Hiragana character classification using convolutional neural networks methods based on Adam, SGD, and RMSProps optimizer

Purpose: Hiragana image classification poses a significant challenge within the realms of image processing and machine learning. Despite advances, achieving high accuracy in Hiragana character recognition remains elusive. In response, this research attempts to enhance...

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Bibliographic Details

Main Authors:	Wahyu Mulyono, Ibnu Utomo, Susanto, Ajib, Christy Atika Sari, Kusumawati, Yupie, Mehedul Islam, Hussain Md, Doheir, Mohamed A.S.
Format:	Article
Language:	en
Published:	Department of Computer Science, Universitas Negeri Semarang 2024
Online Access:	http://eprints.utem.edu.my/id/eprint/28578/2/02723220120251838471629.pdf http://eprints.utem.edu.my/id/eprint/28578/ https://journal.unnes.ac.id/journals/sji/article/view/2313/432
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