Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

A Benchmark Dataset for Manipuri Meetei-Mayek Handwritten Character Recognition

Domaine:

natural language processing

Type de record:

dataset
Créateur:
Sin
Éditeur:
IEE
Hôte:avatar
A benchmark dataset is always required for any classification or recognition system. To the best of our knowledge, no benchmark dataset exists for handwritten character recognition of Manipuri Meetei-Mayek script in public domain so far.Manipuri, also referred to as Meeteilon or sometimes Meiteilon, is a Sino-Tibetan language and also one of the Eight Scheduled languages of Indian Constitution. It is the official language and lingua franca of the southeastern Himalayan state of Manipur, in northeastern India. This language is also used by a significant number of people as their communicating language over the north-east India, and some parts of Bangladesh and Myanmar. It is the most widely spoken language in Northeast India after Bengali and Assamese languages.In this work, we introduce a handwritten Manipuri Meetei-Mayek character dataset which consists of more than 5000 data samples which were collected from a diverse population group that belongs to different age groups (from 4 years to 60 years), genders, educational backgrounds, occupations, communities from three different districts of Manipur, India (Imphal East District, Thoubal District and Kangpokpi District) during March and April 2019. Each individual was asked to write down all the Manipuri characters on one A4-size paper. The recorded responses are scanned with the help of a scanner and then each character is manually segmented from the scanned images.This dataset consists of segmented scanned images of handwritten Manipuri Meetei-Mayek characters (Mapi Mayek, Lonsum Mayek, Cheitap Mayek, Cheising Mayek, Khutam Mayek) of size 128X128 pixels in .JPG format as well as in .MAT format.

Visit

doi.orgieee-dataport.org

Tasks

computer visionoptical character recognition

Tags

Computer VisionImage ProcessingOtherOptical character recognitionHandwritten character recognitionNatural Language ProcessingManipuriMeetei Mayek

Licenses

Creative Commons Attributionhttps://creativecommons.org/licenses/by/4.0

Similaires

A neural network based handwritten Meitei Mayek alphabet optical character recognition systemBenchmark Pashto Handwritten Character Dataset and Pashto Object Character Recognition (OCR) Using Deep Neural Network with Rule Activation Function قياس مجموعة بيانات الأحرف البشتوية المكتوبة بخط اليد والتعرف على الأحرف البشتوية (OCR) باستخدام الشبكة العصبية العميقة مع وظيفة تنشيط القاعدة Benchmark Pashto Handwritten Character Dataset and Pashto Object Character Recognition (OCR) Using Deep Neural Network with Rule Activation Function Benchmark Pashto Handwritten Character Dataset and Pashto Object Character Recognition (OCR) Using Deep Neural Network with Rule Activation FunctionAMHCD: A Database for Amazigh Handwritten Character Recognition ResearchshraddhaA2/handwritten-amharic-character-recognitionsohankandagatla/Handwritten-Amharic-Character-Recognitionnatenaile/Handwritten-Amharic-Character-Recognition

A neural network based handwritten Meitei Mayek alphabet optical character recognition system

Benchmark Pashto Handwritten Character Dataset and Pashto Object Character Recognition (OCR) Using Deep Neural Network with Rule Activation Function قياس مجموعة بيانات الأحرف البشتوية المكتوبة بخط اليد والتعرف على الأحرف البشتوية (OCR) باستخدام الشبكة العصبية العميقة مع وظيفة تنشيط القاعدة Benchmark Pashto Handwritten Character Dataset and Pashto Object Character Recognition (OCR) Using Deep Neural Network with Rule Activation Function Benchmark Pashto Handwritten Character Dataset and Pashto Object Character Recognition (OCR) Using Deep Neural Network with Rule Activation Function

In the area of machine learning, different techniques are used to train machines and perform differe

AMHCD: A Database for Amazigh Handwritten Character Recognition Research

shraddhaA2/handwritten-amharic-character-recognition

Deep learning-based recognition of handwritten Amharic characters using image classification. # Han

sohankandagatla/Handwritten-Amharic-Character-Recognition

A Django web app that recognizes handwritten Amharic characters using a hybrid XGBoost + VGG16 model

natenaile/Handwritten-Amharic-Character-Recognition

Combining CNN-based feature extraction with classical machine learning classifiers enables accurate