.D. (DITS FIT BUT), člen
Zbořil František, doc. Ing., Ph.D. (DITS FIT BUT), člen
Citation
MRNUŠTÍK, Michal. Boosting a evoluční algoritmy. Brno, 2008. Bachelor's Thesis. Brno University of Technology, Faculty of Information Technology. 2008-06-12. Supervised by Hradiš Michal. Available from: https://www.fit.vut.cz/study/thesis/6673/
BibTeX 
@bachelorsthesis{FITBT6673,
    author = "Michal Mrnu\v{s}t\'{i}k",
    type = "Bachelor's thesis",
    title = "Boosting a evolu\v{c}n\'{i} algoritmy",
    school = "Brno University of Technology, Faculty of Information Technology",
    year = 2008,
    location = "Brno, CZ",
    language = "czech",
    url = "https://www.fit.vut.cz/study/thesis/6673/"
}

Theses

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