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s13007-021-00746-1.pdf | 6.22 MB | Adobe PDF | 見る/開く |
タイトル: | Computer vision-based wood identification and its expansion and contribution potentials in wood science: A review |
著者: | Hwang, Sung-Wook Sugiyama, Junji https://orcid.org/0000-0002-5388-4925 (unconfirmed) |
著者名の別形: | 杉山, 淳司 |
キーワード: | Convolutional neural networks Computer vision Deep learning Image recognition Machine learning Wood identification Wood anatomy |
発行日: | 2021 |
出版者: | BMC Springer Nature |
誌名: | Plant Methods |
巻: | 17 |
論文番号: | 47 |
抄録: | 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. |
著作権等: | © The Author(s) 2021. This 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. |
URI: | http://hdl.handle.net/2433/276523 |
DOI(出版社版): | 10.1186/s13007-021-00746-1 |
PubMed ID: | 33910606 |
出現コレクション: | 学術雑誌掲載論文等 |
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