Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Softwoods and Hardwoods01:28

Softwoods and Hardwoods

859
Softwoods and hardwoods, derived from different types of trees, are distinguished by their leaf structures and cellular compositions, each serving unique purposes in construction and manufacturing. Softwoods come from cone-bearing trees with needle-like leaves and are predominantly composed of longitudinal cells called tracheids and a smaller proportion of radial cells known as rays. Due to their cellular structure, softwoods are commonly used in construction for structural frames, sheathing,...
859
Lumber Defects01:23

Lumber Defects

818
Lumber defects, which can affect both the appearance and structural integrity of wood, include a variety of growth and manufacturing flaws. Growth defects such as knots and knotholes occur where branches were once attached to the tree trunk, with knotholes forming when these knots fall out. Other natural defects include decay and insect damage, which compromise the wood's strength and durability.
Shakes are minor fractures that run along or across the wood's annual rings, while wane is...
818

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

In Vivo Wound Healing Activity of <i>Abrus cantoniensis</i> Extract.

Evidence-based complementary and alternative medicine : eCAM·2017
Same author

Gigantol from Dendrobium chrysotoxum Lindl. binds and inhibits aldose reductase gene to exert its anti-cataract activity: An in vitro mechanistic study.

Journal of ethnopharmacology·2017
Same author

[High-risk factors and clinical characteristics of massive pulmonary hemorrhage in infants with extremely low birth weight].

Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics·2017
Same author

Liver X receptor agonist T0901317 reverses resistance of A549 human lung cancer cells to EGFR-TKI treatment.

FEBS open bio·2017
Same author

Naked eye plasmonic indicator with multi-responsive polymer brush as signal transducer and amplifier.

Nanoscale·2017
Same author

Graphene oxide adsorbent based dispersive solid phase extraction coupled with multi-pretreatment clean-up for analysis of trace aflatoxins in traditional proprietary Chinese medicines.

Journal of chromatography. B, Analytical technologies in the biomedical and life sciences·2017
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Apr 30, 2026

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images
06:48

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Published on: January 7, 2019

8.9K

A Multi-Source Data Fusion Network for Wood Surface Broken Defect Segmentation.

Yuhang Zhu1, Zhezhuang Xu1, Ye Lin1

  • 1College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China.

Sensors (Basel, Switzerland)
|March 13, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a novel network combining image and depth data for accurate wood broken defect detection. The approach effectively distinguishes defects from interference like stains, significantly reducing false detections in wood products.

Keywords:
U-Netdeep learningmulti-source data fusionsemantic segmentationwood defect detection

More Related Videos

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

2.7K
Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

396

Related Experiment Videos

Last Updated: Apr 30, 2026

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images
06:48

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Published on: January 7, 2019

8.9K
Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

2.7K
Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

396

Area of Science:

  • Materials Science
  • Computer Vision
  • Artificial Intelligence

Background:

  • Wood surface defects, such as broken areas, compromise the structural integrity of wooden products.
  • Current machine vision defect detection methods struggle to differentiate true defects from similar-looking interferences like stains and mineral lines, leading to high false detection rates.

Purpose of the Study:

  • To develop an advanced detection system for wood surface broken defects.
  • To enhance the accuracy and reliability of defect detection by minimizing false positives caused by interfering visual elements.

Main Methods:

  • A multi-source data fusion network based on U-Net architecture was proposed, integrating both image and depth data.
  • An improved ResNet34 was utilized for multi-level feature extraction from image and depth data, incorporating depthwise separable convolution (DSC) and dilated convolution (DC) to optimize computational efficiency and reduce feature redundancy.
  • An adaptive interacting fusion (AIF) module was designed to effectively integrate the multi-source data, generating robust feature representations for defect identification.

Main Results:

  • The proposed multi-source data fusion network demonstrated superior performance in detecting wood broken defects.
  • The system significantly reduced false detections caused by interference, such as stains and mineral lines, compared to existing methods.
  • Complete and accurate segmentation of wood broken defects was achieved.

Conclusions:

  • The integration of image and depth data through a U-Net-based fusion network offers a robust solution for wood broken defect detection.
  • The developed method effectively suppresses interference, leading to improved accuracy and reliability in identifying structural defects in wood.
  • This approach holds promise for enhancing quality control in the wood products industry.