| | SLO | ENG | Cookies and privacy

Bigger font | Smaller font

Show document Help

Title:Pametni video nadzor domačega okolja z uporabo nevronskih mrež : magistrsko delo
Authors:ID Kos, Uroš (Author)
ID Žlahtič, Bojan (Mentor) More about this mentor... New window
Files:.pdf MAG_Kos_Uros_2025.pdf (5,30 MB)
MD5: BA46D001DEEE93FD264DB4692FBC01AC
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V magistrskem delu smo razvili pameten sistem video nadzora domačega okolja, ki s pomočjo nevronskih mrež omogoča zaznavanje oseb in vozil v realnem času. Sistem uporablja model YOLO za prepoznavanje objektov, lasten model na osnovi ResNet-50 za prepoznavo znamke in modela vozila ter OCR za branje registrskih tablic. Zajeti podatki se shranjujejo v MSSQL bazo in so dostopni prek spletnega vmesnika, razvitega v .NET in Angularju. Rešitev omogoča pregled dogodkov, arhiviranje posnetkov in prikaz v živo ter izkazuje zanesljivo delovanje v različnih vremenskih in svetlobnih pogojih.
Keywords:Pametni video nadzor, nevronske mreže, prepoznavanje vozil, YOLO
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[U. Kos]
Year of publishing:2025
Number of pages:1 spletni vir (1 datoteka PDF (XI, 63 str.))
PID:20.500.12556/DKUM-96004 New window
UDC:004.032.26:004.932(043.2)
COBISS.SI-ID:266779651 New window
Publication date in DKUM:22.12.2025
Views:231
Downloads:50
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
:
Copy citation
  
Average score:(0 votes)
Your score:Voting is allowed only for logged in users.
Share:Bookmark and Share



Hover the mouse pointer over a document title to show the abstract or click on the title to get all document metadata.

Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:20.11.2025

Secondary language

Language:English
Title:Smart video surveillance of the home environment using neural networks
Abstract:In this master’s thesis, we developed a smart home video surveillance system that uses neural networks for real-time detection of people and vehicles. The system employs the YOLO model for object detection, a custom ResNet-50–based model for recognizing vehicle brands and models, and OCR for license plate reading. Captured data are stored in an MSSQL database and accessed through a web interface built with .NET and Angular. The solution enables live view, event tracking, and video archiving, demonstrating reliable performance under various weather and lighting conditions.
Keywords:Smart video surveillance, neural networks, vehicle recognition, YOLO


Comments

Leave comment

You must log in to leave a comment.

Comments (0)
0 - 0 / 0
 
There are no comments!

Back
Logos of partners University of Maribor University of Ljubljana University of Primorska University of Nova Gorica