Detail publikačního výsledku

Detection of parking space availability based on video

KUŽELA, M.; FRÝZA, T.

Originální název

Detection of parking space availability based on video

Anglický název

Detection of parking space availability based on video

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

This paper deals with the use of Machine vision and ML (Machine Learning) for a parking lot occupation detection. It presents and compares an already existing technology that solves such a problem with an AI (Artificial Intelligence) usecase. It introduces tools used to train and create such models and their subsequent results as well as a dataset that was used to verify the trained networks and discusses the future of how such a technology could be used to effectively and more affordably detect occupied parking spaces on parking lots.

Anglický abstrakt

This paper deals with the use of Machine vision and ML (Machine Learning) for a parking lot occupation detection. It presents and compares an already existing technology that solves such a problem with an AI (Artificial Intelligence) usecase. It introduces tools used to train and create such models and their subsequent results as well as a dataset that was used to verify the trained networks and discusses the future of how such a technology could be used to effectively and more affordably detect occupied parking spaces on parking lots.

Klíčová slova

Machine vision; Machine learning; Parking occupancy; Python

Klíčová slova v angličtině

Machine vision; Machine learning; Parking occupancy; Python

Autoři

KUŽELA, M.; FRÝZA, T.

Rok RIV

2025

Vydáno

23.04.2024

Nakladatel

Brno University of Technology, FEKT

Místo

Brno

ISBN

978-80-214-6230-4

Kniha

Proceedings II of the 30th Student EEICT 2024

Strany od

36

Strany do

39

Strany počet

4

BibTex

@inproceedings{BUT188990,
  author="Miloslav {Kužela} and Tomáš {Frýza}",
  title="Detection of parking space availability based on video",
  booktitle="Proceedings II of the 30th Student EEICT 2024",
  year="2024",
  pages="36--39",
  publisher="Brno University of Technology, FEKT",
  address="Brno",
  isbn="978-80-214-6230-4"
}