Fiber Quality Prediction Using Nir Spectral Data: Tree-Based Ensemble Learning VS Deep Neural Networks

Utilization of genetic algorithms to optimize loblolly pine wood property models based on NIR spectra and SilviScan data

(2022) Tu X. Ho et al.   WOOD SCIENCE AND TECHNOLOGY

Acoustic emission monitoring of wood materials and timber structures: A critical review

(2022) Vahid Nasir et al.   CONSTRUCTION AND BUILDING MATERIALS

On the selection of the weighting parameter value in optimizing Eucalyptus globulus pulp yield models based on NIR spectra

(2022) Yi Zhen et al.   WOOD SCIENCE AND TECHNOLOGY

Cutting tool temperature monitoring in circular sawing: measurement and multi-sensor feature fusion-based prediction

(2021) Vahid Nasir et al.   The International Journal of Advanced Manufacturing Technology

Online Color Classification System of Solid Wood Flooring Based on Characteristic Features

(2021) Zilong Zhuang et al.   SENSORS

Combined machine learning–wave propagation approach for monitoring timber mechanical properties under UV aging

(2021) Vahid Nasir et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Machine learning-based prediction of internal checks in weathered thermally modified timber

(2021) Joran van Blokland et al.   CONSTRUCTION AND BUILDING MATERIALS

A review on deep learning in machining and tool monitoring: methods, opportunities, and challenges

(2021) Vahid Nasir et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Machine learning-based prediction of surface checks and bending properties in weathered thermally modified timber

(2021) Joran van Blokland et al.   CONSTRUCTION AND BUILDING MATERIALS

Tool wear monitoring by ensemble learning and sensor fusion using power, sound, vibration, and AE signals

(2021) Vahid Nasir et al.   Manufacturing Letters

Prediction of mechanical properties of wood fiber insulation boards as a function of machine and process parameters by random forest

(2020) M. Schubert et al.   WOOD SCIENCE AND TECHNOLOGY

Models for predicting the within-tree and regional variation of tracheid length and width for plantation loblolly pine

(2020) Joseph Dahlen et al.   FORESTRY

Application of neural networks for classifying softwood species using near infrared spectroscopy

(2020) Sang-Yun Yang et al.   JOURNAL OF NEAR INFRARED SPECTROSCOPY

An overview of variable selection methods in multivariate analysis of near-infrared spectra

(2019) Yong-Huan Yun et al.   TRAC-TRENDS IN ANALYTICAL CHEMISTRY

Wood quality of Chinese zither panel based on convolutional neural network and near-infrared spectroscopy

(2019) Yinglai Huang et al.   APPLIED OPTICS

Classification and characterization of thermally modified timber using visible and near-infrared spectroscopy and artificial neural networks: a comparative study on the performance of different NDE methods and ANNs

(2019) Vahid Nasir et al.   WOOD SCIENCE AND TECHNOLOGY

Non-Destructive Evaluation Techniques and What They Tell Us about Wood Property Variation

(2019) Laurence Schimleck et al.   Forests

Artificial neural network and partial least square regressions for rapid estimation of cellulose pulp dryness based on near infrared spectroscopic data

(2019) Lívia Ribeiro Costa et al.   CARBOHYDRATE POLYMERS

Deep learning for smart manufacturing: Methods and applications

(2018) Jinjiang Wang et al.   JOURNAL OF MANUFACTURING SYSTEMS

Regional calibration models for predicting loblolly pine tracheid properties using near-infrared spectroscopy

(2018) Mohamad Nabavi et al.   WOOD SCIENCE AND TECHNOLOGY

Assessing Trees, Wood and Derived Products with near Infrared Spectroscopy: Hints and Tips

(2016) Jakub Sandak et al.   JOURNAL OF NEAR INFRARED SPECTROSCOPY

Predicting and Correlating the Strength Properties of Wood Composite Process Parameters by Use of Boosted Regression Tree Models

(2015) Dillon M. Carty et al.   FOREST PRODUCTS JOURNAL

Quality control methods for thermally modified wood

(2015) Wim Willems et al.   HOLZFORSCHUNG

A review of recent application of near infrared spectroscopy to wood science and technology

(2015) Satoru Tsuchikawa et al.   JOURNAL OF WOOD SCIENCE

Deep learning

(2015) Yann LeCun et al.   NATURE

Fibre Morphological Characteristics of Kraft Pulps of Acacia melanoxylon Estimated by NIR-PLS-R Models

(2015) Helena Pereira et al.   Materials

Application of Near-Infrared Spectroscopy for Evaluation of Drying Stress on Lumber Surface: A Comparison of Artificial Neural Networks and Partial Least Squares Regression

(2014) Ken Watanabe et al.   DRYING TECHNOLOGY

A Review of Recent Near-Infrared Research for Wood and Paper (Part 2)

(2013) Satoru Tsuchikawa et al.   APPLIED SPECTROSCOPY REVIEWS

A survey on feature selection methods

(2013) Girish Chandrashekar et al.   COMPUTERS & ELECTRICAL ENGINEERING

A Review of Band Assignments in near Infrared Spectra of Wood and Wood Components

(2011) Manfred Schwanninger et al.   JOURNAL OF NEAR INFRARED SPECTROSCOPY

Modeling the longitudinal variation in wood specific gravity of planted loblolly pine (Pinus taeda) in the United States

(2010) F. Antony et al.   CANADIAN JOURNAL OF FOREST RESEARCH

Eucalyptus camaldulensis density and fiber length estimated by near-infrared spectroscopy

(2010) Tetsuya Inagaki et al.   WOOD SCIENCE AND TECHNOLOGY

Regional variation in wood specific gravity of planted loblolly pine in the United States

(2008) Lewis Jordan et al.   CANADIAN JOURNAL OF FOREST RESEARCH