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Identificación de maderas colombianas utilizando el Xylotron: Prueba de concepto de una colaboración internacional
dc.contributor.author | Arévalo B., Rafael E. | spa |
dc.contributor.author | Pulido R., Esperanza N. | spa |
dc.contributor.author | Solórzano G., Juan F. | spa |
dc.contributor.author | Soares, Richard | spa |
dc.contributor.author | Ruffinatto, Flavio | spa |
dc.contributor.author | Ravindran, Prabu | spa |
dc.contributor.author | Wiedenhoeft, Alex C. | spa |
dc.date.accessioned | 2021-01-01 00:00:00 | |
dc.date.accessioned | 2023-09-19T21:10:31Z | |
dc.date.available | 2021-01-01 00:00:00 | |
dc.date.available | 2023-09-19T21:10:31Z | |
dc.date.issued | 2020-01-01 | |
dc.identifier.issn | 0120-0739 | |
dc.identifier.uri | http://test.repositoriodigital.com:8080/handle/123456789/44492 | |
dc.description.abstract | Sistemas de identificación automatizada de maderas pueden fortalecer la lucha contra el tráfico ilegal de maderas. Este trabajo utilizó 764 especímenes de xilotecas, correspondientes a 84 taxones, para desarrollar un modelo de identificación para 14 especies comerciales de Colombia. Se comenzó colectando imágenes de especímenes provenientes de xilotecas fuera de Colombia, que se utilizaron para entrenar y evaluar un modelo inicial. Se colectaron imágenes adicionales provenientes de una xiloteca Colombiana (BOFw), que se utilizaron para refinar y producir el modelo final. La capacidad de reconocimiento de este modelo fue del ~97%, demostrando que incluir muestras locales aumenta la precisión y confiabilidad del sistema [XyloTron]. Este estudio presenta el primer modelo de vision computarizada para identificación de maderas en Colombia, desarrollado en una escala de tiempo corta y bajo cooperación internacional. Concluimos que pruebas en campo y capacitación forense y en aprendizaje automatizado, son los siguientes pasos lógicos a seguir. | spa |
dc.description.abstract | Field deployable computer vision wood identification systems can play a key role in combating illegal logging in the real world. This work used 764 xylarium specimens from 84 taxa to develop an image data set to train a classifier to identify 14 commercial Colombian timbers. We imaged specimens from various xylaria outside Colombia, trained and evaluated an initial identification model, then collected additional images from a Colombian xylarium (BOFw), and incorporated those images to refine and produce a final model. The specimen classification accuracy of this final model was ~ 97%, demonstrating that including local specimens can augment the accuracy and reliability of the XyloTron system. Our study demonstrates the first deployable computer vision model for wood identification in Colombia, developed on a timescale of months rather than years by leveraging international cooperation. We conclude that field testing and advanced forensic and machine learning training are the next logical steps. | eng |
dc.format.mimetype | text/xml | eng |
dc.format.mimetype | application/pdf | eng |
dc.language.iso | eng | eng |
dc.publisher | Universidad Distrital Francisco José de Caldas | spa |
dc.rights | Colombia forestal - 2021 | eng |
dc.rights.uri | https://creativecommons.org/licenses/by-sa/4.0/ | eng |
dc.source | https://revistas.udistrital.edu.co/index.php/colfor/article/view/16700 | eng |
dc.subject | Wood identification | eng |
dc.subject | Forensic wood anatomy | eng |
dc.subject | Deep learning | eng |
dc.subject | Transfer learning | eng |
dc.subject | Machine Learning | eng |
dc.subject | Identificación de madera | spa |
dc.subject | Aprendizaje profundo | spa |
dc.subject | Anatomía forense de madera | spa |
dc.subject | Transferencia de aprendizaje | spa |
dc.title | Identificación de maderas colombianas utilizando el Xylotron: Prueba de concepto de una colaboración internacional | spa |
dc.type | Artículo de revista | spa |
dc.identifier.doi | 10.14483/2256201X.16700 | |
dc.rights.accessrights | info:eu-repo/semantics/openAccess | eng |
dc.type.coar | http://purl.org/coar/resource_type/c_6501 | eng |
dc.type.coar | http://purl.org/coar/resource_type/c_2df8fbb1 | eng |
dc.type.local | Journal article | eng |
dc.title.translated | Imaged based identification of colombian timbers using the xylotron: a proof of concept international partnership | eng |
dc.rights.coar | http://purl.org/coar/access_right/c_abf2 | eng |
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dc.rights.creativecommons | Esta obra está bajo una licencia internacional Creative Commons Atribución-CompartirIgual 4.0. | eng |
dc.type.coarversion | http://purl.org/coar/version/c_970fb48d4fbd8a85 | eng |
dc.type.driver | info:eu-repo/semantics/article | eng |
dc.type.redcol | http://purl.org/redcol/resource_type/ART | eng |
dc.type.version | info:eu-repo/semantics/publishedVersion | eng |
dc.relation.citationvolume | 24 | spa |
dc.relation.citationissue | 1 | spa |
dc.relation.citationedition | Núm. 1 , Año 2021 : Enero-Junio | spa |
dc.relation.ispartofjournal | Colombia forestal | spa |
dc.identifier.eissn | 2256-201X | |
dc.identifier.url | https://doi.org/10.14483/2256201X.16700 | |
dc.relation.citationstartpage | 5 | |
dc.relation.citationendpage | 16 | |
dc.relation.bitstream | https://revistas.udistrital.edu.co/index.php/colfor/article/download/16700/16789 | |
dc.relation.bitstream | https://revistas.udistrital.edu.co/index.php/colfor/article/download/16700/16324 | |
dc.type.content | Text | eng |
dspace.entity.type | Publication | eng |
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