Product-adapted grading of Scots pine sawn timber by an industrial CT-scanner using a visually-trained machine-learning method-Reference-Cited by-同舟云学术

Product-adapted grading of Scots pine sawn timber by an industrial CT-scanner using a visually-trained machine-learning method

Published:2021-07-04 Issue:4 Volume:16 Page:279-286
ISSN:1748-0272
Container-title:Wood Material Science & Engineering
language:en
Short-container-title:Wood Material Science & Engineering

Author:

Olofsson Linus¹^ORCID,Broman Olof¹,Oja Johan¹²,Sandberg Dick¹

Affiliation:

1. Wood Science and Engineering, Luleå University of Technology, Skellefteå, Sweden

2. Norra Timber, Skellefteå, Sweden

Funder

Swedish Innovation Agency

Publisher

Informa UK Limited

Subject

General Materials Science

Link

https://www.tandfonline.com/doi/pdf/10.1080/17480272.2021.1955298

Reference15 articles.

1. Anon. (2018). Boardmaster. Accessed 12 June 2018, available at https://finscan.fi/products/boardmaster/?lang=en. Note: older predecessor to BoardmasterNOVA.

2. Anon. (2019). Simca. Accessed 3 January 2019, available at https://umetrics.com/products/simca.

3. Customer adapted grading of Scots pine sawn timber using a multivariate method

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

5. Classification of wood surfaces according to visual appearance by multivariate analysis of wood feature data

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