A review of artificial intelligence and remote sensing for archaeological research

A Argyrou, A Agapiou - Remote Sensing, 2022 - mdpi.com
The documentation and protection of archaeological and cultural heritage (ACH) using
remote sensing, a non-destructive tool, is increasingly popular for experts around the world …

Archaeophenomics of ancient domestic plants and animals using geometric morphometrics: a review

A Evin, L Bouby, V Bonhomme… - Peer Community …, 2022 - peercommunityjournal.org
Geometric morphometrics revolutionized domestication studies through the precise quanti
cation of the phenotype of ancient plant and animal remains. Geometric morphometrics …

A human–AI collaboration workflow for archaeological sites detection

L Casini, N Marchetti, A Montanucci, V Orrù… - Scientific Reports, 2023 - nature.com
This paper illustrates the results obtained by using pre-trained semantic segmentation deep
learning models for the detection of archaeological sites within the Mesopotamian …

Large Language Models and Generative AI, Oh My!: Archaeology in the Time of ChatGPT, Midjourney, and Beyond

PJ Cobb - Advances in Archaeological Practice, 2023 - cambridge.org
We have all read the headlines heralding, often hyperbolically, the latest advances in text-
and image-based Artificial Intelligence (AI). What is perhaps most unique about these …

Comparison of Machine Learning Pixel-Based Classifiers for Detecting Archaeological Ceramics

A Argyrou, A Agapiou, A Papakonstantinou… - Drones, 2023 - mdpi.com
Recent improvements in low-altitude remote sensors and image processing analysis can be
utilised to support archaeological research. Over the last decade, the increased use of …

Deep learning for archaeological object detection on LiDAR: New evaluation measures and insights

M Fiorucci, WB Verschoof-Van Der Vaart, P Soleni… - Remote Sensing, 2022 - mdpi.com
Machine Learning-based workflows are being progressively used for the automatic
detection of archaeological objects (intended as below-surface sites) in remote sensing …

Scientific inference with interpretable machine learning: Analyzing models to learn about real-world phenomena

T Freiesleben, G König, C Molnar… - arxiv preprint arxiv …, 2022 - arxiv.org
Interpretable machine learning (IML) is concerned with the behavior and the properties of
machine learning models. Scientists, however, are only interested in models as a gateway to …

Egyptian hieroglyphs segmentation with convolutional neural networks

T Guidi, L Python, M Forasassi, C Cucci, M Franci… - Algorithms, 2023 - mdpi.com
The objective of this work is to show the application of a Deep Learning algorithm able to
operate the segmentation of ancient Egyptian hieroglyphs present in an image, with the …

Semantic segmentation (U-Net) of archaeological features in airborne laser scanning—example of the białowieża forest

PZ Banasiak, PL Berezowski, R Zapłata, M Mielcarek… - Remote Sensing, 2022 - mdpi.com
Airborne Laser Scanning (ALS) technology can be used to identify features of terrain relief in
forested areas, possibly leading to the discovery of previously unknown archaeological …

Supervised machine learning algorithms to predict provenance of archaeological pottery fragments

A Anglisano, L Casas, I Queralt, R Di Febo - Sustainability, 2022 - mdpi.com
Code and data sharing are crucial practices to advance toward sustainable archaeology.
This article explores the performance of supervised machine learning classification methods …