Kernel Metadata Declaration — on demand
ISO 26324 asks a DOI Registration Agency to produce a Kernel Metadata Declaration for every DOI it issues. Give any DOI: its public record becomes a record in the Smart Scholars DOI Metadata Format 1.0, checked against every rule, and declared as the Kernel XML.
✓ Meets every rule of the format
The record below is complete and every controlled value is a DOI Attribute Value Set 2.3 spelling. The Declaration on the right follows DOIMetadataKernel.xsd element by element.
What the DOI identifies
Facial Recognition Attendance System
10.46243/jst.2021.v6.i04.pp383-387 · JournalArticle — an article in a journal · Digital · Visual · Language · en
Published 2021-08-16
Part of Journal of Science & Technology · ISSN 2456-5660 · vol. 06 · no. 01 · pp. 383–387
Principal agents
- Ayush Chirde (author → Author)
- Payal Kamthe (author → Author)
- Aishwarya Somvanshi (author → Author)
- Longman Publishers (publisher → Publisher)
Also in the record, outside the Kernel: the abstract, the licence, 4 links, 11 references. Source: Crossref (member 25296), registered 2026-09-10, last deposited 2026-09-20.
System metadata — ISO 26324:2025, Annex B · DOI Handbook 10.1
Each element by the standard's name and the Handbook's (in grey), read off the record.
| DOI Name DOI name | 10.46243/jst.2021.v6.i04.pp383-387 |
| Referent Type referentType | Creation |
| Referent Sub-Type referentSubType | JournalArticle — an article in a journal |
| Referent Name(s) referentName(s) | Facial Recognition Attendance System (PrincipalTitle, en) |
| Basic Metadata basicMetadata | author: Ayush Chirde author: Payal Kamthe author: Aishwarya Somvanshi publisher: Longman Publishers published: 2021-08-16 part of: Journal of Science & Technology · ISSN 2456-5660 · vol. 06 · no. 01 · pp. 383–387 language: en form: Digital · Visual · Language |
| Referent Identifier(s) alternateIdentifier(s) | none besides the DOI |
| Registration Authority registrationAuthorityCode | Crossref — issued by Crossref (member 25296); held here as a copy |
| Created Date issueDate | 2026-09-10 |
| relatedIdentifiers | none needed — the descriptive metadata is in this record |
The record
{
"format": "smartscholars-doi-metadata/1.0",
"doi": "10.46243/jst.2021.v6.i04.pp383-387",
"referent": "Creation",
"type": "JournalArticle",
"structural_type": "Digital",
"modes": [
"Visual"
],
"characters": [
"Language"
],
"titles": [
{
"value": "Facial Recognition Attendance System",
"type": "PrincipalTitle",
"lang": "en"
}
],
"identifiers": [
{
"type": "DOI",
"value": "10.46243/jst.2021.v6.i04.pp383-387"
}
],
"agents": [
{
"role": "author",
"name": {
"given": "Ayush",
"family": "Chirde"
},
"sequence": "first"
},
{
"role": "author",
"name": {
"given": "Payal",
"family": "Kamthe"
},
"sequence": "additional"
},
{
"role": "author",
"name": {
"given": "Aishwarya",
"family": "Somvanshi"
},
"sequence": "additional"
},
{
"role": "publisher",
"name": {
"org": "Longman Publishers"
}
}
],
"dates": {
"published": "2021-08-16",
"date_type": "PublicationDate",
"online": "2021-08-16"
},
"language": "en",
"container": {
"type": "Journal",
"titles": [
{
"value": "Journal of Science & Technology",
"type": "PrincipalTitle"
}
],
"identifiers": [
{
"type": "ISSN",
"value": "2456-5660",
"medium": "electronic"
}
],
"volume": "06",
"issue": "01",
"pages": {
"first": "383",
"last": "387"
}
},
"links": [
{
"url": "https://www.jst.org.in/index.php/pub/article/view/675",
"return_type": "text/html",
"primary": true
},
{
"url": "https://www.jst.org.in/index.php/pub/article/download/675/604",
"purpose": "text-mining",
"return_type": "application/pdf"
},
{
"url": "https://www.jst.org.in/index.php/pub/article/download/675/2735",
"purpose": "text-mining",
"return_type": "application/xml"
},
{
"url": "https://www.jst.org.in/index.php/pub/article/view/675/604",
"purpose": "similarity-checking"
}
],
"abstract": {
"value": "In this digital era, face recognition system plays a very important role in nearly every sector. Face recognition is one of the mostly used natural science. it'll used for security, authentication, identification, and has got a lot of blessings. Despite of obtaining low accuracy once compared to iris recognition and fingerprint recognition, it is being wide used due to its contactless and non-invasive technique. what's a lot of, face recognition system can even be used for attending marking in colleges, colleges, offices, etc. This system aims to make a class attending system that uses the thought of face recognition as existing manual attending system is time overwhelming and cumbersome to stay up. And there's conjointly prospects of proxy attending. Thus, the requirement for this technique can increase. this technique consists of four phases- data creation, face detection, face recognition, attending updating. Data is created by the pictures of the students in class. Face detection and recognition is performed exploitation Haar-Cascade classifier and native Binary Pattern chart algorithmic program severally. Faces unit detected and recognized from live streaming video of the room. attending are armored to the individual faculty at the tip of the session. it's standard that marking attending of the scholars is associate degree obligatory half in academe. standard technique of marking the attending is being followed by numerous establishments and Universities with several manual interventions. to scale back time consumption and human effort, the employment of associate degree automatic method of marking attending supported image process may be implemented. Authors have projected a sensible attending observance system through face detection and recognition techniques supported their face expression. a group of pictures of the scholars are antecedently fed to the system against that the live pictures of the scholars are compared and attending would be recorded supported facial characteristics. The projected approach uses CNN rule for coaching the pictures and LBPH visual descriptor for image classification. This models are going to be capable of providing higher degree of accuracy compared to already existing literature work. Authors have compared their experimental results with the present approaches and located satisfactory",
"lang": "en"
},
"license": {
"url": "https://creativecommons.org/licenses/by/4.0",
"start": "2021-08-16",
"applies_to": "vor"
},
"references": [
{
"key": "ref1",
"unstructured": "K. R. Gutierrez, D. C. Perez, J. O. Mercado, M. N. Miyatake, and Hector Perez-Meana, A face"
},
{
"key": "ref2",
"unstructured": "recognition algorithmic rule exploitation chemist phases and bar chart exploit, International Journal"
},
{
"key": "ref3",
"doi": "10.25291/vr/34-vr-41",
"unstructured": "of Computers, Vol. 5, No.1,pp.34-41,2011"
},
{
"key": "ref4",
"unstructured": "Bromby, Michael C., At Face Value (February 28, 2003). New Law Journal Expert Witness"
},
{
"key": "ref5",
"doi": "10.1055/s-2003-45513",
"unstructured": "Supplement, pp. 301-303, February 28, 2003"
},
{
"key": "ref6",
"unstructured": "Vytautas Perlibakas, ”Face Recognition using Principal Component Analysis and Log-Gabor Filters”, March 2005. 23 pages"
},
{
"key": "ref7",
"unstructured": "Kyungnam Kim, ”Face recognition usi ng principal component analysis”, International Conference on Computer Vision and pattern recognition, 1998"
},
{
"key": "ref8",
"doi": "10.1016/j.patcog.2006.12.002",
"unstructured": "Zhang, Xiaoxun & Jia, Yunde. (2007). A linear discriminant analysis framework based on a random subspace for face recognition. Pattern Recognition. 40. 2585-2591. 10.1016/j.patcog.2006.12.002"
},
{
"key": "ref9",
"unstructured": "Changjun Zhou, Xiaopeng Wei, Qiang Zhang, Xiaoyong Fang,” Fisher's linear discriminant (FLD) and support vector machine (SVM) in non-negative matrix factorization (NMF) residual space for face recognition”, Optica Applicata, Vol. XL, No. 3, 2010"
},
{
"key": "ref10",
"doi": "10.1109/ictss.2014.7013165",
"unstructured": "Adrian Rhesa Septian Siswanto, Anto Satriyo Nugroho, Maulahikmah Galinium, Implementation of Face Recognition Algorithm for Biometrics-Based Time Attendance System, Bandung, Indonesia, 19 January 2015"
},
{
"key": "ref11",
"doi": "10.7763/ijcce.2012.v1.28",
"unstructured": "Nirmalya Kar, Mrinal Kanti Debbarma, Ashim Saha, and Dwijen Rudra Pal, ”Study of Implementing Automated Attendance System Using Face Recognition Techniques”, International Journal of Computer and Communication Engineering, Vol. 1, No. 2, July 2012"
}
],
"record": {
"registrant": "Longman Publishers",
"registered": "2026-09-10",
"updated": "2026-09-20",
"issue_number": 1,
"source": "crossref-api",
"source_agency": "Crossref (member 25296)"
}
}The Kernel Metadata Declaration
DOIMetadataKernel.xsd · namespace http://www.doi.org/2010/DOISchema · Attribute Value Sets 2.3 · draft — the agency's DOI name is filled in on accreditation
<?xml version="1.0" encoding="UTF-8"?>
<!-- DRAFT declaration: Smart Scholars is not yet a DOI Registration Agency. registrationAgencyDoiName is a marker (10.0/ is no RA's prefix) and is filled in on accreditation. -->
<kernelMetadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.doi.org/2010/DOISchema https://www.doi.org/doi_schemas/DOIMetadataKernel.xsd" xmlns="http://www.doi.org/2010/DOISchema">
<referentDoiName>10.46243/jst.2021.v6.i04.pp383-387</referentDoiName>
<primaryReferentType>Creation</primaryReferentType>
<registrationAgencyDoiName>10.0/smart-scholars-draft</registrationAgencyDoiName>
<issueDate>2026-10-04</issueDate>
<issueNumber>1</issueNumber>
<referentCreation>
<name primaryLanguage="en">
<value>Facial Recognition Attendance System</value>
<type>PrincipalTitle</type>
</name>
<identifier>
<nonUriValue>10.46243/jst.2021.v6.i04.pp383-387</nonUriValue>
<uri returnType="text/html" doesContentNegotiation="true">https://doi.org/10.46243/jst.2021.v6.i04.pp383-387</uri>
<type>DOI</type>
</identifier>
<identifier>
<uri returnType="text/html">https://www.jst.org.in/index.php/pub/article/view/675</uri>
<type>URI</type>
</identifier>
<identifier>
<uri>https://www.jst.org.in/index.php/pub/article/download/675/604</uri>
<type>URI</type>
</identifier>
<identifier>
<uri returnType="application/xml">https://www.jst.org.in/index.php/pub/article/download/675/2735</uri>
<type>URI</type>
</identifier>
<identifier>
<uri>https://www.jst.org.in/index.php/pub/article/view/675/604</uri>
<type>URI</type>
</identifier>
<structuralType>Digital</structuralType>
<mode>Visual</mode>
<character>Language</character>
<type>JournalArticle</type>
<principalAgent>
<name>
<value>Ayush Chirde</value>
<type>PrincipalName</type>
</name>
<role>Author</role>
</principalAgent>
<principalAgent>
<name>
<value>Payal Kamthe</value>
<type>PrincipalName</type>
</name>
<role>Author</role>
</principalAgent>
<principalAgent>
<name>
<value>Aishwarya Somvanshi</value>
<type>PrincipalName</type>
</name>
<role>Author</role>
</principalAgent>
<principalAgent>
<name>
<value>Longman Publishers</value>
<type>PrincipalName</type>
</name>
<role>Publisher</role>
</principalAgent>
<linkedCreation>
<name>
<value>Journal of Science & Technology</value>
<type>PrincipalTitle</type>
</name>
<identifier>
<nonUriValue>2456-5660</nonUriValue>
<type>ISSN</type>
</identifier>
<referentCreationRole>Part</referentCreationRole>
<referentCreationSequenceIdentifier>
<value>06</value>
<type>VolumeNumber</type>
</referentCreationSequenceIdentifier>
<referentCreationSequenceIdentifier>
<value>01</value>
<type>IssueNumber</type>
</referentCreationSequenceIdentifier>
<referentCreationSequenceIdentifier>
<value>383-387</value>
<type>PageNumber</type>
</referentCreationSequenceIdentifier>
</linkedCreation>
<language>en</language>
<languageOfReferentContent>
<language>en</language>
<languageOfReferentContentType>Original</languageOfReferentContentType>
</languageOfReferentContent>
<creationDate>
<date>2021-08-16</date>
<creationDateType>PublicationDate</creationDateType>
</creationDate>
</referentCreation>
</kernelMetadata>
