AIMC Topic: Archaeology
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Finding the original mass: A machine learning model and its deployment for lithic scrapers.
PloS one
Jul 28, 2025
Predicting the original mass of a retouched scraper has long been a major goal in lithic analysis. It is commonly linked to lithic technological organization of past societies along with notions of stone tool general morphology, standardization throu...
Dating ancient manuscripts using radiocarbon and AI-based writing style analysis.
PloS one
Jun 4, 2025
Determining by means of palaeography the chronology of ancient handwritten manuscripts such as the Dead Sea Scrolls is essential for reconstructing the evolution of ideas, but there is an almost complete lack of date-bearing manuscripts. To overcome ...
Beyond the Greater Angkor Region: Automatic large-scale mapping of Angkorian-period reservoirs in satellite imagery using deep learning.
PloS one
Mar 26, 2025
Archaeologists often use high-resolution satellite imagery to identify potential archaeological sites or features, including ancient settlements, burial mounds, roads, and even subtle differences in vegetation or topography. Over the last several dec...
Capillariid diversity in archaeological material from the New and the Old World: clustering and artificial intelligence approaches.
Parasites & vectors
Mar 12, 2025
BACKGROUND: Capillariid nematode eggs have been reported in archaeological material in both the New and the Old World, mainly in Europe and South America. They have been found in various types of samples, as coprolites, sediments from latrines, pits,...
Making sense of fossils and artefacts: a review of best practices for the design of a successful workflow for machine learning-assisted citizen science projects.
PeerJ
Feb 13, 2025
Historically, the extensive involvement of citizen scientists in palaeontology and archaeology has resulted in many discoveries and insights. More recently, machine learning has emerged as a broadly applicable tool for analysing large datasets of fos...
Understanding the spread of agriculture in the Western Mediterranean (6th-3rd millennia BC) with Machine Learning tools.
Nature communications
Jan 15, 2025
The first Neolithic farmers arrived in the Western Mediterranean area from the East. They established settlements in coastal areas and over time migrated to new environments, adapting to changing ecological and climatic conditions. While farming prac...
A framework of evolutionary optimized convolutional neural network for classification of shang and chow dynasties bronze decorative patterns.
PloS one
May 14, 2024
As a UNESCO World Cultural Heritage, the aesthetic value of bronze artifacts from the Shang and Chow Dynasties has had a profound influence on Chinese traditional culture and art. To facilitate the digital preservation and protection of these Shang a...
Unstructured satellite survey detects up to 20% of archaeological sites in coastal valleys of southern Peru.
PloS one
Feb 6, 2024
Satellite survey is widely used for archaeological site discovery, but the efficacy of the method has received little systematic investigation. In this analysis, twelve study participants of different experience levels performed an unstructured remot...
Machine learning for stone artifact identification: Distinguishing worked stone artifacts from natural clasts using deep neural networks.
PloS one
Aug 10, 2022
Stone artifacts are often the most abundant class of objects found in archaeological sites but their consistent identification is limited by the number of experienced analysts available. We report a machine learning based technology for stone artifac...
Molecular archaeology and machine learning: Deep learning algorithms help to uncover ancient genes in our genomes and their evolutionary role: Deep learning algorithms help to uncover ancient genes in our genomes and their evolutionary role.
EMBO reports
May 10, 2022
The study of ancient genes in contemporary species is providing new insights about how organisms adapted to new environments during evolution.
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