Automated Class Attendance Management System Using Face Recognition
Prof. S.V Phulari
, Jadhav Pawan , Shaikh B Fatima , Halge Kshitij , Ingale Ajay
attendance recording, remote data entry, data acquisition system, YOLO, HOG, SVM, face recognition algorithm, Raspberry Pi
In this paper we propose an automated attendance system, Which is based on face recognition automatically detect the student face when he entered in a classroom and marks the attendance by recognizing face. The overall system architecture and algorithm used in project is described in this paper. When compared to traditional attendance marking this system saves the time and also helps to monitor the students. The framework depends on Raspberry Pi. The face capturing device used in system is Raspberry Pi which detects the face of student when he enters in a classroom ,the data recognized by Raspberry Pi is stored in CLOUD database, Those data used by android application to display the attendance and perform all other task of our project .the input provided to the system is image and the output of the system is attendance which is displayed on application. The Raspberry Pi 3B+ Camera, just as a 5-inch screen, are associated with the Raspberry Pi. By confronting the camera, the camera will catch the picture at that point pass it to the Raspberry Pi which is modified to deal with the face acknowledgment by actualizing the You only look once (yolo)s. On the off chance that the understudy's info picture matches with the prepared dataset picture the model entryway will open utilizing Servo Motor, at that point the participation results will be put away in the CLOUD database. The database is associated with Attendance Management System (AMS) web server, which makes the participation results reachable to any online associated Application.
"Automated Class Attendance Management System Using Face Recognition", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.5, Issue 5, page no.229 - 233, May-2020, Available :https://ijsdr.org/papers/IJSDR2005039.pdf
Volume 5
Issue 5,
May-2020
Pages : 229 - 233
Paper Reg. ID: IJSDR_191167
Published Paper Id: IJSDR2005039
Downloads: 000347353
Research Area: Engineering
Country: khamagaon, Maharashtra, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
