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 neu-ral network, RNN, deep learning, OCR

Department
Department of Computer Graphics and Multimedia FIT BUT
Degree Programme
Information Technology, Field of Study Computer Graphics and Multimedia
Files
Status
defended, grade C
Date
30 August 2019
Reviewer
Špaňhel Jakub, Ing., Ph.D.
Committee
Růžička Richard, doc. Ing., Ph.D., MBA (DCSY FIT BUT), předseda
Herout Adam, prof. Ing., Ph.D. (DCGM FIT BUT), člen
Hrdina Jaroslav, doc. Mgr., Ph.D. (DADM FME BUT), člen
Malinka Kamil, Mgr., Ph.D. (DITS FIT BUT), člen
Rogalewicz Adam, doc. Mgr., Ph.D. (DITS FIT BUT), člen
Zbořil František, doc. Ing., Ph.D. (DITS 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. 2019-08-30. Supervised by Lysek Tomáš. Available from: https://www.fit.vut.cz/study/thesis/22520/
BibTeX 
@mastersthesis{FITMT22520,
    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/22520/"
}

Theses

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