Restoring and attributing ancient texts using deep neural networks.

Assael, Yannis; Sommerschield, Thea; Shillingford, Brendan; Bordbar, Mahyar; Pavlopoulos, John; Chatzipanagiotou, Marita; Androutsopoulos, Ion; Prag, Jonathan; de Freitas, Nando

Assael, Yannis; Sommerschield, Thea; Shillingford, Brendan; Bordbar, Mahyar; Pavlopoulos, John; Chatzipanagiotou, Marita; Androutsopoulos, Ion; Prag, Jonathan; de Freitas, Nando.

Afiliación

Assael Y; DeepMind, London, UK. yannisassael@google.com.
Sommerschield T; Department of Humanities, Ca' Foscari University of Venice, Venice, Italy. thea.sommerschield@unive.it.
Shillingford B; Center for Hellenic Studies, Harvard University, Washington, DC, USA. thea.sommerschield@unive.it.
Bordbar M; DeepMind, London, UK.
Pavlopoulos J; DeepMind, London, UK.
Chatzipanagiotou M; Department of Informatics, Athens University of Economics and Business, Athens, Greece.
Androutsopoulos I; Department of Informatics, Athens University of Economics and Business, Athens, Greece.
Prag J; Department of Informatics, Athens University of Economics and Business, Athens, Greece.
de Freitas N; Faculty of Classics, University of Oxford, Oxford, UK.

Nature ; 603(7900): 280-283, 2022 03.

Article en En | MEDLINE | ID: mdl-35264762

Asunto(s)

Arqueología/métodos; Aprendizaje Profundo; Escritura/historia; Antigua Grecia/etnología; Escritura Manual; Historia Antigua; Humanos; Programas Informáticos

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Arqueología / Escritura / Aprendizaje Profundo Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Nature Año: 2022 Tipo del documento: Article País de afiliación: Reino Unido

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