Thesis Details

Využití hlubokého učení pro rozpoznání textu v obrazu grafického uživatelského rozhraní

Master's Thesis Student: Hamerník Pavel Academic Year: 2018/2019 Supervisor: Lysek Tomáš, Ing.
English title
Deep Learning for OCR in GUI
Language
Czech
Abstract

Optical character recognition (OCR) has been a topic of interest for many years. It is defined as the process of digitizing a document image into a sequence of characters. Despite decades of intense research, OCR systems with capabilities to that of human still remains an open challenge. In this work there is presented a design and implementation of such system, which is capable of detecting texts in graphical user interfaces.

Keywords

text recognition, neural network, convolutional neural network, CNN, LSTM, recurent neural network, RNN, deep learning, OCR

Department
Degree Programme
Information Technology, Field of Study Computer Graphics and Multimedia
Files
Status
not defended
Date
19 June 2019
Reviewer
Committee
Zemčík Pavel, prof. Dr. Ing. (DCGM FIT BUT), předseda
Burget Radim, Doc. Ing., Ph.D. (UTKO FEEC BUT), člen
Černocký Jan, prof. Dr. Ing. (DCGM FIT BUT), člen
Holík Lukáš, doc. Mgr., Ph.D. (DITS FIT BUT), člen
Hradiš Michal, Ing., Ph.D. (DCGM FIT BUT), člen
Szőke Igor, Ing., Ph.D. (DCGM FIT BUT), člen
Citation
HAMERNÍK, Pavel. Využití hlubokého učení pro rozpoznání textu v obrazu grafického uživatelského rozhraní. Brno, 2019. Master's Thesis. Brno University of Technology, Faculty of Information Technology. 2019-06-19. Supervised by Lysek Tomáš. Available from: https://www-dev.fit.vutbr.cz/study/thesis/22173/
BibTeX
@mastersthesis{FITMT22173,
    author = "Pavel Hamern\'{i}k",
    type = "Master's thesis",
    title = "Vyu\v{z}it\'{i} hlubok\'{e}ho u\v{c}en\'{i} pro rozpozn\'{a}n\'{i} textu v obrazu grafick\'{e}ho u\v{z}ivatelsk\'{e}ho rozhran\'{i}",
    school = "Brno University of Technology, Faculty of Information Technology",
    year = 2019,
    location = "Brno, CZ",
    language = "czech",
    url = "https://www.fit.vut.cz/study/thesis/22173/"
}
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