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http://localhost:8080/xmlui/handle/123456789/4107
Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Shaikh, Salim | - |
dc.contributor.author | Mukadam, Ismail (19CO42) | - |
dc.contributor.author | Shaikh, Fuzail (19CO53) | - |
dc.contributor.author | Ansari, Mohd Sajjad (19CO61) | - |
dc.date.accessioned | 2023-06-06T10:14:16Z | - |
dc.date.available | 2023-06-06T10:14:16Z | - |
dc.date.issued | 2023-05 | - |
dc.identifier.uri | http://localhost:8080/xmlui/handle/123456789/4107 | - |
dc.description.abstract | The current attendance procedure is manual, which is time-consuming for both teachers and students. Manual attendance recording can lead to human errors, and students may have to wait for a long time to be marked present. Automating the attendance process can help increase learning time in the classroom. Facial recognition is a popular technology that can be used to automate attendance. For this project, we developed a facial recognition system that uses traditional facial recognition and recognition mechanisms. Facial recognition is essential for security and surveillance purposes, and it is crucial to have an effective and affordable system. The identification process involves three main steps: face recognition, feature extraction and classification, and real-time detection. Our system uses Python programming language and the OpenCV library for implementation. | en_US |
dc.language.iso | en | en_US |
dc.publisher | AIKTC | en_US |
dc.relation.ispartofseries | PE0727; | - |
dc.subject | Project Report - CO | en_US |
dc.title | Face recognition attendance system | en_US |
dc.type | Project Report | en_US |
Appears in Collections: | Computer Engineering - Project Reports |
Files in This Item:
File | Description | Size | Format | |
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Group 7_Face Recognition Attendance System .pdf Until 2026-06-30 | 14.72 MB | Adobe PDF | View/Open Request a copy |
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