prikaz prve stranice dokumenta MOBILNA ANDROID APLIKACIJA ZA PREPOZNAVANJE TIPOVA TENKOVA KLASIFIKACIJSKIM POSTUPCIMA STROJNOG UČENJA
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undergraduate thesis
MOBILNA ANDROID APLIKACIJA ZA PREPOZNAVANJE TIPOVA TENKOVA KLASIFIKACIJSKIM POSTUPCIMA STROJNOG UČENJA
2022. urn:nbn:hr:200:577727
Alerić, Zvonimir
Josip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
Department of Software Engineering
Chair of Programming Languages and Systems

Cite this document

Alerić, Z. (2022). MOBILNA ANDROID APLIKACIJA ZA PREPOZNAVANJE TIPOVA TENKOVA KLASIFIKACIJSKIM POSTUPCIMA STROJNOG UČENJA (Undergraduate 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:200:577727

Alerić, Zvonimir. "MOBILNA ANDROID APLIKACIJA ZA PREPOZNAVANJE TIPOVA TENKOVA KLASIFIKACIJSKIM POSTUPCIMA STROJNOG UČENJA." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2022. https://urn.nsk.hr/urn:nbn:hr:200:577727

Alerić, Zvonimir. "MOBILNA ANDROID APLIKACIJA ZA PREPOZNAVANJE TIPOVA TENKOVA KLASIFIKACIJSKIM POSTUPCIMA STROJNOG UČENJA." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2022. https://urn.nsk.hr/urn:nbn:hr:200:577727

Alerić, Z. (2022). 'MOBILNA ANDROID APLIKACIJA ZA PREPOZNAVANJE TIPOVA TENKOVA KLASIFIKACIJSKIM POSTUPCIMA STROJNOG UČENJA', Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, accessed 24 November 2024, https://urn.nsk.hr/urn:nbn:hr:200:577727

Alerić Z. MOBILNA ANDROID APLIKACIJA ZA PREPOZNAVANJE TIPOVA TENKOVA KLASIFIKACIJSKIM POSTUPCIMA STROJNOG UČENJA [Undergraduate thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2022 [cited 2024 November 24] Available at: https://urn.nsk.hr/urn:nbn:hr:200:577727

Z. Alerić, "MOBILNA ANDROID APLIKACIJA ZA PREPOZNAVANJE TIPOVA TENKOVA KLASIFIKACIJSKIM POSTUPCIMA STROJNOG UČENJA", Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:200:577727

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Metadata
TitleMOBILNA ANDROID APLIKACIJA ZA PREPOZNAVANJE TIPOVA TENKOVA KLASIFIKACIJSKIM POSTUPCIMA STROJNOG UČENJA
Title (english)ANDROID MOBILE APPLICATION FOR RECOGNITION OF TYPES OF TANKS CLASSIFICATION PROCEDURES OF MACHINERY LEARNING
AuthorZvonimir Alerić
MentorGoran Martinović (mentor)
GranterJosip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
(Department of Software Engineering)
(Chair of Programming Languages and Systems)
Osijek
Defense date and country2022-09-21, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Program Engineering
Abstract
U ovom radu je stvorena Android aplikacija za prepoznavanje tenkova na slici. Tijekom rada istraživane su tehnologije za stvaranje neuronske mreže koja će sa slika prepoznavati tenkove. Stvoren je model koji sadrži konvolucijsku neuronsku mrežu i treniran je na slikama triju modela tenkova. Model je implementiran u aplikaciju stvorenu u Flutteru koristeći Dart jezik. Sam model je imao prosječnu točnost i u većini slučajeva je prepoznao tenk sa slike. Dubokim učenjem možemo istrenirati model konvolucijske neuronske mreže koji će u aplikaciji prepoznavati modele tenkova sa slika, no ovo rješenje ima prostora za poboljšanje.
Abstract (english)
In this paper, an Android application was created to recognize tanks in the image. During the work, technologies were researched to create a neural network that will recognize tanks from images. A model containing a convolutional neural network was created and trained on images of three tank models. The model is implemented in an application created in Flutter using the Dart language. The model itself had average accuracy and in most cases recognized the tank from the picture. With deep learning, we can train a convolutional neural network model that will recognize tank models from images in the application, but this solution has room for improvement.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:200:577727
Study programmeTitle: Undergraduate University Study Programme in Computer Engineering
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsAccess restricted to students and staff of home institution
Terms of useLicence In copyright icon
Created on2022-10-13 14:39:59