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master's thesis
Primjena LLM-a u razumijevanju i generiranju savjeta o prehrani
2024. urn:nbn:hr:200:700349
Tokić, Mateo
Josip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
Department of Software Engineering
Chair of Visual Computing

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Tokić, M. (2024). Primjena LLM-a u razumijevanju i generiranju savjeta o prehrani (Master's thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek. Retrieved from https://urn.nsk.hr/urn:nbn:hr:200:700349

Tokić, Mateo. "Primjena LLM-a u razumijevanju i generiranju savjeta o prehrani." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2024. https://urn.nsk.hr/urn:nbn:hr:200:700349

Tokić, Mateo. "Primjena LLM-a u razumijevanju i generiranju savjeta o prehrani." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2024. https://urn.nsk.hr/urn:nbn:hr:200:700349

Tokić, M. (2024). 'Primjena LLM-a u razumijevanju i generiranju savjeta o prehrani', Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, accessed 16 February 2025, https://urn.nsk.hr/urn:nbn:hr:200:700349

Tokić M. Primjena LLM-a u razumijevanju i generiranju savjeta o prehrani [Master's thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2024 [cited 2025 February 16] Available at: https://urn.nsk.hr/urn:nbn:hr:200:700349

M. Tokić, "Primjena LLM-a u razumijevanju i generiranju savjeta o prehrani", Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:200:700349

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Metadata
TitlePrimjena LLM-a u razumijevanju i generiranju savjeta o prehrani
Title (english)Application of LLMs in understanding and generating dietary advice
AuthorMateo Tokić
MentorČaslav Livada (mentor)
Committee memberČaslav Livada (predsjednik povjerenstva)
Committee memberAlfonzo Baumgartner (član povjerenstva)
Committee memberTomislav Galba (član povjerenstva)
GranterJosip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
(Department of Software Engineering)
(Chair of Visual Computing)
Osijek
Defense date and country2024-12-11, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Artificial Intelligence
Abstract
Ovaj diplomski rad bavi se primjenom velikih jezičnih modela (LLM) za razumijevanje i generiranje savjeta o prehrani. Glavni problem obuhvaća prepoznavanje sastojaka i nutritivnih vrijednosti s prehrambenih proizvoda te integraciju tih podataka u sustav za pružanje korisnih preporuka. Problem je riješen razvojem mobilne aplikacije pomoću React Native i Python Flask tehnologija. Implementacijom docTR modela za optičko prepoznavanje znakova omogućeno je čitanje nutritivnih vrijednosti i sastojaka sa slike proizvoda. Sustav na temelju prepoznatih sastojaka i nutritivnih vrijednosti te korisničkih podataka iz Firestore baze podataka generira savjet koristeći OpenAI-jev GPT- 3.5-turbo model. Ovaj rada svojim rezultatima potvrdio je mogućnost primjene LLM-a za pružanje personaliziranih prehrambenih preporuka otvarajući nove mogućnosti u digitalizaciji prehrane.
Abstract (english)
This thesis deals with the application of large language models (LLM) in understanding and generating dietary advice. The main problem involves identifying ingredients and nutritional values from food products and integrating this data into a system for providing useful recommendations. The problem was solved by developing a mobile application using React Native and Python Flask technologies. By implementing the docTR model for optical character recognition, it is possible to read the nutritional values and ingredients from the product image. Based on recognized ingredients and nutritional values and user data from the Firestore database, the system generates advice using OpenAI's GPT-3.5-turbo model. With its result, this thesis confirmed the possibility of applying LLM to provide personalized nutritional recommendations, opening up new possibilities in the digitization of nutrition.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:200:700349
Study programmeTitle: Graduate University Study Programme in Computer Engineering
Study programme type: university
Study level: graduate
Academic / professional title: sveučilišni/a magistar/magistra inženjer/inženjerka računarstva (sveučilišni/a magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2024-12-20 12:08:30