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undergraduate thesis
Sustav za prepoznavanje rukom pisanog teksta
2022. urn:nbn:hr:235:218726
Zidarić, Matija
University of Zagreb
Faculty of Mechanical Engineering and Naval Architecture

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Zidarić, M. (2022). Sustav za prepoznavanje rukom pisanog teksta (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture. Retrieved from https://urn.nsk.hr/urn:nbn:hr:235:218726

Zidarić, Matija. "Sustav za prepoznavanje rukom pisanog teksta." Undergraduate thesis, University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, 2022. https://urn.nsk.hr/urn:nbn:hr:235:218726

Zidarić, Matija. "Sustav za prepoznavanje rukom pisanog teksta." Undergraduate thesis, University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, 2022. https://urn.nsk.hr/urn:nbn:hr:235:218726

Zidarić, M. (2022). 'Sustav za prepoznavanje rukom pisanog teksta', Undergraduate thesis, University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, accessed 06 February 2025, https://urn.nsk.hr/urn:nbn:hr:235:218726

Zidarić M. Sustav za prepoznavanje rukom pisanog teksta [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture; 2022 [cited 2025 February 06] Available at: https://urn.nsk.hr/urn:nbn:hr:235:218726

M. Zidarić, "Sustav za prepoznavanje rukom pisanog teksta", Undergraduate thesis, University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:235:218726

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Metadata
TitleSustav za prepoznavanje rukom pisanog teksta
Title (english)Handwriting recognition system
AuthorMatija Zidarić
MentorTomislav Stipančić (mentor)
GranterUniversity of Zagreb
Faculty of Mechanical Engineering and Naval Architecture
Zagreb
Defense date and country2022-09-28, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Mechanical Engineering
Abstract
Razvojem računala, danas su algoritmi neuronskih mreža postali izuzetno moćni i rapidno se razvijaju. Rukom pisani tekst je zbog svoje unikatnosti jako zanimljivo područje za primjenu strojnog učenja. Suvremene duboke neuronske mreže nude nova rješenja za poznate probleme. U ovome radu je osmišljena programska aplikacija korištenjem biblioteka OpenCV, Keras i TensorFlow. Korišteni programski jezik je Python i ResNet kao arhitektura neuronske mreže. Provedena je i evaluacija dobivenog modela na primjerima rukom pisanog teksta.
Abstract (english)
The development of computers has resulted in extremely powerful neural network algorithms which continue to develop rapidly. Due to its uniqueness, handwritten text is a very interesting area for the application of machine learning. Modern deep neural networks offer new solutions to existing problems. In this thesis, a software application was designed using OpenCV, Keras and TensorFlow libraries. Python was used as the programming language and ResNet as the neural network architecture. An evaluation of the obtained model was also carried out on the examples of handwritten text.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:235:218726
Study programmeTitle: Mechanical Engineering
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka strojarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka strojarstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2022-09-24 12:16:46