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Archaeology

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Machine learning for stone artifact identification: Distinguishing worked stone artifacts from natural clasts using deep neural networks.

PloS one
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...

Restoring and attributing ancient texts using deep neural networks.

Nature
Ancient history relies on disciplines such as epigraphy-the study of inscribed texts known as inscriptions-for evidence of the thought, language, society and history of past civilizations. However, over the centuries, many inscriptions have been dama...

A framework of evolutionary optimized convolutional neural network for classification of shang and chow dynasties bronze decorative patterns.

PloS one
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
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...

Beyond the Greater Angkor Region: Automatic large-scale mapping of Angkorian-period reservoirs in satellite imagery using deep learning.

PloS one
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...

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
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
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...

Capillariid diversity in archaeological material from the New and the Old World: clustering and artificial intelligence approaches.

Parasites & vectors
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,...