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Wood Material Science & Engineering Volume 10, 2015 - Issue 4
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Original Articles

Optimization potential for perception-oriented appearance classification by simulated sawing of computed tomography-scanned logs of Norway spruce

Lorenz BreinigForest Research Institute of Baden-Württemberg, 79100Freiburg, GermanyCorrespondence[email protected]
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,
Olof BromanDivision of Wood Science and Engineering, Luleå University of Technology, 931 87Skellefteå, SwedenView further author information
,
Franka BrüchertForest Research Institute of Baden-Württemberg, 79100Freiburg, GermanyView further author information
&
Gero BeckerChair of Forest Utilisation, Institute of Forest Sciences, University of Freiburg, 79085Freiburg, GermanyView further author information
Pages 319-334 | Received 08 Jul 2014, Accepted 14 Oct 2014, Published online: 07 Nov 2014

Citations (5)

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Linus Olofsson, Olof Broman, Johan Oja & Dick Sandberg. (2021) Product-adapted grading of Scots pine sawn timber by an industrial CT-scanner using a visually-trained machine-learning method. Wood Material Science & Engineering 16:4, pages 279-286.
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Articles from other publishers (4)

Xiaolin Li, Guillaume Pot, Phuc Ngo, Joffrey Viguier & Hélène Penvern. (2023) An image processing method to recognize position of sawn boards within the log. Wood Science and Technology 57:6, pages 1401-1420.
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Alfred Teischinger, Roland Maderebner & Alexander Petutschnigg. 2023. Springer Handbook of Wood Science and Technology. Springer Handbook of Wood Science and Technology 1787 1833 .
Kazimierz A. Orlowski, Daniel Chuchala, Marcin Szczepanski, Wojciech Migda, Wiktoria Wojnicz & Jakub Sandak. (2022) Lateral forces determine dimensional accuracy of the narrow-kerf sawing of wood. Scientific Reports 12:1.
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Martin Pernkopf, Martin Riegler & Manfred Gronalt. (2019) Profitability gain expectations for computed tomography of sawn logs. European Journal of Wood and Wood Products 77:4, pages 619-631.
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