Open Access Journal

ISSN : 2394-6849 (Online)

International Journal of Engineering Research in Electronics and Communication Engineering(IJERECE)

Monthly Journal for Electronics and Communication Engineering

Open Access Journal

International Journal of Science Engineering and Management (IJSEM)

Monthly Journal for Science Engineering and Management

ISSN : 2456-1304 (Online)

Facial Recognized Attendance Using Deep Learning

Author : Sapna B Kulkarni 1 Md Shahid Afridi P 2 K Manish 3 Md Fardeen 4 Naveena Kumara K 5

Date of Publication :22nd November 2021

Abstract: We are Living in a 21st Century where everything around us has become dependent on technology to make our life much easier and to work faster. People often use technology to complete the daily task . To the best of our knowledge, the process of recording attendance at the schools, universities, offices is still manual. In schools and universities the Attendance sheet is passed to all the students to sign on it and record attendance. Where as in office the employee should sign on the record book to make sure that he is present in office. This is slow, inefficient and time-consuming. This project is to offer system that can automate the process of recording and tracking the attendance using Facial Recognition Technology using Deep Learning. Facial Recognition Technology is becoming much popular in different areas such as Airports, Banks, Military, etc. Best example is our Mobile phone where we can unlock device using Face Recognition Technology. We will use Deep Learning techniques to detect, recognize and verify the captured faces. We aim to provide a system that will make the attendance process faster and more precisely

Reference :

    1. _detection_ system_for_attendance_of_class_students ttendance_of_class_students
    2. Hapani, Smit, et al. "Automated Attendance System Using Image Processing." 2018 Fourth International Conference onComputing Communication Control and Automation (ICCUBEA). IEEE, 2018.
    3. Akbar, Md Sajid, et al. "Face Recognition and RFID Verified Attendance System." 2018 International Conference onComputing, Electronics & Communications Engineering (iCCECE). IEEE, 2018.
    4. Okokpujie, Kennedy O., et al. "Design and implementation of a student attendance system using iris biometric recognition." 2017 International Conference on Computational Science and Computational Intelligence (CSCI). IEEE,2017.
    5. Zhao pie, Hang xu, “Face Recognition via Deep Learning Using Data Augmentation Based on Orthogonal Experiments”
    6. Lukas, Samuel, et al. "Student attendancesystem in classroom using face recognition technique." 2016 International Conference on Information and Communication Technology Convergence (ICTC). IEEE, 2016.

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