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Performance of hidden Markov model and dynamic Bayesian network classifiers on handwritten Arabic word recognition [PDF]
, 2011 This paper presents a comparative study of two machine learning techniques for recognizing handwritten Arabic words, where hidden Markov models (HMMs) and dynamic Bayesian networks (DBNs) were evaluated.
Alkhateeb, Jawad H. +3 more
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A multi-purpose dataset of Devanagari script comprising of isolated numerals and vowels
Data in Brief, 2022 This article presents handwritten isolated characters of the Devanagari script. Devanagari script contains ten numerals, 13 vowels, and 33 consonants. Devanagari Character dataset includes 23 different characters of numerals and vowels.
Duddela Sai Prashanth +2 more
doaj +1 more source
uTHCD: A New Benchmarking for Tamil Handwritten OCR
IEEE Access, 2021 The robustness of a typical Handwritten character recognition system relies on the availability of comprehensive supervised data samples. There has been considerable work reported in the literature about creating the database for several Indic scripts ...
Noushath Shaffi, Faizal Hajamohideen
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Machine Learning with Applications, 2021 The recognition of online handwriting is a vital application of pattern recognition, which involves the extraction of spatial and temporal information of handwritten patterns, and understanding the handwritten text while writing on the digital surface ...
Sukhdeep Singh +2 more
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End-to-End Historical Handwritten Ethiopic Text Recognition Using Deep Learning
IEEE Access, 2023 Recognizing handwritten text is a challenging task, especially for scripts with numerous alphabets and symbols. The Ethiopic script has a vast character set and is used for historical documents in typewritten, handwritten, and hand-printed forms. However,
Ruchika Malhotra, Maru Tesfaye Addis
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A Survey on Arabic Handwritten Script Recognition Systems
International Journal of Artificial Intelligence and Machine Learning, 2021 The optical character recognition (OCR) system is still an active research field in pattern recognition. Such systems can identify, recognize and distinguish electronically between characters and texts, printed or handwritten. They can also do a transformation of such data type into machine-processable form to facilitate the interaction between user ...
Soumia Djaghbellou +3 more
openaire +2 more sources
Urdu handwritten text recognition: a survey
IET Image Processing, 2020 Work on the problem of handwritten text recognition in Urdu script has been an active research area. A significant progress is made in this interesting and challenging field in the last few years.
Mujtaba Husnain +5 more
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Recognition of Handwritten Character of Manipuri Script
Journal of Computers, 2010 In this paper a backpropagation neural network based handwritten characters (Mapum Mayek ) recognition system of Manipuri Script is investigated. This paper presents various steps involved in the recognition process. It begins with thresholding of gray level image into binarised image, then from the binarised image the character pattern is segmented ...
Tangkeshwar Thokchom +3 more
openaire +1 more source
Multi-script Handwritten Digit Recognition Using Multi-task Learning [PDF]
, 2021 Handwritten digit recognition is one of the extensively studied area in machine learning. Apart from the wider research on handwritten digit recognition on MNIST dataset, there are many other research works on various script recognition.
Gondere, Mesay Samuel +3 more
core +1 more source
Online Handwritten Arabic Scripts Recognition Using Stroke-Based Class Labeling Scheme
International Journal of Computational Intelligence Systems, 2020 With the increasing availability of pen-based user interfaces, we often come upon multiple data sets of online handwritten scripts such as letters, words, etc., that are collected based on a viable interface.
Rabiaa Zitouni, Hala Bezine, Najet Arous
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