A comparative analysis on driver drowsiness detection using CNN

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Naren Thiruvalar V.; Vimal E.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: INTERNATIONAL JOURNAL OF NONLINEAR ANALYSIS AND APPLICATIONS Year:2021 | Volume:12 | Issue:Special Issue Page(s): 1835-1843

Download Full-Text

View:

Download:

Cites:

Information Journal Paper

Title

A comparative analysis on driver drowsiness detection using CNN

Author(s)

Naren Thiruvalar V. | Vimal E. | Issue Writer Certificate

Keywords

CNN

Drowsiness Detection

Viola-Jones

PERCLOS

Abstract

The main objective of this project is to detect driver’s drowsiness and alert the driver which is an important precautionary measure in order to avoid accidents. Here two different algorithms based on Convolution Neural Network (CNN) were applied and the results were compared respectively. “Highway Hypnosis” is a serious issue to be addressed while driving especially on highways. Drivers who travel on highways continuously for more than 3 hours must be aware of this serious problem. If there is proper knowledge of it, fatalities would be drastically reduced. In this project, a dedicated detection coupled with an alarm system is provided to alert the driver in case of drowsiness. CNN is used since it is very effective in analyzing images and videos. In this project, a live video feed is used to detect drowsiness by suitable algorithms.

Multimedia

No record.

Cites

No record.

References

No record.

Cite

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans