Published June 30, 2023
| Version v1
Conference paper
Open
Supervised vs. unsupervised deep learning for medieval Hebrew manuscripts
- 1. The Open University of Israel
- 2. Shamoon College of Engineering, Beer-Sheva, Israel
- 3. Ben-Gurion University of the Negev, Israel
Contributors
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Hosting institution:
- 1. University of Graz
- 2. Belgrade Center for Digital Humanities
- 3. Le Mans Université
- 4. Digital Humanities im deutschsprachigen Raum
Description
Paleographical features can be extracted from digitized images by applying deep machine learning. This paper presents an unsupervised deep-learning method for determining script types and modes for medieval Hebrew manuscripts. The results would be presented vs. the previously published results of supervised deep learning for the same datasets.
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VASYUTINSKY_SHAPIRA_Daria_Supervised_vs__unsupervised_deep_l.pdf
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Additional details
Related works
- Is part of
- Book: 10.5281/zenodo.7961822 (DOI)