Automatic and non-destructive inner wood quality assessment of wood logs using 3D computed tomography and machine learning
Authors
Gokul Kottilapurath Surendran
Faculty of Forestry and Wood Sciences, Czech University of Life Sciences Prague, Prague, Czech Republic
Tomáš Bucha
National Forest Centre, Centre of Excellence of Forest-based Industry – LignoSilva, Zvolen, Slovak Republic
Tomáš Gergeľ
National Forest Centre, Centre of Excellence of Forest-based Industry – LignoSilva, Zvolen, Slovak Republic
Ondrej Vacek
National Forest Centre, Centre of Excellence of Forest-based Industry – LignoSilva, Zvolen, Slovak Republic
Technical University in Zvolen, Faculty of Wood Sciences and Technology, Zvolen, Slovak Republic
Martin Mokros
University College London, Department of Geography, UK- London, United Kingdom
DOI: https://doi.org/10.2478/forj-2026-0011 | Journal eISSN: 2454-0358 (formerly 0323-1046, 1338-4295) | Journal ISSN: 2454-034X (formerly 0323-1046)
Language: English
Page range: 171 - 184
Published online: Oct 8, 2026
Published in print: Sep 1, 2026
Published by: National Forest Centre and Czech University of Life Sciences in Prague, Faculty of Forestry and Wood Sciences
In partnership with: Paradigm Publishing Services
Keywords:
Related subjects:
© 2026 Gokul Kottilapurath Surendran, Tomáš Bucha, Tomáš Gergeľ, Ondrej Vacek, Martin Mokros, published by National Forest Centre and Czech University of Life Sciences in Prague, Faculty of Forestry and Wood Sciences
This work is licensed under the Creative Commons Attribution 4.0 License.