📅 17 August 2024
DOI: 10.26877/asset.v6i4.771
A Web-Based for Demak Batik Classification Using VGG16 Convolutional Neural Network
Advance Sustainable Science, Engineering and Technology (ASSET)
Universitas Persatuan Guru Republik Indonesia Semarang
📄 Abstract
The diversity of Demak batik motifs presents challenges in classification and identification. This research aims to develop a Demak batik motif classification system using deep learning and VGG16 convolutional network. A dataset of Demak batik images is collected and processed to train the model. The VGG16 architecture is modified by fine-tuning to optimize the classification performance. Results show that the modified VGG16 model achieved a classification accuracy of 98.72% on the test dataset, demonstrating its potential application in preserving and digitizing Demak batik cultural heritage.
🔖 Keywords
#Batik Demak; Deep learning; Convolutional Network; Classification; VGG16; Cultural Preservation
ℹ️ Informasi Publikasi
Tanggal Publikasi
17 August 2024
Volume / Nomor / Tahun
Volume 6, Nomor 4, Tahun 2024
📝 HOW TO CITE
Ardyani, Salma Shafira Fatya; Sari, Christy Atika, "A Web-Based for Demak Batik Classification Using VGG16 Convolutional Neural Network," Advance Sustainable Science, Engineering and Technology (ASSET), vol. 6, no. 4, Aug. 2024.
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