Open AccessReal Time Attendance Marking System
Author(s) -
R John,
s Akhilesh.,
Gayathri Geetha Nair,
Jeen Raju,
B Krishnendhu.
Publication year - 2020
Publication title -
international journal of innovative science and research technology
Language(s) - English
Resource type - Journals
ISSN - 2456-2165
DOI - 10.38124/ijisrt20aug617
Subject(s) - attendance , computer science , fingerprint (computing) , biometrics , phone , set (abstract data type) , mobile phone , multimedia , artificial intelligence , real time computing , operating system , linguistics , philosophy , economics , programming language , economic growth
Attendance management is an important procedure in an educational institution as well as in business organizations. Most of the available methods are time consuming and manipulative. The traditional method of attendance management is carried out in handwritten registers. Other than the manual method, there exist biometric methods like fingerprint and retinal scan, RFID tags, etc. All of these methods have disadvantages, therefore, in order to avoid these difficulties here, we introduce a new method for attendance management using deep learning technology. Using deep learning we can easily train a data-set. Real-time face algorithms are used and recognized faces of students in real-time while attending lectures. This system aims to be less time- consuming in comparison to the existing system of marking attendance.The program runs on anaconda flask server.Here real time image is captured using mobile phone camera. The faces on the image of the persons are then recognized and attendance is marked on an excel file.