ATTENDANCE MANAGEMENT SYSTEM USING FACE RECOGNITION AND DEEP LEARNING

Author(s):  
Filip Marenčić ◽  
Zlatko Stapić ◽  
Petra Grd

Attendance Management System under unconstrained video using face recognition technology has made a great variation from the traditional method of attendance marking system. This attendance management system has been developed under the domain of Deep Learning by using Face recognition. Automatic Attendance Management under unconstrained video using face recognition systems which automatically mark attendance by detecting end to end face from the frames obtained from live stream video of surveillance camera which placed in center of the classroom. From the recognized faces, it will be compared with stored images in database, then the attendance report will be generated and it also provides attendance reports to parents of the absentee’s student.


Author(s):  
K. V. Prasad Reddy ◽  
R. Chaitanya Latha ◽  
M. Lohitha ◽  
R. Sonia ◽  
A. B. Usha

To Maintain the attendance record with day to day activities is a challenging task. The conventional method of calling name of each student is time consuming and there is always a chance of proxy attendance. The smart attendance management will replace the manual method, which takes a lot of time consuming and difficult to maintain. There are many biometric processes, in that face recognition is the best method. Here we are using the computer vision which is a field of deep learning that is used for the camera reading and writing and using TkInter to create a GUI application.


Author(s):  
Yosua Alvin Adi Soetrisno ◽  
Aghus Sofwan ◽  
M. Arfan ◽  
Sumardi

2020 ◽  
Vol 9 (3) ◽  
pp. 25-30
Author(s):  
So Yeon Jeon ◽  
Jong Hwa Park ◽  
Sang Byung Youn ◽  
Young Soo Kim ◽  
Yong Sung Lee ◽  
...  

Face recognition plays a vital role in security purpose. In recent years, the researchers have focused on the pose illumination, face recognition, etc,. The traditional methods of face recognition focus on Open CV’s fisher faces which results in analyzing the face expressions and attributes. Deep learning method used in this proposed system is Convolutional Neural Network (CNN). Proposed work includes the following modules: [1] Face Detection [2] Gender Recognition [3] Age Prediction. Thus the results obtained from this work prove that real time age and gender detection using CNN provides better accuracy results compared to other existing approaches.


2017 ◽  
Vol 2 (2) ◽  
pp. 31-35
Author(s):  
Akshada Abnave ◽  
Charulata Banait ◽  
Mrunalini Chopade ◽  
Supriya Godalkar ◽  
Soudamini Pawar ◽  
...  

M-learning or mobile learning is defined as learning through mobile apps, social interactions and online educational hubs via Internet or network using personal mobile devices such as tablets and smart phones. However, in such open environment examination security is most challenging task as students can exchange mobile devices or also can exchange information through network during examination. This paper aims to design secure examination management system for m- learning and provide appropriate mechanism for anti- impersonation to ensure examination security. The users are authenticated through OTP. To prevent students from exchanging mobile devices during examination, system re-authenticates students automatically through face recognition at random time without interrupting the test. The system also provides external click management i.e. prevent students from accessing online sites and already downloaded files during examination.


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