Automated detection and classification of multi-cell Phytoliths using Deep Learning-Based Algorithms

This paper presents an algorithm for automated detection and classification of multi-cell phytoliths, one of the major components of many archaeological and paleoenvironmental deposits. This identification, based on phytolith wave pattern, is made using a pretrained VGG19 deep learning model. This a...

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Bibliographic Details
Published in:	Journal of archaeological science Vol. 148; p. 105654
Main Authors:	Berganzo-Besga, Iban, Orengo, Hector A., Lumbreras, Felipe, Aliende, Paloma, Ramsey, Monica N.
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.12.2022
Subjects:	algorithms archaeology automation color Computational archaeology Deep learning Google colaboratory Hordeum Machine learning Middle East paleoecology Phytoliths species Triticum monococcum subsp. aegilopoides Middle East Deep learning Phytoliths Google colaboratory Computational archaeology Machine learning
ISSN:	0305-4403
Online Access:	Get full text
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