Cite this DOI
10.46243/jst.2022.v7.i01.pp1-16 · Machine Learning Algorithms for Handwritten Devanagari Character Recognition: A Systematic Review
APA (7th edition)
Mimansha Agrawal, M. A. (2023). Machine Learning Algorithms for Handwritten Devanagari Character Recognition: A Systematic Review. *Journal of Science & Technology*, *7*(1), 1–16. https://doi.org/10.46243/jst.2022.v7.i01.pp1-16
⬇ text Italics are shown as *asterisks* in plain text — the journal or book title and the volume.
BibTeX
@article{mimanshaagrawal2023machine,
author = {Mimansha Agrawal, Mimansha Agrawal},
title = {{Machine Learning Algorithms for Handwritten Devanagari Character Recognition: A Systematic Review}},
journal = {Journal of Science \& Technology},
year = {2023},
month = {jul},
volume = {7},
number = {1},
pages = {1--16},
publisher = {Longman Publishers},
issn = {2456-5660},
doi = {10.46243/jst.2022.v7.i01.pp1-16},
url = {https://doi.org/10.46243/jst.2022.v7.i01.pp1-16},
language = {en},
abstract = {Devanagari Character Recognition is a system in which handwritten Image is recognized and converted into a digital form. Devanagari handwritten character recognition system is based on Deep learning technique, which manages the recognition of Devanagari script particularly Hindi. This recognition system mainly has five stages i.e. Pre-processing, Segmentation, Feature Extraction, Prediction and Post processing. This paper has analyzed the approach for recognition of handwritten Devanagari characters. There are various approaches to solve this. Some of the methods along with their accuracy and techniques used are discussed here. Depending upon the dataset and accuracies of each character the techniques differs}
}RIS (EndNote, Zotero, Mendeley)
TY - JOUR TI - Machine Learning Algorithms for Handwritten Devanagari Character Recognition: A Systematic Review AU - Mimansha Agrawal, Mimansha Agrawal JO - Journal of Science & Technology PY - 2023 DA - 2023/07/26/ VL - 7 IS - 1 SP - 1 EP - 16 PB - Longman Publishers SN - 2456-5660 LA - en AB - Devanagari Character Recognition is a system in which handwritten Image is recognized and converted into a digital form. Devanagari handwritten character recognition system is based on Deep learning technique, which manages the recognition of Devanagari script particularly Hindi. This recognition system mainly has five stages i.e. Pre-processing, Segmentation, Feature Extraction, Prediction and Post processing. This paper has analyzed the approach for recognition of handwritten Devanagari characters. There are various approaches to solve this. Some of the methods along with their accuracy and techniques used are discussed here. Depending upon the dataset and accuracies of each character the techniques differs DO - 10.46243/jst.2022.v7.i01.pp1-16 UR - https://doi.org/10.46243/jst.2022.v7.i01.pp1-16 ER -
CSL-JSON
{
"type": "article-journal",
"id": "10.46243/jst.2022.v7.i01.pp1-16",
"DOI": "10.46243/jst.2022.v7.i01.pp1-16",
"URL": "https://doi.org/10.46243/jst.2022.v7.i01.pp1-16",
"title": "Machine Learning Algorithms for Handwritten Devanagari Character Recognition: A Systematic Review",
"source": "Smart Scholars DOI Registry",
"container-title": "Journal of Science & Technology",
"author": [
{
"family": "Mimansha Agrawal",
"given": "Mimansha Agrawal"
}
],
"issued": {
"date-parts": [
[
2023,
7,
26
]
]
},
"volume": "7",
"issue": "1",
"page": "1-16",
"publisher": "Longman Publishers",
"language": "en",
"abstract": "Devanagari Character Recognition is a system in which handwritten Image is recognized and converted into a digital form. Devanagari handwritten character recognition system is based on Deep learning technique, which manages the recognition of Devanagari script particularly Hindi. This recognition system mainly has five stages i.e. Pre-processing, Segmentation, Feature Extraction, Prediction and Post processing. This paper has analyzed the approach for recognition of handwritten Devanagari characters. There are various approaches to solve this. Some of the methods along with their accuracy and techniques used are discussed here. Depending upon the dataset and accuracies of each character the techniques differs",
"ISSN": "2456-5660"
} ⬇ .json What citeproc and reference managers read; the DOI system hands it out for Accept: application/vnd.citationstyles.csl+json, and so does this registry's resolver.
From the record as registered (version 2) — the record and its history. Programs: https://registry.smartscholars.in/api.php?action=cite&doi=10.46243%2Fjst.2022.v7.i01.pp1-16 gives all four in one JSON answer.
