Road traffic sign recognition using computer vision
| dc.contributor.author | Alsiyeu U. | |
| dc.date.accessioned | 2025-04-16T10:00:58Z | |
| dc.date.available | 2025-04-16T10:00:58Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | Road traffic accidents are a major public problem in Kazakhstan, with driver inattention and ignorance of traffic signs among the leading causes. Current driver assistance systems integrated in map apps may be inaccurate and irrelevant, especially in rural areas and on highways. The solution proposed by the research includes a computer vision algorithm for accurate and robust detection and recognition of road traffic signs in real time which will be integrated into a mobile application with a notification system. The algorithm will use deep learning neural networks to detect and recognize traffic signs in real time. The algorithm will be trained on a dataset, which will be collected manually and augmented using machine learning techniques. The proposed system has the potential to improve road safety in Kazakhstan by helping drivers to be more aware of traffic signs and to reduce driver inattention. | |
| dc.identifier.citation | Alsiyeu U / Road traffic sign recognition using computer vision / 2024 / 7M06102 - Computer Science | |
| dc.identifier.uri | https://repository.sdu.edu.kz/handle/123456789/1715 | |
| dc.language.iso | en | |
| dc.publisher | Faculty of Engineering and Natural Science | |
| dc.subject | Road traffic | |
| dc.subject | computer vision | |
| dc.subject | GPS | |
| dc.title | Road traffic sign recognition using computer vision | |
| dc.type | Thesis |