prikaz prve stranice dokumenta Detekcija geografskih karakteristika Venere korištenjem algoritama strojnog učenja
  Download
PDF 5.78 MB
master's thesis
Detekcija geografskih karakteristika Venere korištenjem algoritama strojnog učenja
2022. urn:nbn:hr:190:009642
Đuranović, Daniel
University of Rijeka
Faculty of Engineering
Department of Automation and Electronics
Section of Electronics, Robotics and Automation

Cite this document

Đuranović, D. (2022). Detekcija geografskih karakteristika Venere korištenjem algoritama strojnog učenja (Master's thesis). Rijeka: University of Rijeka, Faculty of Engineering. Retrieved from https://urn.nsk.hr/urn:nbn:hr:190:009642

Đuranović, Daniel. "Detekcija geografskih karakteristika Venere korištenjem algoritama strojnog učenja." Master's thesis, University of Rijeka, Faculty of Engineering, 2022. https://urn.nsk.hr/urn:nbn:hr:190:009642

Đuranović, Daniel. "Detekcija geografskih karakteristika Venere korištenjem algoritama strojnog učenja." Master's thesis, University of Rijeka, Faculty of Engineering, 2022. https://urn.nsk.hr/urn:nbn:hr:190:009642

Đuranović, D. (2022). 'Detekcija geografskih karakteristika Venere korištenjem algoritama strojnog učenja', Master's thesis, University of Rijeka, Faculty of Engineering, accessed 02 April 2025, https://urn.nsk.hr/urn:nbn:hr:190:009642

Đuranović D. Detekcija geografskih karakteristika Venere korištenjem algoritama strojnog učenja [Master's thesis]. Rijeka: University of Rijeka, Faculty of Engineering; 2022 [cited 2025 April 02] Available at: https://urn.nsk.hr/urn:nbn:hr:190:009642

D. Đuranović, "Detekcija geografskih karakteristika Venere korištenjem algoritama strojnog učenja", Master's thesis, University of Rijeka, Faculty of Engineering, Rijeka, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:190:009642

Please login to the repository to save this object to your list.
Metadata
TitleDetekcija geografskih karakteristika Venere korištenjem algoritama strojnog učenja
Title (english)Detection of Venus geographic characteristics using machine learning algorithms
AuthorDaniel Đuranović
MentorZlatan Car (mentor)
Committee memberSaša Vlahinić (predsjednik povjerenstva)
Committee memberZlatan Car (član povjerenstva)
Committee memberIvan Volarić (član povjerenstva)
GranterUniversity of Rijeka
Faculty of Engineering
(Department of Automation and Electronics)
(Section of Electronics, Robotics and Automation)
Rijeka
Defense date and country2022-09-20, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Electrical Engineering
Automation and Robotics
Abstract
Ovim radom opisana je realizacija sustava za detekciju vulkana sa satelitskih snimka planetarne površine Venere. U prvome dijelu objašnjeni su osnovni princip rada i struktura YOLO algoritma koji je korišten kao metoda detekcije objekata. Zatim su prezentirane metode pripreme i obrade Magellan seta podataka u svrhu učenja neuronske mreže. Nakon toga su prezentirani problemi s kojima se suočilo zbog relativno malog seta podataka, te su objašnjena rješenja s kojima se uspjelo doći do... More zadovoljavajućih rezultata modela. Na samome kraju predstavljena su idejna rješenja za buduća istraživanja u svrhu poboljšanja preciznosti modela kod detekcije jako malih objekata. Less
Abstract (english)
This work describes the implementation of a volcano detection system with a satellite image of the planetary surface of Venus. In the first part, the basic working principle and structure of the YOLO algorithm, which is used as an object detection method, are explained. Then the methods of preparation and processing of the Magellan dataset for the purpose of neural network learning are presented. After that, the problems faced due to a relatively small set of data were presented,... More and the solutions with which it was possible to achieve satisfactory model results were explained. At the very end, conceptual solutions for future research are presented in order to improve the precision of the model for detection of very small objects. Less
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:190:009642
Study programmeTitle: Graduate University Study of Electrical Engineering
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka elektrotehnike (magistar/magistra inženjer/inženjerka elektrotehnike)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence Attribution 4.0 International (CC BY 4.0) icon
Created on2022-09-19 15:35:32
accessibility

closeAccessibilityrefresh

If you wish to permanently save changes, click on Save, if not - your settings will be reset when you restart the browser.