Third Eye:Student attendance & behavior Monitoring in classroom through facial Recognition by analyzing live video data
dc.contributor.advisor | Mohammad Ashrafuzzaman Khan | |
dc.contributor.author | MD Raihan Khan Student | |
dc.contributor.author | Zannatul Islam Proma | |
dc.contributor.id | 1831118042 | |
dc.contributor.id | 1911916642 | |
dc.coverage.department | Electrical and Computer Engineering | |
dc.date.accessioned | 2025-04-22 | |
dc.date.accessioned | 2025-04-22T04:06:20Z | |
dc.date.available | 2025-04-22T04:06:20Z | |
dc.date.issued | 2022 | |
dc.description.abstract | We are more drawn to automated systems because of rapid technological advancements. For the majority of issues, we find automated systems to be the answer. Therefore, we came up with an automated system for student behavior monitoring in the classroom. This system captures and makes a summary of student behavior in the classroom. The faculty is in charge of overseeing student attendance, attention, and activities including entering and exiting the classroom in addition to making sure that lessons go well. Manual observation of these could affect the teaching and learning process of the faculty and students and causes a distraction from the main syllabus. The system records the entire session and identifies when the students pay attention in the classroom, and then reports to the faculties. Students’ performance can be recorded, and the data can be used for continuous assessment in the future. There are mainly two objectives of our project: First, to detect faces and recognize them for attendance and to detect students’ attentiveness and behavior in the classroom during lectures. | |
dc.description.degree | Undergraduate | |
dc.identifier.cd | 600000496 | |
dc.identifier.print-thesis | To be assigned | |
dc.identifier.uri | https://repository.northsouth.edu/handle/123456789/1137 | |
dc.language.iso | en | |
dc.publisher | North South University | |
dc.rights | © NSU Library | |
dc.title | Third Eye:Student attendance & behavior Monitoring in classroom through facial Recognition by analyzing live video data | |
dc.type | Thesis | |
oaire.citation.endPage | 49 | |
oaire.citation.startPage | 1 |
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