Applications of computer vision in examination proctoring
| dc.contributor.author | Sapargali N. | |
| dc.date.accessioned | 2024-12-19T12:17:52Z | |
| dc.date.available | 2024-12-19T12:17:52Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | In 2019, a disease called COVID-19 hit the whole world and with the appearance of this disease, a new era of distance learning has begun. Learning has moved to apps like Google Meet, Microsoft Teams, Zoom, Webex and messengers like Whatsapp, Telegram, etc. Almost all universities and schools changed their courses to reflect what is going on in the world now. With all of this going on, their grades and scores should be going down, but many students did better than the average. This is because there has never been a way to do a well-organized test online without using different methods for each student. To solve the problem at hand, we need a system that can help us figure out how students are cheating. When it comes to online tests, the use of proctoring procedures is a big problem for the research community. This work shows us how to make a full multi-model system using computer vision so that people don’t have to be there during the inspection. We propose a system with many features that students can use during the test object identification, and estimating head posture using facial landmarks and face detection(is it the same student or another). | |
| dc.identifier.uri | https://repository.sdu.edu.kz/handle/123456789/1594 | |
| dc.language.iso | en | |
| dc.subject | distance learning, apps, proctoring, head posture, facial landmarks, face detection | |
| dc.title | Applications of computer vision in examination proctoring | |
| dc.type | Other |