Eko Hari Rachmawanto
Dian Nuswantoro University

Published : 10 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : IAES International Journal of Artificial Intelligence (IJ-AI)

Handwritten Javanese script recognition method based 12-layers deep convolutional neural network and data augmentation Ajib Susanto; Ibnu Utomo Wahyu Mulyono; Christy Atika Sari; Eko Hari Rachmawanto; De Rosal Ignatius Moses Setiadi; Md Kamruzzaman Sarker
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 12, No 3: September 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v12.i3.pp1448-1458

Abstract

Although numerous studies have been conducted on handwritten recognition, there is little and non-optimal research on Javanese script recognition due to its limitation to basic characters. Therefore, this research proposes the design of a handwritten Javanese Script recognition method based on twelve layers deep convolutional neural network (DCNN), consisting of four convolutions, two pooling, and five fully connected (FC) layers, with SoftMax classifiers. Five FC layers were proposed in this research to conduct the learning process in stages to achieve better learning outcomes. Due to the limited number of images in the Javanese script dataset, an augmentation process is needed to improve recognition performance. This method obtained 99.65% accuracy using seven types of geometric augmentation and the proposed DCNN model for 120 Javanese script character classes. It consists of 20 basic characters plus 100 others from the compound of basic and vowels characters.