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| dc.contributor.author | 03-134172-082, SAYAM ZAFAR | |
| dc.date.accessioned | 2024-10-30T06:54:02Z | |
| dc.date.available | 2024-10-30T06:54:02Z | |
| dc.date.issued | 2021-07-18 | |
| dc.identifier.other | BULC764 | |
| dc.identifier.uri | http://hdl.handle.net/123456789/18304 | |
| dc.description.abstract | Attendance of students has always been a challenging factor for teachers in terms of time, and accuracy. Already built manual attendance system has a chance of human error. Automated attendance system has also introduced the technology of biometric identifications of students using fingerprints and eye iris which is again a time consuming process. Proposed system will mark attendance automatically in classroom using real time face recognition technique without student/teacher’s intervention. The attendance of each student is marked on the basis of duration of his/her presence in class. System will also generate daily/monthly report of student presence along with his in/out behaviour in class. As an additional feature, system will also generate alert for any unknown person detected in cameras. | en_US |
| dc.description.sponsorship | Supervisor: Dr Muhammad Aasim Qureshi | en_US |
| dc.language.iso | en | en_US |
| dc.relation.ispartofseries | ;BULC764 | |
| dc.title | Smart Attendance using Real Time Face Recognition | en_US |
| dc.type | Project Reports | en_US |
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BS (CS) (BULC) [217]