| Autor: |
Arindam, Gupta, Rajeswari, D. |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 2024, Vol. 3075 Issue 1, p1-14, 14p |
| Abstrakt: |
The key goal of this project is to create an eye-tracking drowsiness detection system because it is thought that doing so will allow for the early diagnosis of driving fatigue symptoms and the prevention of auto accidents. When this happens when drowsiness is identified, a warning signal is given to the driver. This study introduces a component in the Advanced Driver Assistance System (ADAS) that handles automatically detecting driver tiredness using visual data and artificial intelligence. This approach seeks to improve transportation safety by reducing the number of accidents brought on by fatigued drivers. We propose an algorithm for the detection, observation, and analysis of the the driver's face and gaze for the evaluation of PERCLOS, a drowsiness indication associated with slowly closing eyes with scientific support. The preprocessing techniques that we have used are CNN+Inception V3,RNN,LSTM and VGG13. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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