<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-05-12T08:09:05Z</responseDate><request verb="GetRecord" identifier="oai:riubu.ubu.es:10259/7378" metadataPrefix="oai_dc">https://riubu.ubu.es/oai/request</request><GetRecord><record><header><identifier>oai:riubu.ubu.es:10259/7378</identifier><datestamp>2023-03-22T12:05:54Z</datestamp><setSpec>com_10259_4219</setSpec><setSpec>com_10259_5086</setSpec><setSpec>com_10259_2604</setSpec><setSpec>col_10259_4220</setSpec></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:doc="http://www.lyncode.com/xoai" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
<dc:title>“You Are Not My Type”: An Evaluation of Classification Methods for Automatic Phytolith Identification</dc:title>
<dc:creator>Diez Pastor, José Francisco</dc:creator>
<dc:creator>Latorre Carmona, Pedro</dc:creator>
<dc:creator>Arnaiz González, Álvar</dc:creator>
<dc:creator>Ruiz Pérez, Javier</dc:creator>
<dc:creator>Zurro, Débora</dc:creator>
<dc:subject>Feature extraction</dc:subject>
<dc:subject>Machine learning</dc:subject>
<dc:subject>Microfossils</dc:subject>
<dc:subject>Morphometry</dc:subject>
<dc:subject>Proxy</dc:subject>
<dc:subject>Informática</dc:subject>
<dc:subject>Computer science</dc:subject>
<dc:description>Phytoliths can be an important source of information related to environmental and climatic change, as well as to ancient plant use by&#xd;
humans, particularly within the disciplines of paleoecology and archaeology. Currently, phytolith identification and categorization is performed manually by researchers, a time-consuming task liable to misclassifications. The automated classification of phytoliths would allow&#xd;
the standardization of identification processes, avoiding possible biases related to the classification capability of researchers. This paper presents a comparative analysis of six classification methods, using digitized microscopic images to examine the efficacy of different quantitative&#xd;
approaches for characterizing phytoliths. A comprehensive experiment performed on images of 429 phytoliths demonstrated that the automatic phytolith classification is a promising area of research that will help researchers to invest time more efficiently and improve their&#xd;
recognition accuracy rate.</dc:description>
<dc:description>This work was supported by the project TIN2015- 67534-P (MINECO/FEDER, UE) of the Ministerio de Economía y Competitividad of the Spanish Government, by the project BU085P17 (JCyL/FEDER, UE) of the Junta de Castilla y León (both projects co-financed through European Union FEDER funds) and by Grups de Recerca de Qualitat CaSEs – Culture and Socio-Ecological Dynamics (2017 SGR 212), AGAUR-Generalitat de Catalunya. The authors gratefully acknowledge the support of NVIDIA Corporation and its donation of the TITAN Xp GPUs used in this research.</dc:description>
<dc:date>2023-02-06T07:40:24Z</dc:date>
<dc:date>2023-02-06T07:40:24Z</dc:date>
<dc:date>2020-11</dc:date>
<dc:type>info:eu-repo/semantics/article</dc:type>
<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
<dc:identifier>1431-9276</dc:identifier>
<dc:identifier>http://hdl.handle.net/10259/7378</dc:identifier>
<dc:identifier>10.1017/S1431927620024629</dc:identifier>
<dc:identifier>1435-8115</dc:identifier>
<dc:language>eng</dc:language>
<dc:relation>Microscopy and Microanalysis. 2020, V. 26, n. 6, p. 1158-1167</dc:relation>
<dc:relation>https://doi.org/10.1017/S1431927620024629</dc:relation>
<dc:relation>info:eu-repo/grantAgreement/MINECO//TIN2015-67534-P/ES/ALGORITMOS DE ENSEMBLES PARA PROBLEMAS DE SALIDAS MULTIPLES. NUEVOS DESARROLLOS Y APLICACIONES/</dc:relation>
<dc:relation>info:eu-repo/grantAgreement/Junta de Castilla y León//BU085P17//Minería de datos para le mejora del mantenimiento y disponibilidad de máquinas de altas presiones/</dc:relation>
<dc:relation>info:eu-repo/grantAgreement/AGAUR//2017 SGR 212/</dc:relation>
<dc:rights>Atribución 4.0 Internacional</dc:rights>
<dc:rights>http://creativecommons.org/licenses/by/4.0/</dc:rights>
<dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
<dc:format>application/pdf</dc:format>
<dc:publisher>Cambridge University Press</dc:publisher>
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