@article{Arora_Bist_Prakash_Chaurasia_2020, title={A Novel Approach for Facial Attendance:AttendXNet}, volume={2}, url={https://att.aptisi.or.id/index.php/att/article/view/86}, DOI={10.34306/att.v2i2.86}, abstractNote={<p>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.</p>}, number={2}, journal={Aptisi Transactions on Technopreneurship (ATT)}, author={Arora, Kawal and Bist, Ankur Singh and Prakash, Roshan and Chaurasia, Saksham}, year={2020}, month={Jun.}, pages={104–111} }