ACADSTAFF UGM

CREATION
Title : Hybrid convolutional neural networks-support vector machine classifier with dropout for Javanese character recognition
Author :

Diyah Utami Kusumaning Putri, S.Kom., M.Sc., M.Cs. (1) Dinar Nugroho Pratomo, S.Kom., M.IM., M.Cs. (2) Prof. Dr. Drs. Azhari, MT. (3)
Date : 0 2023
Keyword : Convolutional neural networks,Dropout,Javanese character recognition,Multilayer perceptron,Support vector machine Convolutional neural networks,Dropout,Javanese character recognition,Multilayer perceptron,Support vector machine
Abstract : This research paper explores the hybrid models for Javanese character recognition using 15600 characters gathered from digital and handwritten sources. The hybrid model combines the merit of deep learning using convolutional neural networks (CNN) to involve feature extraction and a machine learning classifier using support vector machine (SVM). The dropout layer also manages overfitting problems and enhances training accuracy. For evaluation purposes, we also compared CNN models with three different architectures with multilayer perceptron (MLP) models with one and two hidden layer(s). In this research, we evaluated three variants of CNN architectures and the hybrid CNN-SVM models on both the accuracy of classification and training time. The experimental outcomes showed that the classification performances of all CNN models outperform the classification performances of both MLP models. The highest testing accuracy for basic CNN is 94.2% when using model 3 CNN. The increment of hidden layers to the MLP model just slightly enhances the accuracy. Furthermore, the hybrid model gained the highest accuracy result of 98.35% for classifying the testing data when combining model 3 CNN with the SVM classifier. We get that the hybrid CNN-SVM model can enhance the accuracy results in the Javanese characters recognition.
Group of Knowledge : Ilmu Komputer
Original Language : English
Level : Internasional
Status :
Published
Document
No Title Document Type Action
1 Full Dokumen Jurnal.pdf
Document Type : [PAK] Full Dokumen
[PAK] Full Dokumen View
2 Bukti Korespondensi Telkomnika_compressed.pdf
Document Type : [PAK] Bukti Korespondensi Penulis
[PAK] Bukti Korespondensi Penulis View
3 Certificate Author for Diyah Utami Kusumaning Putri, Dinar Nugroho Pratomo, Azhari Azhari .pdf
Document Type : Dokumen Pendukung Karya Ilmiah (Hibah, Publikasi, Penelitian, Pengabdian)
Dokumen Pendukung Karya Ilmiah (Hibah, Publikasi, Penelitian, Pengabdian) View