DOAJ Open Access 2023

Application of convolutional networks of the YOLO architecture for calculating free parking spaces in an arbitrary parking lot

Alekhina Anna Korolev Pavel Dorrer Mikhail

Lihat Sumber DOI

Abstrak

The paper describes the solution of the problem of automatic fixation of the availability of free parking spaces in parking lots based on the video stream of the surveillance camera. The problem was solved using a combination of the YOLOv7 model for detecting objects of interest of the “car” type, trained on a specially created training sample and grouping of objects using the k-means algorithm. The proposed solution has shown satisfactory accuracy and suitability for practical use in conditions of significant optical interference – daily light fluctuations and precipitation for calculating free parking spaces by the model without retraining it for various parking lots

Topik & Kata Kunci

Environmental sciences

Penulis (3)

Alekhina Anna

Korolev Pavel

Dorrer Mikhail

Format Sitasi

APA MLA BibTeX

Anna, A., Pavel, K., Mikhail, D. (2023). Application of convolutional networks of the YOLO architecture for calculating free parking spaces in an arbitrary parking lot. https://doi.org/10.1051/e3sconf/202345803024

Akses Cepat

Lihat di Sumber doi.org/10.1051/e3sconf/202345803024

Informasi Jurnal

Tahun Terbit: 2023
Sumber Database: DOAJ
DOI: 10.1051/e3sconf/202345803024
Akses: Open Access ✓