Work

Research Comparative Analysis of OCR Models for Urdu Language Characters Recognition

Year: 2024

Type: article

Abstract: There have been many research works to digitalize Urdu Characters through machine learning algorithms. The algorithms that were already used for Urdu Optical Character Recognition [OCR] are Convolutional Neural Network [CNN], Recurrent Neural Network [RNN], and Transformer etc. There are also many machine learning algorithms that have not been used for Urdu OCR e.g Support Vector Machine, Graph Neural Network etc. This research paper proposes a comparative study between the performances of the already implemented Urdu OCR on some of following algorithms like Convolutional Neural Network/ Transformer Model it also proposed a new implemented Urdu OCR using on Support Vector Machine algorithm.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.14028815

Authors: Muhammad Murad, Muhammad Shahzad, Naheeda Fareed

Institution: Alhamd Islamic University

Language: English

Topic: Handwritten Text Recognition Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W6967936941

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