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title Signal and Noise: Epigraphic Ventures in Machine Learning
author Aaron Hershkowitz
licence http://creativecommons.org/licenses/by-nc-sa/4.0
link
description This module offers an overview of ongoing epigraphic machine learning projects (NLP and Text Restoration, classification, computer vision) discussing specific issues, future developments and critical caveats.
date 2023/01/23– 2023/01/23
language en
institution University of Bologna, Italy
focus https://w3id.org/encode/competences/Greek
focus https://w3id.org/encode/competences/Latin
focus https://w3id.org/encode/competences/3dReconstruction
focus https://w3id.org/encode/competences/MachineLearning
focus https://w3id.org/encode/competences/Epigraphy
exercise
literature
qualifications
format Lecture
medium in presence
location University of Bologna
competences
partof https://w3id.org/encode/modules/ENCODE Workshop AI and Ancient Writing Cultures

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From the triple store.

Results of: DESCRIBE <https://w3id.org/encode/modules/m99>.
Results of: SELECT * WHERE{ BIND (<https://w3id.org/encode/modules/m99> as ?this) { ?this ?predicate ?object . OPTIONAL {?object ?predicateOfObject ?objectOfObject} } UNION { ?subject ?predicate ?this} }.