A Recursive Encoding for Cuneiform Signs
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Abstract (arXiv)
One of the most significant problems in cuneiform pedagogy is the process of looking up unknown signs, which often involves a tedious page-by-page search through a sign list. This paper proposes a new "recursive encoding" for signs, which represents the arrangement of strokes in a way a computer can process. A series of new algorithms then offers students a new way to look up signs by any distinctive component, as well as providing new ways to render signs and tablets electronically.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 4 of its 48 references that are in the map. First posted on arXiv 25 Jun 2024.
Builds on
4 of 48 references.
References · 4
- 2017SplineCNN: Fast Geometric Deep Learning with Continuous B-Spline Kernelscited by 161
- 2018Recognizing Cuneiform Signs Using Graph Based Methodscited by 14
- 2016Stroke Sequence-Dependent Deep Convolutional Neural Network for Online Handwritten Chinese Character Recognitioncited by 6
- 2020Investigating Machine Learning Methods for Language and Dialect Identification of Cuneiform Textscited by 2
Built on by
Citing papers per year: 2026: 1.
1 paper.