Work

Hangul Character Recognition of A New Hangul Dataset with Vision Transformers Model

Year: 2024

Type: article

Abstract: This study aims to develop a Vision Transformers (ViT) model for recognizing Korean characters (Hangeul) in response to the growing interest in learning the Korean language and Korean culture in Indonesia. The research methodology involves training the ViT model using a comprehensive dataset of 29,636 base Korean characters. The ViT model has achieved a significant level of accuracy with the score of 93% in recognizing base Korean characters. By integrating deep learning, this study is expected to make a positive contribution to the development of language learning tools for Korean character recognition, unlocking its potential for applications and systems based on the Korean language.

Source: SINTECH (Science and Information Technology) Journal

DOI: 10.31598/sintechjournal.v7i3.1677

Authors: Aurelia Shana, Sutramiani Ni Putu, Desy Purnami Singgih Putri

Institution: Udayana University

Language: English

Topic: Handwritten Text Recognition Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

Funder: Universitas Udayana

OpenAlex ID: W4406188517

FWCI: 0.141

Cites:

Cited by: 1

Related to: 10