A Novel Approach for Facial Attendance:AttendXNet | Zendy

Ankur Singh Bist | Zendy

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A Novel Approach for Facial Attendance:AttendXNet

Author(s) -

Ankur Singh Bist

Publication year - 2020

Publication title -

aptisi transactions on technopreneurship (att)

Language(s) - English

Resource type - Journals

eISSN - 2656-8888

pISSN - 2655-8807

DOI - 10.34306/att.v2i2.86

Subject(s) - attendance , computer science , artificial intelligence , facial recognition system , deep learning , face (sociological concept) , residual neural network , machine learning , spoofing attack , pattern recognition (psychology) , computer security , social science , sociology , economics , economic growth

Recent advancements in the area of facial recognition and verification introduced thepossibility of facial attendance for various use cases. In this paper we present a system namedas AttendXNet. Our method uses the ResNet and Multi-layer feed forward network to achievethe state of art results. Extensive analysis of various deep learning and machine learningtechniques is described. Face anti-spoofing is a major challenge in facial attendance.Extended-MobileNet is used to resolve the same issue. We also introduced the end to endpipeline to implement an attendance system for various use cases.

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