• Nguyen Thi Nhung Hung Yen University of Technology and Education
  • Bui Thi Kim Thoa Hung Yen University of Technology and Education
  • Tran Long Quang Anh Hanoi University of Science and Technology
  • Nguyen Phu Dat Hanoi University of Industry
Keywords: Convolutional neural networks (CNNs), deep learning, YOLO, YOLOv3, image recognition, traffic sign recognition


Research paper on convolutional neural networks, YOLOv3 algorithm, a deep learning model which is being widely researched and developed in the field of computer vision for real-time objects recognition. Applying this algorithm to build an identification system, analysis, and build a neural network to recognize traffic signs. The results of the paper are based on the model that has been built, tested, and evaluated. The results show that using the model in the image recognition problem is completely appropriate. In addition, they are the basis for the research and development of convolutional neural networks in recognition and controlling problems with real-time images, and videos.


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How to Cite
Nguyen Thi Nhung, Bui Thi Kim Thoa, Tran Long Quang Anh, & Nguyen Phu Dat. (2022). TRAFFIC SIGN DETECTION AND RECOGNITION WITH DEEP CONVOLUTIONAL NEURAL NETWORKS. UTEHY Journal of Science and Technology, 32(4), 39-45. Retrieved from