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Computer vision-based wood identification and its expansion and contribution potentials in wood science: A review

The remarkable developments in computer vision and machine learning have changed the methodologies of many scientific disciplines. They have also created a new research field in wood science called computer vision-based wood identification, which is making steady progress towards the goal of buildin...

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Detalles Bibliográficos
Autores principales: Hwang, Sung-Wook, Sugiyama, Junji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8082842/
https://www.ncbi.nlm.nih.gov/pubmed/33910606
http://dx.doi.org/10.1186/s13007-021-00746-1
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author Hwang, Sung-Wook
Sugiyama, Junji
author_facet Hwang, Sung-Wook
Sugiyama, Junji
author_sort Hwang, Sung-Wook
collection PubMed
description The remarkable developments in computer vision and machine learning have changed the methodologies of many scientific disciplines. They have also created a new research field in wood science called computer vision-based wood identification, which is making steady progress towards the goal of building automated wood identification systems to meet the needs of the wood industry and market. Nevertheless, computer vision-based wood identification is still only a small area in wood science and is still unfamiliar to many wood anatomists. To familiarize wood scientists with the artificial intelligence-assisted wood anatomy and engineering methods, we have reviewed the published mainstream studies that used or developed machine learning procedures. This review could help researchers understand computer vision and machine learning techniques for wood identification and choose appropriate techniques or strategies for their study objectives in wood science.
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spelling pubmed-80828422021-04-29 Computer vision-based wood identification and its expansion and contribution potentials in wood science: A review Hwang, Sung-Wook Sugiyama, Junji Plant Methods Review The remarkable developments in computer vision and machine learning have changed the methodologies of many scientific disciplines. They have also created a new research field in wood science called computer vision-based wood identification, which is making steady progress towards the goal of building automated wood identification systems to meet the needs of the wood industry and market. Nevertheless, computer vision-based wood identification is still only a small area in wood science and is still unfamiliar to many wood anatomists. To familiarize wood scientists with the artificial intelligence-assisted wood anatomy and engineering methods, we have reviewed the published mainstream studies that used or developed machine learning procedures. This review could help researchers understand computer vision and machine learning techniques for wood identification and choose appropriate techniques or strategies for their study objectives in wood science. BioMed Central 2021-04-28 /pmc/articles/PMC8082842/ /pubmed/33910606 http://dx.doi.org/10.1186/s13007-021-00746-1 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Review
Hwang, Sung-Wook
Sugiyama, Junji
Computer vision-based wood identification and its expansion and contribution potentials in wood science: A review
title Computer vision-based wood identification and its expansion and contribution potentials in wood science: A review
title_full Computer vision-based wood identification and its expansion and contribution potentials in wood science: A review
title_fullStr Computer vision-based wood identification and its expansion and contribution potentials in wood science: A review
title_full_unstemmed Computer vision-based wood identification and its expansion and contribution potentials in wood science: A review
title_short Computer vision-based wood identification and its expansion and contribution potentials in wood science: A review
title_sort computer vision-based wood identification and its expansion and contribution potentials in wood science: a review
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8082842/
https://www.ncbi.nlm.nih.gov/pubmed/33910606
http://dx.doi.org/10.1186/s13007-021-00746-1
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