The XyloTron: Flexible, Open-Source, Image-Based Macroscopic Field Identification of Wood Products

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUSDA-
Autor(es): dc.contributorUniv Wisconsin-
Autor(es): dc.contributorPurdue Univ-
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.creatorRavindran, Prabu-
Autor(es): dc.creatorThompson, Blaise J.-
Autor(es): dc.creatorSoares, Richard K.-
Autor(es): dc.creatorWiedenhoeft, Alex C.-
Data de aceite: dc.date.accessioned2022-02-22T00:06:11Z-
Data de disponibilização: dc.date.available2022-02-22T00:06:11Z-
Data de envio: dc.date.issued2020-12-09-
Data de envio: dc.date.issued2020-12-09-
Data de envio: dc.date.issued2020-07-10-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.3389/fpls.2020.01015-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/195564-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/195564-
Descrição: dc.descriptionForests, estimated to contain two thirds of the world's biodiversity, face existential threats due to illegal logging and land conversion. Efforts to combat illegal logging and to support sustainable value chains are hampered by a critical lack of affordable and scalable technologies for field-level inspection of wood and wood products. To meet this need we present the XyloTron, a complete, self-contained, multi-illumination, field-deployable, open-source platform for field imaging and identification of forest products at the macroscopic scale. The XyloTron platform integrates an imaging system built with off-the-shelf components, flexible illumination options with visible and UV light sources, software for camera control, and deep learning models for identification. We demonstrate the capabilities of the XyloTron platform with example applications for automatic wood and charcoal identification using visible light and human-mediated wood identification based on ultra-violet illumination and discuss applications in field imaging, metrology, and material characterization of other substrates.-
Descrição: dc.descriptionUS Department of State-
Descrição: dc.descriptionForest Stewardship Council-
Descrição: dc.descriptionWisconsin Idea Baldwin Grant-
Descrição: dc.descriptionUSDA, Ctr Wood Anat Res, Forest Prod Lab, Madison, WI 53726 USA-
Descrição: dc.descriptionUniv Wisconsin, Dept Bot, Madison, WI 53705 USA-
Descrição: dc.descriptionUniv Wisconsin, Dept Chem, 1101 Univ Ave, Madison, WI 53706 USA-
Descrição: dc.descriptionPurdue Univ, Dept Forestry & Nat Resources, W Lafayette, IN 47907 USA-
Descrição: dc.descriptionUniv Estadual Paulista, Dept Ciencias Biol Bot, Botucatu, SP, Brazil-
Descrição: dc.descriptionUniv Estadual Paulista, Dept Ciencias Biol Bot, Botucatu, SP, Brazil-
Descrição: dc.descriptionUS Department of State: 19318814Y0010-
Formato: dc.format8-
Idioma: dc.languageen-
Publicador: dc.publisherFrontiers Media Sa-
Relação: dc.relationFrontiers In Plant Science-
???dc.source???: dc.sourceWeb of Science-
Palavras-chave: dc.subjectwood identification-
Palavras-chave: dc.subjectcharcoal identification-
Palavras-chave: dc.subjectconvolutional neural networks-
Palavras-chave: dc.subjectdeep learning-
Palavras-chave: dc.subjectsustainability-
Palavras-chave: dc.subjectforest products-
Palavras-chave: dc.subjectcomputer vision-
Título: dc.titleThe XyloTron: Flexible, Open-Source, Image-Based Macroscopic Field Identification of Wood Products-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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