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

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Authors
Hwang, Sung-Wook; Sugiyama, Junji
Issue Date
2021-04-28
Publisher
BMC
Citation
Plant Methods. 2021 Apr 28;17(1):47
Keywords
Convolutional neural networksComputer visionDeep learningImage recognitionMachine learningWood identifcationWood anatomy
Abstract
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.
ISSN
1746-4811
Language
English
URI
https://hdl.handle.net/10371/174711
DOI
https://doi.org/10.1186/s13007-021-00746-1
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College of Agriculture and Life Sciences (농업생명과학대학)Dept. of Agricultural Biotechnology (농생명공학부)Journal Papers (저널논문_농생명공학부)
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