id
	11016
Url
	https://chloe.cnr.it/s/BiDiAr/item/11016
Resource template
	Academic Article
Resource class
	bibo:AcademicArticle
Title
	The contribution of artificial intelligence to aerial photointerpretation of archaeological sites: a comparison between traditional and Machine Learning methods
Creator
	Cacciari, Ilaria
	Pocobelli, Giorgio F.
Date
	2021
Language
	eng
Rights
	https://creativecommons.org/licenses/by-nc-nd/4.0/deed.en CC BY-NC-ND 4.0
Abstract
	On the basis of the research activity carried out as part of the Archeo 3.0 project ‘Integration of key enabling technologies for the efficiency of preventive archaeological excavations’, the authors explore the feasibility and limits of the automated approach for the recognition of archaeological marks. This approach is mainly motivated by the relevance that aerial photographs play in the reconstruction of ancient topography of human settlements. For this aim, a collection of historical aerial photographs of both the city and the necropolis of Vulci has been considered. These photographs, in colour and B/W, have been previously used in a PhD thesis in Ancient Topography in which the traditional methodology (photointerpretation and cartographic restitution) has been fully exploited. In this work, a systematic study is presented in order to compare the results obtained with Machine Learning techniques vs traditional ones. This comparison allows us to discuss the strengths and limits of both methodologies.
Is Part Of
	https://chloe.cnr.it/s/BiDiAr/item/2002
Cited by
	11073
Doi
	https://doi.org/10.19282/ac.32.1.2021.05
Issue
	1
Pages
	81–98
Uri
	http://www.archcalc.cnr.it/journal/id.php?id=1128
Volume
	32
Homepage
	https://www.zotero.org/groups/5293298/bidiar/items/7IUDB9QE/item-list

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