Development of Deep Learning Models for Traffic Sign Recognition in Autonomous Vehicles
Kozhamkulova Z. Bidakhmet Z. Vorogushina M. Tashenova Z. Tussupova B. Nurlybaeva E. Kambarov D.
2024Science and Information Organization
International Journal of Advanced Computer Science and Applications
2024#15Issue 5913 - 920 pp.
This research paper investigates the development of deep learning models for traffic sign recognition in autonomous vehicles. Leveraging convolutional neural networks (CNNs), the study explores various architectural configurations and evaluation methodologies to assess the efficacy of CNNs in accurately identifying and classifying traffic signs. Through a systematic evaluation process utilizing metrics such as accuracy, precision, recall, and F-score, the research demonstrates the robustness and generalization capability of the developed models across diverse environmental conditions. Furthermore, the utilization of visualization techniques, including the Matplotlib library, enhances the interpretability of model training dynamics and optimization progress. The findings highlight the significance of CNN architecture in facilitating hierarchical feature extraction and spatial dependency learning, thereby enabling reliable and efficient traffic sign recognition. The successful recognition of traffic signs under varying lighting conditions underscores the resilience of the developed models to environmental perturbations. Overall, this research contributes to advancing the capabilities of autonomous vehicle systems and lays the groundwork for the implementation of intelligent traffic sign recognition systems aimed at enhancing road safety and navigational efficiency.
computer vision , deep learning , image classification , machine learning , Traffic sign recognition
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Almaty University of Power Engineering and Telecommunications, Almaty, Kazakhstan
Turan Unviersity, Almaty, Kazakhstan
Al-Farabi Kazakh National University, Almaty, Kazakhstan
L.N. Gumilyov Eurasian National University, Astana, Kazakhstan
KazNAA named after T.K.Zhurgenov, Almaty, Kazakhstan
Almaty University of Power Engineering and Telecommunications
Turan Unviersity
Al-Farabi Kazakh National University
L.N. Gumilyov Eurasian National University
KazNAA named after T.K.Zhurgenov
10 лет помогаем публиковать статьи Международный издатель
Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026