# Corazza 2022: Unsupervised deep learning supports reclassification of Bronze age cypriot writing system

> Michele Corazza, Fabio Tamburini, Miguel Valério et al., 2022. 2 records on Mysteries Department cite it. The inductive-methods survey cites its…

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[Sources](https://mysteriesdept.com/sources)[Voynich Manuscript](https://mysteriesdept.com/mysteries/voynich-manuscript)Corazza 2022

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# Unsupervised deep learning supports reclassification of Bronze age cypriot writing system

Michele Corazza, Fabio Tamburini, Miguel Valério et al., 2022. _PLOS ONE_.

Uses deep learning on sign shapes, together with paleographic and epigraphic evidence, to test the usual division of the undeciphered Cypro-Minoan script into three subgroups, and finds support for reclassifying it.

**Voynich Manuscript** Articledoi: **[10.1371/journal.pone.0269544](https://doi.org/10.1371/journal.pone.0269544)** Checked against the original0

## What it's used for here

The inductive-methods survey cites its unsupervised grouping of signs as a model for clustering Voynich glyph images.

## Cited by on this site 2 records

[2 methods surveys]

Mathematics, inductive methods

SRC

## Cite it

```
Corazza, M., Tamburini, F., Valério, M., & Ferrara, S. (2022). Unsupervised deep learning supports reclassification of Bronze age cypriot writing system. PLOS ONE. https://doi.org/10.1371/journal.pone.0269544
```

[Read it free at doi.org](https://doi.org/10.1371/journal.pone.0269544)[PDF stored here · 22 pages](https://mysteriesdept.com/sources/SRC0D8MQJ6R4GRV/unsupervised-deep-learning-supports-reclassification-of/pdf)

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**SRC** 0D8MQJ6R4GRV

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