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A Novel Approach for Facial Attendance:AttendXNet

Aptisi Transactions on Technopreneurship (ATT) · Vol. 2 No. 2 (2020) · pp. 104–111

DOI
10.34306/att.v2i2.86
ISSN
2656-8888, 2655-8807
Published
2020-06-05
Publisher
Pandawan
Language
en
License
creativecommons.org/licenses/by/4.0

Abstract

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.

Keywords

Collaboration network of the authors

28 authors · 68 co-authorship links

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universitas Raharja
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Bhupesh RawatAffiliation unknown3
Srishti BiswasAffiliation unknown1
Ritesh MishraAffiliation unknown1
Marviola HardiniAffiliation unknown1
Megha UpretiAffiliation unknown1
Chitra PandeyAffiliation unknown1
Buphest RawatAffiliation unknown1
Mukti BudiartoUniversitas Raharja1
Ari AsmawatiAffiliation unknown1
Prakriti RashiAffiliation unknown1
Wahyu Yustika PrihastiwiAffiliation unknown1
Siti Nurindah SariAffiliation unknown1
Dedeh SupriyantiAffiliation unknown1
Vonda ElmandaAffiliation unknown1
MulyatiAffiliation unknown1
Muhammad FakhrezzyAffiliation unknown1
Regina Dinda OctavyraAffiliation unknown1
Desy AprianiAffiliation unknown1
Efa Ayu NabilaAffiliation unknown1
Nur Ihsan PermadiAffiliation unknown1
Nizirwan AnwarAffiliation unknown1
Noor Azura ZakariaAffiliation unknown1
Greisy JacquelineAffiliation unknown1
Li Wei MingAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://att.aptisi.or.id/index.php/att/oai, first harvested 6 Nov 2026, last seen 8 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">A Novel Approach for Facial Attendance:AttendXNet</dc:title>
	<dc:creator xml:lang="en">Arora, Kawal</dc:creator>
	<dc:creator xml:lang="en">Bist, Ankur Singh</dc:creator>
	<dc:creator xml:lang="en">Prakash, Roshan</dc:creator>
	<dc:creator xml:lang="en">Chaurasia, Saksham</dc:creator>
	<dc:subject xml:lang="en">Feature extraction, Support Vector Machine, Muli-layer Neural Network, Face Anti-spoofing, Faiss</dc:subject>
	<dc:description xml:lang="en">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.</dc:description>
	<dc:publisher xml:lang="en">Pandawan</dc:publisher>
	<dc:date>2020-06-05</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:format>application/epub+zip</dc:format>
	<dc:identifier>https://att.aptisi.or.id/index.php/att/article/view/86</dc:identifier>
	<dc:identifier>10.34306/att.v2i2.86</dc:identifier>
	<dc:source xml:lang="en">Aptisi Transactions on Technopreneurship (ATT); Vol. 2 No. 2 (2020): September; 104 - 111</dc:source>
	<dc:source xml:lang="id">Aptisi Transactions On Technopreneurship (ATT); Vol 2 No 2 (2020): September; 104 - 111</dc:source>
	<dc:source>2656-8888</dc:source>
	<dc:source>2655-8807</dc:source>
	<dc:source>10.34306/att.v2i2</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://att.aptisi.or.id/index.php/att/article/view/86/33</dc:relation>
	<dc:relation>https://att.aptisi.or.id/index.php/att/article/view/86/34</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2020 Kawal Arora, Ankur Singh Bist, Roshan Prakash, Saksham Chaurasia</dc:rights>
	<dc:rights xml:lang="en">http://creativecommons.org/licenses/by/4.0</dc:rights>
</oai_dc:dc>