지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2019.1
- 수록면
- 385 - 392 (8page)
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초록· 키워드
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In our previous study, we investigated the use of ensemble models based on LeNet and MiniVGGNet to classify the images of transverse and longitudinal surfaces of five Korean softwoods (cedar, cypress, Korean pine, Korean red pine, and larch). It had accomplished an average F1 score of more than 98%; the classification performance of the longitudinal surface image was still less than that of the transverse surface image. In this study, ensemble methods of two different convolutional neural network models (LeNet3 for smartphone camera images and NIRNet for NIR spectra) were applied to lumber species classification. Experimentally, the best classification performance was obtained by the averaging ensemble method of LeNet3 and NIRNet. The average F1 scores of the individual LeNet3 model and the individual NIRNet model were 91.98% and 85.94%, respectively. By the averaging ensemble method of LeNet3 and NIRNet, an average F1 score was increased to 95.31%.
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참고문헌 (20)
참고문헌 신청
Adedipe, O. E. / 2008 / Classification of red oak(Quercus rubra)and white oak(Quercus alba)wood using a near infrared spectrometer and soft independent modelling of class analogies / Journal of Near Infrared Spectroscopy 16(1):49~57
Brunner, C. C. / 2007 / Using color in machine vision systems for wood processing / Wood and Fiber Science 22(4):413~428
조병관 / 2016 / Study on Rapid Measurement of Wood Powder Concentration of Wood-Plastic Composites using FT-NIR and FT-IR Spectroscopy Techniques / 목재공학 44(6):852~863
엄유정 / 2018 / 밀성박씨 경주 손곡문중 목판의 수종식별 / 목재공학 46(3):270~277
Goutte, C. / 2005 / A probabilistic interpretation of precision, recall and F-score, with implication for evaluation / European Conference on Information Retrieval :345~359
Brunner, C. C. / 2007 / Using color in machine vision systems for wood processing / Wood and Fiber Science 22(4):413~428
조병관 / 2016 / Study on Rapid Measurement of Wood Powder Concentration of Wood-Plastic Composites using FT-NIR and FT-IR Spectroscopy Techniques / 목재공학 44(6):852~863
엄유정 / 2018 / 밀성박씨 경주 손곡문중 목판의 수종식별 / 목재공학 46(3):270~277
Goutte, C. / 2005 / A probabilistic interpretation of precision, recall and F-score, with implication for evaluation / European Conference on Information Retrieval :345~359
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Performance Enhancement of Automatic Wood Classification of Korean Softwood by Ensembles of Convolutional Neural Networks
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Partial Least Squares Analysis on Near-Infrared Absorbance Spectra by Air-dried Specific Gravity of Major Domestic Softwood Species
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Soft Independent Modeling of Class Analogy for Classifying Lumber Species Using Their Near-infrared Spectra
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Looking inside S2S predictions: Inter-model comparison and multi-model ensemble performance
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Effect of Organic Solvent Extractives on Korean Softwoods Classification Using Near-infrared Spectroscopy
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Leave-one-out Bayesian model averaging for probabilistic ensemble forecasting
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Future projections and uncertainty assessment of precipitation extremes in the Korean peninsula from the CMIP6 ensemble
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Global Ensemble Prediction System in KMA
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