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ONLINE PROCTORING SYSTEM USING DEEP LEARNING
1ATHIRA A G, 2PRAMEEJA PRASIDHAN
1Msc Scholar, 2Assistant Professor
1,2Department of Computer Science
1,2St.Joseph’s College(Autonomous), Irinjalakuda, Thrissur , Kerala
ABSTRACT
Distance and on- line mastering ( or e-learning) has emerge as a norm in schooling and education due to a ramification of benefits similar as effectiveness, flexibility, affordability and ease of use. Insulation requirements. however, tracking participants and scholars throughout training, specifically assessments, is a major task for on- line systems due to the dearth of physical presence. strategies and technologies need to be advanced that offer sturdy equipment for detecting unfair, unethical and unlawful conduct for the duration of the study room requirements. We suggest in this paper a new online surveillance system that uses deep learning to continuously monitor physical locations without the need for a physical examiner. The system makes use of biometric strategies which includes face sensor OpenCV DNN and the eye tracking algorithm OpenCV. further, the machine consists of person and phone detection. To make sure equity for the duration of examinations, the device can also recognize devices including cell telephones, laptops, iPads and books.
KEYWORDS : Deep Learning, CNN ,YOLOv3,OpenCV,Online Proctoring.
