dc.contributor.author |
Gamlath, Yugani |
|
dc.contributor.author |
Pathiraja, Ashan |
|
dc.date.accessioned |
2024-03-26T04:45:31Z |
|
dc.date.available |
2024-03-26T04:45:31Z |
|
dc.date.issued |
2023 |
|
dc.identifier.citation |
Gamlath, Yugani; Pathiraja, Ashan (2023), Automated Face Recognition based Attendance Monitoring Approach for the Sustainable Economic Recovery in Sri Lanka, 8th International Conference on Advances in Technology and Computing (ICATC 2023), Faculty of Computing and Technology, University of Kelaniya Sri Lanka. Page 11-14. |
en_US |
dc.identifier.uri |
http://repository.kln.ac.lk/handle/123456789/27838 |
|
dc.description.abstract |
These days, biometric authentication methods, begin growing rapidly as one of promising authentication methods, besides the conventional authentication method. Almost all biometrics techniques require some actions by user, which are the user needs to place funds on the scanner to set the fingers. The user shall stand still in a fixed position in front of the camera for iris or retina identification process. The face recognition method has several external advantages compared to other biometric methods. Because this method can be done without action since the face image can be obtained by the camera. The new system can recognize the faces captured automatically by the camera accurately. And also this automated attendance monitoring method can use for the sustainable economic recovery in this economic crisis period in various phases. |
en_US |
dc.publisher |
Faculty of Computing and Technology, University of Kelaniya Sri Lanka. |
en_US |
dc.subject |
Recognition, Biometric authentication, Attendance, Face recognition, Automated, System |
en_US |
dc.title |
Automated Face Recognition based Attendance Monitoring Approach for the Sustainable Economic Recovery in Sri Lanka |
en_US |