10.46243/jst.2018.v3.i05.pp81-90 registered
Recognition of Handwriting Characters Using an Artificial Neural Network
Resolves to https://www.jst.org.in/index.php/pub/article/view/196
Held by Longman Publishers (India) · prefix 10.46243 live · DOI address https://doi.org/10.46243/jst.2018.v3.i05.pp81-90
Registered 29 Sep 2026 via crossref · record version 2 · last change 29 Sep 2026, 11:59 PM · record sha256 d3d0943271a76f8c…
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What the DOI identifies
JournalArticle — an article in a journal · Digital · Visual · en
Recognition of Handwriting Characters Using an Artificial Neural Network (PrincipalTitle)
Published 2018-09-18
Part of Journal of Science & Technology · ISSN 2456-5660 · volume 03 · issue 05 · pages 81–90
Agents
- Dr S.B. Thorat (author)
- Dr. P.B. Tamsekar (author)
- Dr. P.R. Patil (author)
- Longman Publishers (publisher)
Identifiers DOI 10.46243/jst.2018.v3.i05.pp81-90
Abstract
Research in the area of handwriting recognition has several applications, including the digitization of handwritten documents and the ability to use handwriting as an input method for gadgets. In this project, an Artificial Neural Network (ANN) was used to produce a handwriting recognition system, and the Streamlit library was used to develop a graphical user interface (GUI). We preprocessed the photos by scaling, turning to grayscale, and normalising pixel values using a dataset of handwritten numbers from Kaggle. Two hidden layers with ReLU activation and Softmax activation for the output layer made up the ANN model's design. After adding the pytesseract library, the model had a 90% accuracy rate on the test dataset. Users could draw a digit and get results for digit recognition using the GUI interface. Future studies could concentrate on increasing precision and broadening the system's ability to recognise handwritten text. The overall potential of ANN and GUI technologies for handwriting recognition applications is demonstrated by this project
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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.2018.v3.i05.pp81-90 | doi |
| Referent Type referentType | Creation | referent |
| Referent Sub-Type referentSubType | JournalArticle — an article in a journal | type |
| Referent Name(s) referentName(s) | Recognition of Handwriting Characters Using an Artificial Neural Network (PrincipalTitle, en) | titles |
| Basic Metadata basicMetadata | author: Dr S.B. Thorat author: Dr. P.B. Tamsekar author: Dr. P.R. Patil publisher: Longman Publishers published: 2018-09-18 part of: Journal of Science & Technology · ISSN 2456-5660 · vol. 03 · no. 05 · pp. 81–90 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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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) | 92 fields set · sha256 f7679cbc827b… |
| 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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