論文

査読有り 最終著者 責任著者 本文へのリンクあり 国際誌
2021年4月

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

Plant Methods
  • Sung-Wook Hwang
  • ,
  • Junji Sugiyama

17
47
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1186/s13007-021-00746-1
出版者・発行元
Springer Science and Business Media LLC

<title>Abstract</title>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.

リンク情報
DOI
https://doi.org/10.1186/s13007-021-00746-1
共同研究・競争的資金等の研究課題
木質材料の構造力学的最適化による環境応答戦略の理解
共同研究・競争的資金等の研究課題
木材多様性データベースの構築
URL
https://link.springer.com/content/pdf/10.1186/s13007-021-00746-1.pdf 本文へのリンクあり
URL
https://link.springer.com/article/10.1186/s13007-021-00746-1/fulltext.html 本文へのリンクあり
ID情報
  • DOI : 10.1186/s13007-021-00746-1
  • eISSN : 1746-4811

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