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Author: Sang-Yun Yang
8 Articles are founded.
Effect of Organic Solvent Extractives on Korean Softwoods Classification Using Near-infrared Spectroscopy
Journal of the Korean Wood Science and Technology 2019;47(4):509-518.
https://doi.org/10.5658/WOOD.2019.47.4.509
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https://doi.org/10.5658/WOOD.2019.47.4.509
Wood Species Classification Utilizing Ensembles of Convolutional Neural Networks Established by Near-Infrared Spectra and Images Acquired from Korean Softwood Lumber
Journal of the Korean Wood Science and Technology 2019;47(4):385-392.
https://doi.org/10.5658/WOOD.2019.47.4.385
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https://doi.org/10.5658/WOOD.2019.47.4.385
Performance Enhancement of Automatic Wood Classification of Korean Softwood by Ensembles of Convolutional Neural Networks
Journal of the Korean Wood Science and Technology 2019;47(3):265-276.
https://doi.org/10.5658/WOOD.2019.47.3.265
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https://doi.org/10.5658/WOOD.2019.47.3.265
Visual Classification of Wood Knots Using k-Nearest Neighbor and Convolutional Neural Network
Journal of the Korean Wood Science and Technology 2019;47(2):229-238.
https://doi.org/10.5658/WOOD.2019.47.2.229
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https://doi.org/10.5658/WOOD.2019.47.2.229
Soft Independent Modeling of Class Analogy for Classifying Lumber Species Using Their Near-infrared Spectra
Journal of the Korean Wood Science and Technology 2019;47(1):101-109.
https://doi.org/10.5658/WOOD.2019.47.1.101
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https://doi.org/10.5658/WOOD.2019.47.1.101
Evaluation of Deterioration of Larix kaempferi Wood Heat-treated by Superheated Steam through Field Decay Test for 12 Months
Journal of the Korean Wood Science and Technology 2018;46(5):497-510.
https://doi.org/10.5658/WOOD.2018.46.5.497
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https://doi.org/10.5658/WOOD.2018.46.5.497
Automatic Wood Species Identification of Korean Softwood Based on Convolutional Neural Networks
Journal of the Korean Wood Science and Technology 2017;45(6):797-808.
https://doi.org/10.5658/WOOD.2017.45.6.797
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https://doi.org/10.5658/WOOD.2017.45.6.797
Finite Difference Evaluation of Moisture Profile in Boxed-heart Large-cross-section Square Timber of Pinus densiflora during High Temperature Drying
Journal of the Korean Wood Science and Technology 2017;45(6):762-771.
https://doi.org/10.5658/WOOD.2017.45.6.762
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https://doi.org/10.5658/WOOD.2017.45.6.762