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Comparison of two forensic wood identification technologies for ten Meliaceae woods: computer vision versus mass spectrometry

dc.contributor.authorRavindran, Prabu
dc.contributor.authorWiedenhoeft, Alex C.
dc.contributor.institutionUniv Wisconsin
dc.contributor.institutionUS Forest Serv
dc.contributor.institutionPurdue Univ
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2020-12-10T17:36:22Z
dc.date.available2020-12-10T17:36:22Z
dc.date.issued2020-07-04
dc.description.abstractA wealth of forensic wood identification technologies has been developed or improved in recent years, with many attempts to compare results between technologies. The utility of such comparisons is greatly reduced when the species tested with each technology are different and when performance metrics are not calculated or presented in the same way. Here, a species-level XyloTron computer vision model is presented along with a side-by-side comparison for species- and genus-level identification of the 10 species of Meliaceae studied by Deklerck et al. using mass spectrometry. The species-level accuracies of the XyloTron model and the mass spectrometry models are comparable, while the genus-level accuracy of the XyloTron model is higher than that of the mass spectrometry model. The paper concludes with a call for better practices to compare disparate forensic wood identification technologies from a performance driven perspective.en
dc.description.affiliationUniv Wisconsin, Dept Bot, Madison, WI 53706 USA
dc.description.affiliationUS Forest Serv, Forest Prod Lab, Ctr Wood Anat Res, USDA, Madison, WI 53726 USA
dc.description.affiliationPurdue Univ, Dept Forestry & Nat Resources, W Lafayette, IN 47907 USA
dc.description.affiliationUniv Estadual Paulista Botucatu, Ciencias Biol Bot, Sao Paulo, Brazil
dc.description.affiliationUnespUniv Estadual Paulista Botucatu, Ciencias Biol Bot, Sao Paulo, Brazil
dc.format.extent1139-1150
dc.identifierhttp://dx.doi.org/10.1007/s00226-020-01178-1
dc.identifier.citationWood Science And Technology. New York: Springer, v. 54, n. 5, p. 1139-1150, 2020.
dc.identifier.doi10.1007/s00226-020-01178-1
dc.identifier.issn0043-7719
dc.identifier.urihttp://hdl.handle.net/11449/195489
dc.identifier.wosWOS:000545289000001
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofWood Science And Technology
dc.sourceWeb of Science
dc.titleComparison of two forensic wood identification technologies for ten Meliaceae woods: computer vision versus mass spectrometryen
dc.typeArtigo
dcterms.licensehttp://www.springer.com/open+access/authors+rights?SGWID=0-176704-12-683201-0
dcterms.rightsHolderSpringer
dspace.entity.typePublication

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