DRIVER SLEEPINESS DETECTION USING CONVOLUTION NEURAL NETWORK

Authors

  • Khamzaev Jamshid Fayzidin o’g’li TUIT named after Muhammad al-Khwarizmi
  • Yakhshiboev Rustam Erkinboy o’g’l TUIT named after Muhammad al-Khwarizmi
  • Ochilov Temur Dilshodovich TUIT named after Muhammad al-Khwarizmi
  • Siddiqov Boburbek Norpo’lat o’g’li TUIT named after Muhammad al-Khwarizmi

Keywords:

CNN, model, computer vision, driver, system, artificial intelligence

Abstract

This article discusses the CNN model based on artificial intelligence. With this model, it is possible to define and develop a driver drowsiness detection system. The system will greatly help truckers, because dividing the driving of transport will lead to eye fatigue and the driver himself.

References

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Yaxshiboyev, Rustam, and Dilbar Yaxshiboyeva. "ANALYSIS OF ALGORITHMS FOR PREDICTION AND PRELIMINARY DIAGNOSTICS OF GASTROENTEROLOGICAL DISEASES." CENTRAL ASIAN JOURNAL OF EDUCATION AND COMPUTER SCIENCES (CAJECS) 1.2 (2022): 49-56.

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Published

2022-08-28

How to Cite

Khamzaev, J., Yaxshiboyev, R., Ochilov, T., & Siddiqov, B. (2022). DRIVER SLEEPINESS DETECTION USING CONVOLUTION NEURAL NETWORK. CENTRAL ASIAN JOURNAL OF EDUCATION AND COMPUTER SCIENCES (CAJECS), 1(4), 31–35. Retrieved from https://cajecs.com/index.php/cajecs/article/view/v1i44

Issue

Vol. 1 No. 4 (2022): CAJECS

Section

Technical sciences

License

Copyright (c) 2022 CENTRAL ASIAN JOURNAL OF EDUCATION AND COMPUTER SCIENCES (CAJECS)

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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