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Journals / Advances in Artificial Intelligence Research / 2023 / Cilt: 3 Sayı: 2

Development of a Traffic Speed Limit Sign Detection System Based on Yolov4 Network

Semih Selçuk(Anadolu Isuzu Otomotiv Sanayi ve Tic. A.Ş.)0000-0003-3759-5362
Sefa Beker(Anadolu Isuzu Otomotiv Sanayi ve Tic. A.Ş.)0000-0001-7646-546X
Ömer Faruk Boyraz(Anadolu Isuzu Otomotiv Sanayi ve Tic. A.Ş.)0000-0002-3292-2814
Pages
66–75
Publication Date
2023-10-29
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

After the model training, the model was validated and the test results were found to be 98%.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Recent developments in artificial intelligence technologies have accelerated the transition to smart systems in the automotive industry.
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Key Findings & Data:In this system, Yolov4 model is used to achieve high speed and accuracy levels.
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Conclusion & Impact:After the model training, the model was validated and the test results were found to be 98%.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Speed Limit Sign · Object Detection · Deep Learning

Abstract

Recent developments in artificial intelligence technologies have accelerated the transition to smart systems in the automotive industry. By anticipating driving conditions, these technologies enable the prevention of driver-related errors and accidents as well as the provision of crucial information to the driver. In this study, an artificial intelligence-based system is designed to provide information to drivers about speed signs on the road in order to support traffic safety. In this system, Yolov4 model is used to achieve high speed and accuracy levels. After the model training, the model was validated and the test results were found to be 98%.

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Cite This Article

Selçuk, S., Beker, S., Boyraz, Ö. F. (2023). Development of a Traffic Speed Limit Sign Detection System Based on Yolov4 Network. Advances in Artificial Intelligence Research, Cilt: 3 Sayı: 2, 66–75. https://doi.org/10.54569/aair.1184569

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