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WEBCAM REAL TIME IMPLEMENTATION OF AI FACE DETECTION ATTENDANCE

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dc.contributor.author Simangunsong, Kevin David Hizkia
dc.date.accessioned 2024-10-08T06:19:11Z
dc.date.available 2024-10-08T06:19:11Z
dc.date.issued 2023
dc.identifier.uri http://repository.president.ac.id/xmlui/handle/123456789/11854
dc.description.abstract In a classroom setting during a presentation, keeping track of attendance is not just a difficult chore, but also one that takes a lot of time. There will always be a chance of proxy attendance because the lecture had an extremely high number of students in attendance. Conventional techniques of attendance recording have been difficult. The problem of face recognition is expanding because of the increasing demand for effective and automatic attendance marking methods. Standard biometrics like fingerprints and RFID tags have been widely used in recent years to address the issue of automatic attendance recording, but these methods lack the element of reliability. A face detection and identification algorithm-based automatic attendance marking, and management system is proposed for this project. This system's goal is to create an automated system that uses facial recognition technology to track student attendance in place of the existing techniques. The major goal of this effort is to improve the system for tracking attendance effective, convenient, and timesaving. Face recognition techniques will be used in this instance to identify faces. The picture is then compared to the already-stored record, and attendance will then be recorded in the database as appropriate. This technique lessens the workload of individuals when compared to the current system's traditional attendance marking system. en_US
dc.language.iso en_US en_US
dc.publisher President University en_US
dc.relation.ispartofseries Information Technologies;001201800101
dc.title WEBCAM REAL TIME IMPLEMENTATION OF AI FACE DETECTION ATTENDANCE en_US
dc.type Thesis en_US


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