Innovative multidisciplinary method using Machine Learning to define human behaviors and environments during the Caune de l’Arago (Tautavel, France) Middle Pleistocene occupations

Autor: Sophie Grégoire, Nicolas Boulbes, Bernard Quinio, Matthieu Boussard, Caroline Chopinaud, Anne-Marie Moigne, Agnès Testu, Vincenzo Celiberti, Cédric Fontaneil, Christian Perrenoud, Anne-Sophie Lartigot Campin, Thibaud Saos, Tony Chevalier, Véronique Pois, Henry de Lumley, Marie-Antoinette de Lumley, Antoine Harfouche, Rolande Marciniack, Philippe Carrez, Thierry Hervé

Publikováno v: HAL
Big Data and Archaeology Proceedings of the XVIII UISPP World Congress (4-9 June 2018, Paris, France)
XVIII UISPP World Congress Big Data and Archaeology
XVIII UISPP World Congress Big Data and Archaeology, Jun 2018, Paris, France. pp.28-47
Big Data and Archaeology : Proceedings of the XVIII UISPP World Congress (4-9 June 2018, Paris, France), Sessions III-1 François Djindjian, (éd.) ; Paola Moscati, (éd.)
Archaeopress. Big Data and Archaeology : Proceedings of the XVIII UISPP World Congress (4-9 June 2018, Paris, France), Sessions III-1 François Djindjian, (éd.) ; Paola Moscati, (éd.), pp.28-47, 2021, Proceedings of the XVIII UISPP World Congress (4-9 June 2018, Paris, France)

International audience; SCHOPPER ANR project aim to develop a method to test research hypotheses using Machine Learning and immersives virtual environments. After 54 years of excavations, the Caune de l'Arago cave delivers a large amount of raw data

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::18ccc23ad903ae5f8529668d9b12bb0f
https://hal.science/hal-03381489