Deep Learning Approach for Drowsiness Detection Using Facial Features-Reference-Cited by-同舟云学术

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Deep Learning Approach for Drowsiness Detection Using Facial Features

Published:2024-05-24 Issue: Volume: Page:1-7
ISSN:
Container-title:2024 5th International Conference for Emerging Technology (INCET)
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Author:

Mokashi Bibisara¹,Tigadi Arun S¹,Chilad Bharati²,Rudrappa Gujanatti¹,Jadhav Sushant¹

Affiliation:

1. KLE Technological University, Dr. M S Sheshgiri College of Engineering and Technology,Department of Electronics and Communication,Belagavi,India

2. KLE Technological University, Dr. M S Sheshgiri College of Engineering and Technology,Department of Computer Science,Belagavi,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10592862/10592849/10593414.pdf?arnumber=10593414

Reference18 articles.

1. A preliminary study on the barriers and facilitators to improving the health, safety, and well-being of aging heavy vehicle drivers

2. Recent Trends in Driver Safety Monitoring Systems: State of the Art and Challenges

3. Autonomous Vehicles: Present Technological Traits and Scope for Future Innovation

4. Blinks and saccades as indicators of fatigue in sleepiness warnings: looking tired?

5. Towards Identification of Packaged Products via Computer Vision

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