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undergraduate thesis
Umjetna inteligencija kod autonomnih vozila
2018. urn:nbn:hr:166:354302
Šušić, Igor
University of Split
Faculty of Science
Department of Informatics

Cite this document

Šušić, I. (2018). Umjetna inteligencija kod autonomnih vozila (Undergraduate thesis). Split: University of Split, Faculty of Science. Retrieved from https://urn.nsk.hr/urn:nbn:hr:166:354302

Šušić, Igor. "Umjetna inteligencija kod autonomnih vozila." Undergraduate thesis, University of Split, Faculty of Science, 2018. https://urn.nsk.hr/urn:nbn:hr:166:354302

Šušić, Igor. "Umjetna inteligencija kod autonomnih vozila." Undergraduate thesis, University of Split, Faculty of Science, 2018. https://urn.nsk.hr/urn:nbn:hr:166:354302

Šušić, I. (2018). 'Umjetna inteligencija kod autonomnih vozila', Undergraduate thesis, University of Split, Faculty of Science, accessed 18 April 2024, https://urn.nsk.hr/urn:nbn:hr:166:354302

Šušić I. Umjetna inteligencija kod autonomnih vozila [Undergraduate thesis]. Split: University of Split, Faculty of Science; 2018 [cited 2024 April 18] Available at: https://urn.nsk.hr/urn:nbn:hr:166:354302

I. Šušić, "Umjetna inteligencija kod autonomnih vozila", Undergraduate thesis, University of Split, Faculty of Science, Split, 2018. Available at: https://urn.nsk.hr/urn:nbn:hr:166:354302

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Metadata
TitleUmjetna inteligencija kod autonomnih vozila
Title (english)Artificial intelligence in autonomous vehicles
AuthorIgor Šušić
MentorSaša Mladenović (mentor)
Committee memberSaša Mladenović (predsjednik povjerenstva)
Committee memberGoran Zaharija (član povjerenstva)
Committee memberDivna Krpan (član povjerenstva)
GranterUniversity of Split
Faculty of Science
(Department of Informatics)
Split
Defense date and country2018-09-24, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U ovom radu objašnjeni su osnovni pojmovi za razumijevanje neuronskih mreža, s naglaskom na konvolucijske neuronske mreže i princip učenja mreža. Pokazano je na primjeru kako djeluju neuronske mreže, te kako možemo koristiti simulator za sakupljanje podataka i treniranje modela s samo kreiranim podatcima. Također je prikazano i objašnjeno kako kreirati konvolucijsku neuronsku mrežu služeći se gotovim bibliotekama koje ubrzavaju proces izrade prototipa i brinu se da se maksimalno isključi ljudska pogreška prilikom kreiranja mreže. Potrebno je samo razumjeti materiju da bi se jednostavno kreirala mreža i testirala.
Abstract (english)
In this work, main terms and concept „how neural network learns“ are explained for easier understanding on the topic of how neural networks work, with a highlight on convolutional neural networks. It is shown by example how CNN work, how we could use free simulators to create data for ourselves and train model with the same data. It has also been shown by an example, how to create CNN using popular frameworks that make a job lot easier and safer. You just need to understand what are you doing and no time should be spent on programming.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:166:354302
Study programmeTitle: Computer Science
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) informatike (sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) informatike)
Type of resourceText
File originBorn digital
Access conditionsAccess restricted to students and staff of home institution
Terms of useLicence In copyright icon
Created on2019-01-25 15:58:54