| Title: | Vehicle and label detection method based on YOLOv11 |
| Authors: | Guo Qicheng |
| Keywords: | материалы конференций;оbject detection;vehicles;computer vision |
| Issue Date: | 2025 |
| Publisher: | БГУИР |
| Citation: | Guo Qicheng. Vehicle and label detection method based on YOLOv11 / Guo Qicheng // Big Data и анализ высокого уровня = Big Data and Advanced Analytics : сборник научных статей XI Международной научно-практической конференции, Республика Беларусь, Минск, 23–24 апреля 2025 года / Белорусский государственный университет информатики и радиоэлектроники [и др.] ; редкол.: В. А. Богуш [и др.]. – Минск, 2025. – С. 340–342. |
| Abstract: | This paper proposes a vehicle and label detection method based on the YOLOv11 algorithm. By constructing a custom dataset of vehicles and labels, the YOLOv11 model is trained to achieve precise detection of vehicles and their rear-mounted labels. This paper details the dataset creation process, label design, model training procedure, and the selection of optimal training parameters. Finally, the algorithm's performance is evaluated using a validation set. Experimental results demonstrate that the YOLOv11-based vehicle and label detection method exhibits strong performance in terms of accuracy and real-time capability, meeting the requirements of practical applications. |
| URI: | https://libeldoc.bsuir.by/handle/123456789/59677 |
| Appears in Collections: | BIG DATA and Advanced Analytics = BIG DATA и анализ высокого уровня : сборник научных статей (2025)
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