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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