Classification of Batik Motifs Using Convolutional Neural Networks
5 Pages Posted: 2 Oct 2018
Date Written: August 1, 2018
Abstract
Batik is Indonesia’s traditional cultural heritage which is a cloth-making technique using canting and malam. Each region of Indonesia usually produces their own batik motifs. This paper proposes the convolutional neural networks to recognize the batik motifs from images. The dataset consists of batik motifs from Lasem, Solo, and Yogyakarta region. In total, there are 13 classes of batik motif in the dataset. Experimental results show that the model performance is not sufficient enough to accurately detect most of the batik motifs.
Suggested Citation: Suggested Citation
Tristanto, Jonathan and Hendryli, Janson and Erny Herwindiati, Dyah, Classification of Batik Motifs Using Convolutional Neural Networks (August 1, 2018). International Conference on Information Technology, Engineering, Science & its Applications, Available at SSRN: https://ssrn.com/abstract=3258935 or http://dx.doi.org/10.2139/ssrn.3258935
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