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Neural network analysis for predicting metrics of fragmented laminar artifacts: a case study from MP...

Neural network analysis for predicting metrics of fragmented laminar artifacts: a case study from MP...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_526276858dc142f1be0d66aa5af95a3c

Neural network analysis for predicting metrics of fragmented laminar artifacts: a case study from MPPNB sites in the Southern Levant

About this item

Full title

Neural network analysis for predicting metrics of fragmented laminar artifacts: a case study from MPPNB sites in the Southern Levant

Publisher

London: Nature Publishing Group UK

Journal title

Scientific reports, 2024-11, Vol.14 (1), p.29714-21, Article 29714

Language

English

Formats

Publication information

Publisher

London: Nature Publishing Group UK

More information

Scope and Contents

Contents

This study was aimed at introducing a new method for predicting the original metrics of fragmented standardized artifacts, specifically of flint blades from the Middle Pre-Pottery Neolithic B (10,200/100–9,500/400 cal B.P.) in the Southern Levant. The excessive re-use of these artifacts or poor preservation conditions often prevent a complete set o...

Alternative Titles

Full title

Neural network analysis for predicting metrics of fragmented laminar artifacts: a case study from MPPNB sites in the Southern Levant

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_526276858dc142f1be0d66aa5af95a3c

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_526276858dc142f1be0d66aa5af95a3c

Other Identifiers

ISSN

2045-2322

E-ISSN

2045-2322

DOI

10.1038/s41598-024-77184-1

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