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Facial Recognition System for Automatic Attendance Tracking Using an Ensemble of Deep-Learning Techniques

Publication Type : Conference Paper

Publisher : IEEE

Source : 2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT), 2021, pp. 1-6, doi: 10.1109/ICCCNT51525.2021.9580098.

Url : https://ieeexplore.ieee.org/document/9580098

Campus : Amritapuri

School : School of Computing

Year : 2021

Abstract : Face recognition technology has made countless contributions in improving and changing the world. Attendance Systems utilizing Real-Time Face Recognition technology is a solution that can efficiently carry out the procedure of marking student attendance. Face recognition-based attendance system is the process by which we mark the attendance of the students present in the classroom by utilizing the facial data that is acquired from a surveillance camera. The proposed system captures the face of students attending the lecture by first detecting a face from the video input and with the help of an ensemble of deep learning models recognize the student and mark his/her attendance in the database [1]. This system uses an ensemble of facial recognition models such as VGG-FACE, Facenet, Openface, DeepFace so that it may be able to yield a much higher accuracy while identifying the subject.

Cite this Research Publication : Venugopal A, Rahul R Krishna, Rahul Varma U, "Facial Recognition System for Automatic Attendance Tracking Using an Ensemble of Deep-Learning Techniques," 2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT), 2021, pp. 1-6, doi: 10.1109/ICCCNT51525.2021.9580098.

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