Best practices for the application of computer vision-based machine learning in archaeology

Journal of Archaeological Science 2026 Open access

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Authors: Iban Berganzo‐Besga, Héctor A. Orengo, Felipe Lumbreras
DOI: 10.1016/j.jas.2026.106577
Cited by: 1
References: 28

Abstract

• Defines seven best practices for CV-based ML in archaeology. • Links sources, preprocessing, training, post-treatment and validation. • Shows how to reduce false positives in low-density survey settings. • Integrates explainability, cross-validation and ethical responsibility. • Promotes reproducible, FAIR and archaeologically informed AI workflows.

Fields of Study & Subjects

Image Processing and 3D Reconstruction Archaeological Research and Protection Archaeology and ancient environmental studies

Publication details

Journal / source
Journal of Archaeological Science
Publisher
Elsevier BV
Volume
191
Pages
106577–106577
Publication date
27 May 2026
Language
EN