Interpretation of geophysical surveys of archaeological sites using artificial neural networks

DJ Bescoby; GC Cawley; PN Chroston

doi:10.1109/IJCNN.2003.1223850

Interpretation of geophysical surveys of archaeological sites using artificial neural networks

DJ Bescoby, GC Cawley, PN Chroston

Research output: Contribution to conference › Paper › peer-review

2 Citations (Scopus)

Abstract

Geophysical surveys form a vital component of modern archaeological studies, providing data on the location of surviving sub-surface remains. Unfortunately interpretation of the raw output from geophysical surveys requires considerable expertise and current methods for machine interpretation are computationally expensive. In this paper, we describe the use of multi-layer perceptron neural networks from automated interpretation of geophysical survey data and present promising initial results for a survey taken of the Roman suburb of Butrint, a classical city situated in what is now Albania. Clearly a computationally efficient and straightforward means of inverting geophysical survey data is potentially an extremely useful tool in encouraging public awareness of cultural heritage.

Original language	English
Pages	1132-1137
Number of pages	6
DOIs	https://doi.org/10.1109/IJCNN.2003.1223850
Publication status	Published - Jul 2003
Event	IEEE/INNS International Joint Conference on Artificial Neural Networks - Portland, United States Duration: 20 Jul 2003 → 24 Jul 2003

Conference

Conference	IEEE/INNS International Joint Conference on Artificial Neural Networks
Abbreviated title	IJCNN-2003
Country/Territory	United States
City	Portland
Period	20/07/03 → 24/07/03

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/IJCNN.2003.1223850

Cite this

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title = "Interpretation of geophysical surveys of archaeological sites using artificial neural networks",

abstract = "Geophysical surveys form a vital component of modern archaeological studies, providing data on the location of surviving sub-surface remains. Unfortunately interpretation of the raw output from geophysical surveys requires considerable expertise and current methods for machine interpretation are computationally expensive. In this paper, we describe the use of multi-layer perceptron neural networks from automated interpretation of geophysical survey data and present promising initial results for a survey taken of the Roman suburb of Butrint, a classical city situated in what is now Albania. Clearly a computationally efficient and straightforward means of inverting geophysical survey data is potentially an extremely useful tool in encouraging public awareness of cultural heritage.",

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AB - Geophysical surveys form a vital component of modern archaeological studies, providing data on the location of surviving sub-surface remains. Unfortunately interpretation of the raw output from geophysical surveys requires considerable expertise and current methods for machine interpretation are computationally expensive. In this paper, we describe the use of multi-layer perceptron neural networks from automated interpretation of geophysical survey data and present promising initial results for a survey taken of the Roman suburb of Butrint, a classical city situated in what is now Albania. Clearly a computationally efficient and straightforward means of inverting geophysical survey data is potentially an extremely useful tool in encouraging public awareness of cultural heritage.

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