Papers by Jonathan Prag

1 papers
Restoring ancient text using deep learning: a case study on Greek epigraphy (D19-1)

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Challenge: illegible parts of ancient texts must be restored by specialists, known as epigraphists, using deep neural networks to recover missing characters from text input.
Approach: They propose a model that recovers missing characters from a damaged text input using deep neural networks.
Outcome: The proposed model achieves a 30.1% character error rate, compared to the 57.3% of human epigraphists.

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