prikaz prve stranice dokumenta Sustav za obradu senzorskih podataka s bicikla zasnovan na metodama strojnog učenja
No public access
master's thesis
Sustav za obradu senzorskih podataka s bicikla zasnovan na metodama strojnog učenja
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. urn:nbn:hr:168:699044
Roglić, Matija
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Roglić, M. (2021). Sustav za obradu senzorskih podataka s bicikla zasnovan na metodama strojnog učenja (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:699044

Roglić, Matija. "Sustav za obradu senzorskih podataka s bicikla zasnovan na metodama strojnog učenja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:699044

Roglić, Matija. "Sustav za obradu senzorskih podataka s bicikla zasnovan na metodama strojnog učenja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:699044

Roglić, M. (2021). 'Sustav za obradu senzorskih podataka s bicikla zasnovan na metodama strojnog učenja', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 22 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:699044

Roglić M. Sustav za obradu senzorskih podataka s bicikla zasnovan na metodama strojnog učenja [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2021 [cited 2024 November 22] Available at: https://urn.nsk.hr/urn:nbn:hr:168:699044

M. Roglić, "Sustav za obradu senzorskih podataka s bicikla zasnovan na metodama strojnog učenja", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:168:699044

Metadata
TitleSustav za obradu senzorskih podataka s bicikla zasnovan na metodama strojnog učenja
Title (english)System for Bicycle Sensor Data Processing Based on Machine Learning Methods
AuthorMatija Roglić
MentorMario Cifrek (mentor)
Committee memberMario Cifrek (predsjednik povjerenstva)
Committee memberHrvoje Džapo (član povjerenstva)
Committee memberŽeljka Lučev Vasić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2021-07-08, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Electrical Engineering
Abstract
U radu je prikazan razvoj sustava na električnom biciklu koji koristi neuronsku mrežu kako bi detektirao lice korisnika i prepoznao ga. Sustav je baziran na Yocto Linux operacijskom sustavu kako bi se smanjila veličina i povećala efikasnost sustava. Na Yocto Linuxu je tijekom izgradnje dodan sloj za izgradnju TensorFlow Lite biblioteke i ROS Noetic sustava. Sam model se pokreće uz pomoć interpretera iz TensorFlow Lite biblioteke u ROS okruženju na DART-SOM-MX6 pločici, te prima ulazne podatke s prednje kamere bicikla, detektira i obrađuje lice na fotografiji te izbacuje poruku s imenom prepoznate osobe ako se ta osoba nalazi u bazi podataka.
Abstract (english)
Through the master thesis a system on an electrical bike was developed that uses neural networks to detect and recognise the user's face. The system is based on Yocto Linux operating system to decrease the size and increase the efficiency of the whole system. While building Yocto image, a layer containing recipes for building TensorFlow Lite interpreter and ROS Noetic has been added. The model is run with interpreter on a DART-SOM-MX6 board in ROS environment and it receives input from a front camera, detects the face and recognises it and sends the message about the face it recognized.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:699044
Study programmeTitle: Electrical Engineering and Information Technology
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka elektrotehnike i informacijske tehnologije (magistar/magistra inženjer/inženjerka elektrotehnike i informacijske tehnologije)
Type of resourceText
File originBorn digital
Access conditionsClosed access
Terms of useLicence In copyright icon
Public note
Created on2023-01-13 13:43:30