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Nikola Plavac

Last ned pressefoto
Last ned pressefoto
Foto: Kai T. Dragland / NTNU

Nikola Plavac

PhD Candidate
Institutt for datateknologi og informatikk
Fakultet for informasjonsteknologi og elektroteknikk

[email protected]
A249 Ametystbygget, Gjøvik
Google Scholar
Om Publikasjoner Undervisning

Om

Nikola Plavac (1999) holds bachelor's degree with honours from University of Novi Sad (Faculty of Technical Sciences) in Biomedical Engineering (2018). During the final year of bachelor's studies, he completed a 6-months internship in Continental R&D Center Novi Sad as System Test Engineer. The main responsibility was writing and performing manual and automatic tests of a newly integrated Walk-Away-Lock (WAL) functionality. In 2024, Nikola graduated from the Master Erasmus Mundus program in Computational Colour and Spectral Imaging (COSI). His final thesis title was "Assessment of Deep Learning Algorithms for Automatic License Plate Recognition on Distorted Images", supervised by Dr. Seyed Ali Amirshahi, Prof. Marius Pedersen, and Prof. Sophie Triantaphillidou. 

Research interests 

Color Imaging, Image Processing, Image Quality Assessment, Camera Pipeline Engineering, System Testing, Computer Vision

PhD

Nikola is currently an Integrated PhD Candidate at the Department of Computer Science, NTNU Gjøvik. His project has a working title "Influence of Imaging Pipeline on Performance of Computer Vision Tasks".

Teaching 

As part of his employment at NTNU, he is performing teaching duties. In the Autumn 2024, he was teaching assistant for IMT4304 - Cross-media Color Reproduction and IDIG4321 - Introduction to Color Image Processing courses. In the IMT4304 course, his responsibility was assisting students with practical laboratory sessions, as well as designing and delivering practical calculation sessions. In the IDIG4321, he was assisting students with practical coding sessions and served as an examiner.

Kompetanseord

  • Color Imaging
  • Image Processing
  • Image Quality

Publikasjoner

The Influence of Read Noise on an Automatic License Plate Recognition System

This study aims to investigate how a specific type of distortion in imaging pipelines, such as read noise, affects the performance of an automatic license plate recognition algorithm.

Performance of Automatic License Plate Recognition Systems on Distorted Images

Three ALPR systems were used to evaluate their robustness to distortions using images from six ALPR datasets. Two groups of distortions were the focus of our study: simulated weather conditions and modeled camera read noise in the imaging pipeline.
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2024

  • Plavac, Nikola; Amirshahi, Seyed Ali; Pedersen, Marius; Triantafyllidou, Sofia. (2024) The Influence of Read Noise on an Automatic License Plate Recognition System. London Imaging Meeting (LIM)
    Vitenskapelig artikkel
  • Plavac, Nikola; Amirshahi, Seyed Ali; Pedersen, Marius; Triantafyllidou, Sofia. (2024) Performance of Automatic License Plate Recognition Systems on Distorted Images. Journal of Imaging Science and Technology
    Vitenskapelig artikkel

Tidsskriftspublikasjoner

  • Plavac, Nikola; Amirshahi, Seyed Ali; Pedersen, Marius; Triantafyllidou, Sofia. (2024) The Influence of Read Noise on an Automatic License Plate Recognition System. London Imaging Meeting (LIM)
    Vitenskapelig artikkel
  • Plavac, Nikola; Amirshahi, Seyed Ali; Pedersen, Marius; Triantafyllidou, Sofia. (2024) Performance of Automatic License Plate Recognition Systems on Distorted Images. Journal of Imaging Science and Technology
    Vitenskapelig artikkel

Undervisning

Teaching assistant - Høst 2024:
IMT4304 - Cross-media Color Reproduction
IDIG4321 - Introduction to Color Image Processing

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