A Sawn Timber Tree Species Recognition Method Based on AM-SPPResNet

Open-Set Domain Adaptation in Machinery Fault Diagnostics Using Instance-Level Weighted Adversarial Learning

(2021) Wei Zhang et al.   IEEE Transactions on Industrial Informatics

Detection and visualization of encoded local features as anatomical predictors in cross-sectional images of Lauraceae

(2020) Sung-Wook Hwang et al.   JOURNAL OF WOOD SCIENCE

Predicting compressive strength of consolidated molecular solids using computer vision and deep learning

(2020) Brian Gallagher et al.   MATERIALS & DESIGN

Prediction of tensile strength of sawn timber: definitions and performance of indicating properties based on surface laser scanning and dynamic excitation

(2020) Andreas Briggert et al.   MATERIALS AND STRUCTURES

Defect Detection of Industry Wood Veneer Based on NAS and Multi-Channel Mask R-CNN

(2020) Jiahao Shi et al.   SENSORS

Classification of mechanism of reinforcement in the fiber-matrix interface: Application of Machine Learning on nanoindentation data

(2020) Georgios Konstantopoulos et al.   MATERIALS & DESIGN

DeepRescore: Leveraging Deep Learning to Improve Peptide Identification in Immunopeptidomics

(2020) Kai Li et al.   PROTEOMICS

Assessment of Tomato Maturity in Different Layers by Spatially Resolved Spectroscopy

(2020) Yuping Huang et al.   SENSORS

Anatomical features of Fagaceae wood statistically extracted by computer vision approaches: Some relationships with evolution

(2019) Kayoko Kobayashi et al.   PLoS One

Wood species recognition through multidimensional texture analysis

(2018) Panagiotis Barmpoutis et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Multiresolution LDBP descriptors for texture classification using anisotropic diffusion with an application to wood texture analysis

(2017) P.S. Hiremath et al.   PATTERN RECOGNITION LETTERS

Attributes of Sawn Timber Important for the Manufacturers of Value-Added Wood Products in Malaysia

(2016) Jegatheswaran Ratnasingam et al.   BioResources

Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition

(2015) Kaiming He et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Study on the identification of the wood surface defects based on texture features

(2015) Xie YongHua et al.   OPTIK

Bayesian texture classification and retrieval based on multiscale feature vector

(2010) Turgay Celik et al.   PATTERN RECOGNITION LETTERS

An optimum feature extraction method for texture classification

(2008) Engin Avci et al.   EXPERT SYSTEMS WITH APPLICATIONS