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All Journal JAIS (Journal of Applied Intelligent System)
Rabei Raad Ali
Tun Hussein Onn Malaysia University

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CNN for Image Identification of Hiragana Based on Pattern Recognition using CNN Chaerul Umam; Andi Danang Krismawan; Rabei Raad Ali
Journal of Applied Intelligent System Vol 6, No 2 (2021): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v6i2.4586

Abstract

Hiragana is one of the letters in Japanese. In this study, CNN (Convolutional Neural Network) method used as identication method, while he preprocessing used thresholding. Then carry out the normalization stage and the filtering stage to remove noise in the image. At the training stage use maxpooling and danse methods as a liaison in the training process, wherea in testing stage using the Adam Optimizer method. Here, we use 1000 images from 50 hiragana characters with a ratio of 950: 50, 950 as training data and 50 data as testing data. Our experiment yield accuracy in 95%.
Co-Authors Andi Danang Krismawan Chaerul Umam