2016
DOI: 10.1016/j.jas.2015.09.003
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A conceptual framework for a computer-assisted, morphometric-based phytolith analysis and classification system

Abstract: Although automated approaches to shape analysis and object classification have been widely applied in the biological sciences, technical and time considerations have limited their use in phytolith research. As advanced microscopy systems become more affordable and accessible and digital imaging software provides a wider range of sophisticated analytical tools, there is increased potential for effective use of machinevision and automation in phytolith research. In this paper, we describe technical limitations o… Show more

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Cited by 22 publications
(18 citation statements)
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“…These advances include the development of computer‐assisted phytolith identification systems as well as a better integration of phytolith analysis with micromorphology and morphometric approaches to soil analysis (Ball et al. ; Evett and Cuthrell ).…”
Section: Collaborations In Archaeological Practicementioning
confidence: 99%
“…These advances include the development of computer‐assisted phytolith identification systems as well as a better integration of phytolith analysis with micromorphology and morphometric approaches to soil analysis (Ball et al. ; Evett and Cuthrell ).…”
Section: Collaborations In Archaeological Practicementioning
confidence: 99%
“…Os estudos fitolíticos, principalmente quando associados a outros indicadores (análise multiproxy), são úteis para a interpretação de condições paleobiogeoclimáticas (Yost et al, 2018;Neumann et al, 2017;Ball et al, 2016;Evett et al, 2016;Field et al, 2016;Hart, 2016;Hodson, 2016;Pearsall, 2016;Zurro et al, 2016;Albert et al, 2015;Vrydaghs et al, 2015;McCune et al, 2015;Power et al, 2014;Hyland et al, 2013;Watling et al 2013). No Brasil, estudos recentes foram realizados por Coe et al (2018), Babot et al (2017), Calegari et al (2017aCalegari et al ( , 2017b, , Parolin et al (2017), Santos (2017), Chueng (2016), Paisani et al (2016), Silva et al (2016), Santos et al (2015), Luz et al (2015), Calegari et al (2015) Coe et al (2015), Coe et al (2014), Calegari et al (2013), Coe et al (2013).…”
Section: Introductionunclassified
“…In our previous study, we built a quantitative and easily operated model (the municipal administrative area spatial zoning model, M-MSZ model) for MAA spatial zoning, based on the existing spatial equilibrium model for regional development [65]. The obtained model was optimized with combination of the neural network and expert public decision analysis methods [66][67][68], and it is compared with the existing spatial zoning models (including the urban structure zoning model, UGB model and major function-oriented zoning model) using the same factors. Moreover, three representative cities in China were modeled empirically using this model, and the results were compared with those obtained using the existing models.…”
Section: Introductionmentioning
confidence: 99%