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Automated Attendance System Using Face Recognition with One-Shot Learning and Siamese Neural Networks

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dc.contributor.author Shaik, Md. Abu
dc.contributor.author Islam, Ashikul
dc.date.accessioned 2019-09-22T08:35:03Z
dc.date.available 2019-09-22T08:35:03Z
dc.date.issued 2019-05-03
dc.identifier.uri http://hdl.handle.net/123456789/3442
dc.description.abstract A face is the identity of a person. Not only human but also machines can now identify a person. Face recognition system is a Biometric Artificial Intelligence application. Now it is widely used everywhere in the world. It can be also used in our classroom. It is compulsory to take attendance in an educational institute like school, college, university. Corny approach for attendance is to call students by their names and record the attendance. We are going to use an automated attendance system in our classroom to avoid it. In this approach, we can use the face detection and recognition method. Face detection differentiates the faces from each other and recognition method recognizes the person for daily attendance. For face detection, we can use Haar cascade classifier and for face recognition, we can use Google’s FaceNet model. It takes less time than a corny approach. It also helps the teacher to maintain a large classroom. The system also helps to avoid a large number of students from skipping the daily classes. In this system, there is no way of cheating like fake attendance. With the help of this system, we can take attendance at any time. Automated attendance system is now also an individual research subject. We can now focus to make the method more efficient in real time scenario. en_US
dc.language.iso en_US en_US
dc.publisher Daffodil International University en_US
dc.relation.ispartofseries ;P13311
dc.subject Computer Science en_US
dc.subject Face Recognition en_US
dc.subject Attendance en_US
dc.subject Face Identity en_US
dc.title Automated Attendance System Using Face Recognition with One-Shot Learning and Siamese Neural Networks en_US
dc.type Other en_US

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