A SURVEY ON ADVANCED ATTENDANCE API | Zendy

J Jeevandeep | Zendy; G Chintan | Zendy; G M Deekshith | Zendy; C R Anirudh | Zendy; R Sandeep | Zendy

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A SURVEY ON ADVANCED ATTENDANCE API

Author(s) -

J Jeevandeep,

G Chintan,

G M Deekshith,

C R Anirudh,

R Sandeep

Publication year - 2022

Publication title -

international research journal of computer science

Language(s) - English

Resource type - Journals

ISSN - 2393-9842

DOI - 10.26562/irjcs.2022.v0902.001

Subject(s) - biometrics , attendance , scope (computer science) , computer science , identification (biology) , facial recognition system , iris recognition , process (computing) , field (mathematics) , multimedia , computer security , artificial intelligence , feature extraction , operating system , botany , mathematics , pure mathematics , economics , biology , programming language , economic growth

In today's rapidly changing world, automatic face recognition (AFR) technologies have made significant advances. Keeping up with the attendance register day by day is a troublesome and tedious process. There are many robotized strategies for a similar application like biometrics, radio-frequency identification (RFID), iris detection, voice detection, and more. The objective of this paper is to review some of the state-of-the-art techniques used in the implementation of marking attendance. The existing methodologies show that there is a scope for improvement in the implementation of smart attendance. In our future work, we want to present a framework by utilizing deep learning and thereby tap into the potential that it guarantees in the field of face-based biometrics.

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