A Novel Approach for Facial Attendance:AttendXNet


  • Kawal Arora Signy Advanced Technologies
  • Ankur Singh Bist Signy Advanced Technologies
  • Roshan Prakash Signy Advanced Technologies
  • Saksham Chaurasia Signy Advanced Technologies




Feature extraction, Support Vector Machine, Muli-layer Neural Network, Face Anti-spoofing, Faiss


Recent advancements in the area of facial recognition and verification introduced the possibility of facial attendance for various use cases. In this paper we present a system named as AttendXNet. Our method uses the ResNet and Multi-layer feed forward network to achieve the state of art results. Extensive analysis of various deep learning and machine learning techniques 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 end pipeline to implement an attendance system for various use cases.


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How to Cite

Arora, K., Bist, A. S., Prakash, R., & Chaurasia, S. (2020). A Novel Approach for Facial Attendance:AttendXNet. Aptisi Transactions on Technopreneurship (ATT), 2(2), 104–111. https://doi.org/10.34306/att.v2i2.86