10.46243/jst.2021.v6.i06.pp94-102 registered
Comparative Analysis of Handwritten Digit Recognition Using Logistic Regression, SVM, KNN and CNN Algorithms
Resolves to https://www.jst.org.in/index.php/pub/article/view/520
Held by Longman Publishers (India) · prefix 10.46243 live · DOI address https://doi.org/10.46243/jst.2021.v6.i06.pp94-102
Registered 29 Sep 2026 via crossref · record version 2 · last change 29 Sep 2026, 11:59 PM · record sha256 f2298259e3982cf3…
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What the DOI identifies
JournalArticle — an article in a journal · Digital · Visual · en
Comparative Analysis of Handwritten Digit Recognition Using Logistic Regression, SVM, KNN and CNN Algorithms (PrincipalTitle)
Published 2021-12-18
Part of Journal of Science & Technology · ISSN 2456-5660 · volume 06 · issue 06 · pages 94–102
Agents
- Dr. R. Pradeep Kumar Reddy (author)
- C. Naga Raju (author)
- Longman Publishers (publisher)
Identifiers DOI 10.46243/jst.2021.v6.i06.pp94-102
Abstract
The style of handwriting varies from person to person. Handwritten numbers are not always the same size, orientation and width. To develop a system to understand this, the machine recognizes handwritten digit images and classifies them into 10 digits (from 0 to 9).Handwritten digit recognition is a technology which is used for automatic recognizing and detecting handwritten digital data through various machine learning models. This paper uses a different machine learning algorithms to improve productivity and a variety of models to reduce complexity. Machine Learning is an artificial intelligence application which learns from previous experiences and it automatically improves with the previous experiences. This paper is about recognizing handwritten digits from 0 to 9 from the well-known Modified National Institute of Standards and Technology(MNIST) dataset, then comparison takes place between machine learning algorithms like Support Vector Machine(SVM), logistic regression, K-Nearest Neighbor (KNN) and deep learning algorithm like CNN
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Each element by the standard's name (Annex B: reference elements, then administrative) and the Handbook's (in grey), read off the record above.
| Element | Value | In the record |
|---|---|---|
| DOI Name DOI name | 10.46243/jst.2021.v6.i06.pp94-102 | doi |
| Referent Type referentType | Creation | referent |
| Referent Sub-Type referentSubType | JournalArticle — an article in a journal | type |
| Referent Name(s) referentName(s) | Comparative Analysis of Handwritten Digit Recognition Using Logistic Regression, SVM, KNN and CNN Algorithms (PrincipalTitle, en) | titles |
| Basic Metadata basicMetadata | author: Dr. R. Pradeep Kumar Reddy author: C. Naga Raju publisher: Longman Publishers published: 2021-12-18 part of: Journal of Science & Technology · ISSN 2456-5660 · vol. 06 · no. 06 · pp. 94–102 language: en form: Digital · Visual · Language | agents, dates, container, language, structural_type, modes, characters |
| Referent Identifier(s) alternateIdentifier(s) | none besides the DOI | identifiers, relations (IsSameAs) |
| Registration Authority registrationAuthorityCode | Crossref — issued by Crossref (member 25296); held here as a copy | record.source_agency (our code, ra_doi_name, for names issued here once appointed) |
| Created Date issueDate | 2026-09-08 | record.registered (when the DOI name was first registered) |
| relatedIdentifiers | none needed — the descriptive metadata is in this record | container, relations (only where the descriptive metadata lives at another identifier) |
complete Every System Metadata element is here, with the basic metadata a journal article needs.
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History — the ledger
Every change to this DOI, in order, as it was recorded. Entries are only ever added, never changed or removed.
| # | When | What | By | Changes |
|---|---|---|---|---|
| 1 | 29 Sep 2026, 10:00 PM | register registered at Crossref; record read from api.crossref.org | Administrator (admin) | 104 fields set · sha256 24021b74ed65… |
| 2 | 29 Sep 2026, 11:59 PM | update record re-read from api.crossref.org | Administrator (admin) | container.titles.0.value: |
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