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master's thesis
Sustav za prepoznavanje znakovne abecede
2024. urn:nbn:hr:190:501478
Jandrić, Ivan
University of Rijeka
Faculty of Engineering

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Jandrić, I. (2024). Sustav za prepoznavanje znakovne abecede (Master's thesis). Rijeka: University of Rijeka, Faculty of Engineering. Retrieved from https://urn.nsk.hr/urn:nbn:hr:190:501478

Jandrić, Ivan. "Sustav za prepoznavanje znakovne abecede." Master's thesis, University of Rijeka, Faculty of Engineering, 2024. https://urn.nsk.hr/urn:nbn:hr:190:501478

Jandrić, Ivan. "Sustav za prepoznavanje znakovne abecede." Master's thesis, University of Rijeka, Faculty of Engineering, 2024. https://urn.nsk.hr/urn:nbn:hr:190:501478

Jandrić, I. (2024). 'Sustav za prepoznavanje znakovne abecede', Master's thesis, University of Rijeka, Faculty of Engineering, accessed 28 September 2024, https://urn.nsk.hr/urn:nbn:hr:190:501478

Jandrić I. Sustav za prepoznavanje znakovne abecede [Master's thesis]. Rijeka: University of Rijeka, Faculty of Engineering; 2024 [cited 2024 September 28] Available at: https://urn.nsk.hr/urn:nbn:hr:190:501478

I. Jandrić, "Sustav za prepoznavanje znakovne abecede", Master's thesis, University of Rijeka, Faculty of Engineering, Rijeka, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:190:501478

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Metadata
TitleSustav za prepoznavanje znakovne abecede
Title (english)Sign alphabet recognition system
AuthorIvan Jandrić
MentorMiroslav Vrankić (mentor)
Committee memberIvo Ipšić (predsjednik povjerenstva)
Committee memberMladen Tomić (član povjerenstva)
Committee memberIvan Štajduhar (član povjerenstva)
GranterUniversity of Rijeka
Faculty of Engineering
Rijeka
Defense date and country2024-07-14, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Artificial Intelligence
Abstract
U radu je istražen napredak u kurikulumu i metodama učenja znakovnog jezika. Uz analizu napretka opisano je trenutno stanje na polju detekcije znakovnog jezika umjetnom inteligencijom. Pregledani su trenutno dostupni komercijalni sustavi za učenje znakovnog jezika. Opisan je proces strojnog učenja modela detekcije zna- kovnog jezika te utjecaj promjene hiperparametara učenja na preciznost i odziv de- tekcije. Kroz izrađeni modularni višeplatformski sustav za učenje znakovne abecede uz primjenu umjetne inteligencije, dokazano je kako su znanja stečena postojećim istraživanjima dostatna za izradu takvog sustava. Naposljetku, navedena su moguća buduća istraživanja i poboljšanja sustava za učenje.
Abstract (english)
The paper explores progress in the curriculum and methods of sign language learning. The current state and progress in sign language detection using artificial intelligence have been examined. Presently available commercial sign language learning sys- tems are reviewed. The machine learning process of the sign language detection model is described, as well as the influence of changing the learning hyperparameters on the precision and recall of the detection. Through the created modular multi- platform system for sign language alphabet learning with the application of artificial intelligence, it has been proven that the knowledge gained from existing research is sufficient for the creation of such a system. Finally, possible future research and improvement of the learning system are listed.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:190:501478
Study programmeTitle: Computer Engineering
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence Attribution 4.0 International (CC BY 4.0) icon
Created on2024-07-17 12:01:34