a driver face monitoring system for fatigue and detction
Sheeba Jasmine C,Leniu Theresa A, Jeevitha G,M. NAVANEETHAKRISHNAN, M.E., Ph.D.,
Published in International Journal of Advanced Research in Computer Science Engineering and Information Technology
ISSN: 2321-3337 Impact Factor:1.521 Volume:6 Issue:3 Year: 30 March,2021 Pages:1432-1437
Abstract
Machine learning (ML) is the scientific study of algorithms and statistical models that computer systems use to effectively perform a specific task without using explicit instructions, relying on patterns and inference instead. It is seen as a subset of artificial intelligence. Machine learning algorithms build a mathematical model of sample data, known as “training data”, in order to make predictions or decision without being explicitly programmed to perform the task. Machine learning algorithms are used in a wide variety of applications, such as email filtering, and computer vision, where it is infeasible to develop an algorithm of specific instructions for performing the task. Drowsiness detection is a computer technology related to computer vision and image processing that deals with detecting instances of person’s face.it is a technology which helps to prevent accidents caused by the driver getting drowsy. A computer vision system that can automatically detect driver drowsiness in a real-time video stream and then play an alarm if the driver appears to be drowsy is a great pros for the drivers around and help then have a safety ride.
Kewords
ml,Machine Learning
Reference
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