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Wood Material Science & Engineering Volume 18, 2023 - Issue 2
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Original Articles

Comparing modelling performance of chemometric methods for wood discrimination by near infrared spectroscopy

F. Digdem TuncerFaculty of Forestry, Department of Forest Biology and Wood Protection Technology, Istanbul University-Cerrahpasa, Istanbul, TurkeyCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-6588-4789View further author information
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Pages 422-433 | Received 12 Nov 2021, Accepted 05 Feb 2022, Published online: 23 Feb 2022

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Read on this site (2)

Sohrab Rahimi, Stavros Avramidis, Farrokh Sassani & Vahid Nasir. (2024) Machine learning-based prediction of internal moisture variation in kiln-dried timber. Wood Material Science & Engineering 19:2, pages 499-510.
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Xi Pan, Jian Qiu & Zhong Yang. (2023) Identification of softwood species using convolutional neural networks and raw near-infrared spectroscopy. Wood Material Science & Engineering 18:4, pages 1338-1348.
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Articles from other publishers (1)

Rui Li, Yan Liu, Zhenzhen Xia, Qiao Wang, Xin Liu & Zhiyong Gong. (2023) Discriminating geographical origins and determining active substances of water caltrop shells through near-infrared spectroscopy and chemometrics. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 303, pages 123198.
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