@inproceedings{3e9cea19534e4f87be4a0df364b3f87b,
title = "Transfer Learning on Balinese Character Recognition of Lontar Manuscript Using MobileNet",
abstract = "The Balinese lontar manuscripts are cultural heritage written using Balinese characters on dried palm leaves. The conservation of the lontar manuscript is carried out by understanding the meaning contained in it. This research is the first step in the conservation of the lontar manuscript by recognizing Balinese characters. In this study, we recognized Balinese characters on lontar using a transfer learning approach. Transfer learning is done by fine-tuning the number of parameters of the pre-trained model to speed up the model convergence by modifying the number of trainable parameters on the pre-trained model. We modified the number of MobileNet architecture parameters with varying the number of trainable parameters and three optimizers to produce the best performance model. Based on the experimental result, the best recognition model yields 86.23% accuracy with a combination of SGD optimizer and 60% trainable parameters.",
keywords = "Balinese Character, Lontar Manuscript, MobileNet, Optimizers, Transfer Learning",
author = "Sutramiani, {Ni Putu} and Nanik Suciati and Daniel Siahaan",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 4th International Conference on Informatics and Computational Sciences, ICICoS 2020 ; Conference date: 10-11-2020 Through 11-11-2020",
year = "2020",
month = nov,
day = "10",
doi = "10.1109/ICICoS51170.2020.9299030",
language = "English",
series = "ICICoS 2020 - Proceeding: 4th International Conference on Informatics and Computational Sciences",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "ICICoS 2020 - Proceeding",
address = "United States",
}