KFU. Card publication. Traffic Sign Recognition System Based on Neural Network Algorithm

KAZAN
FEDERAL UNIVERSITY

- RUS
- 中文
- ES

TRAFFIC SIGN RECOGNITION SYSTEM BASED ON NEURAL NETWORK ALGORITHM

Form of presentation

Articles in international journals and collections

Year of publication

2025

Язык

английский

Authors, employees of KFU

Akhmedova Alfira Mazitovna, author

Zhazhneva Irina Vasilevna, author

Authors, students KFU

Gabitova Aygul Irekovna, author

Bibliographic description in the original language

Gabitova A, Akhmedova A, Zhazhneva I., Traffic Sign Recognition System Based on Neural Network Algorithm//Proceedings - 2025 International Russian Smart Industry Conference, SmartIndustryCon 2025. - 2025. - Vol., Is.. - P.488-493.

Annotation

2025 International Russian Smart Industry Conference (SmartIndustryCon)

Keywords

recognition, convolutional neural networks, telegram bot, traffic signs, RTSD

The name of the journal

2025 International Russian Smart Industry Conference (SmartIndustryCon)

URL

https://www.scopus.com/inward/record.uri?eid=2-s2.0-105007157577&doi=10.1109%2fSmartIndustryCon65166.2025.10985965&partnerID=40&md5=540897c6eebaf098a6537c3642ce8857

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=315531&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Akhmedova Alfira Mazitovna	ru_RU
dc.contributor.author	Zhazhneva Irina Vasilevna	ru_RU
dc.contributor.author	Gabitova Aygul Irekovna	ru_RU
dc.date.accessioned	2025-01-01T00:00:00Z	ru_RU
dc.date.available	2025-01-01T00:00:00Z	ru_RU
dc.date.issued	2025	ru_RU
dc.identifier.citation	Gabitova A, Akhmedova A, Zhazhneva I., Traffic Sign Recognition System Based on Neural Network Algorithm//Proceedings - 2025 International Russian Smart Industry Conference, SmartIndustryCon 2025. - 2025. - Vol., Is.. - P.488-493.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=315531&p_lang=2	ru_RU
dc.description.abstract	2025 International Russian Smart Industry Conference (SmartIndustryCon)	ru_RU
dc.description.abstract	This paper presents the implementation of a system for automatic recognition of traffic signs using convolutional neural networks (CNN). The solution is based on the ResNet architecture with elements of recurrent layers, which increases the accuracy and versatility of image processing. Traffic sign recognition system provides user functionality to upload images of signs to the telegram bot, receive their classification, as well as useful tips on traffic rules. Development was performed using the PyTorch library, RTD dataset, and DeepPavlov language model. Test results showed high model accuracy (97.7% accuracy) and user-friendliness of the interface. The developed solution can be used both in educational institutions for driver training and as an auxiliary tool for analyzing the traffic situation	ru_RU
dc.language.iso	ru	ru_RU
dc.subject	recognition	ru_RU
dc.subject	convolutional neural networks	ru_RU
dc.subject	telegram bot	ru_RU
dc.subject	traffic signs	ru_RU
dc.subject	RTSD	ru_RU
dc.title	Traffic Sign Recognition System Based on Neural Network Algorithm	ru_RU
dc.type	Articles in international journals and collections	ru_RU