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

Detection of Gross Error: The Q Test01:00

Detection of Gross Error: The Q Test

7.3K
When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
7.3K
Lumber Defects01:23

Lumber Defects

698
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...
698
Imperfections in Crystal Structure: Point, Line and Plane Defects01:25

Imperfections in Crystal Structure: Point, Line and Plane Defects

90
A perfect crystal, in theory, has a uniform structure with the same unit cell and lattice points throughout. However, any deviation from this periodic arrangement is known as an imperfection or defect. These defects can be categorized into three types: point, line, and plane defects.Point defects occur when there is a deviation from the ideal due to missing atoms, displaced atoms, or additional atoms. These imperfections might occur due to imperfect packing during crystallization or because of...
90
Detection of Black Holes01:10

Detection of Black Holes

2.6K
Although black holes were theoretically postulated in the 1920s, they remained outside the domain of observational astronomy until the 1970s.
Their closest cousins are neutron stars, which are composed almost entirely of neutrons packed against each other, making them extremely dense. A neutron star has the same mass as the Sun but its diameter is only a few kilometers. Therefore, the escape velocity from their surface is close to the speed of light.
Not until the 1960s, when the first neutron...
2.6K
Quantifying and Rejecting Outliers: The Grubbs Test01:02

Quantifying and Rejecting Outliers: The Grubbs Test

4.6K
Sometimes, a data set can have a recorded numerical observation that greatly  deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier.  To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This...
4.6K
Boundary Conditions: Lossless Lines01:21

Boundary Conditions: Lossless Lines

455
Consider a single-phase, two-wire, lossless transmission line terminated by an impedance at the receiving end and a source with Thevenin voltage and impedance at the sending end. The line, with length, has a surge impedance and wave velocity determined by the line's inductance and capacitance.
At the receiving end, the boundary condition states that the voltage equals the product of the receiving-end impedance and current. This relationship is expressed as a function of the incident and...
455

You might also read

Related Articles

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

Sort by
Same author

A DAG-Based Offloading Strategy with Dynamic Parallel Factor Adjustment for Edge Computing in IoV.

Sensors (Basel, Switzerland)·2025
Same author

A Multi-Branch Network for Integrating Spatial, Spectral, and Temporal Features in Motor Imagery EEG Classification.

Brain sciences·2025
Same author

A Nasal Resistance Measurement System Based on Multi-Sensor Fusion of Pressure and Flow.

Micromachines·2025
Same author

Gastrodin: a comprehensive pharmacological review.

Naunyn-Schmiedeberg's archives of pharmacology·2024
Same author

Extraction process, physicochemical properties, and digestive performance of red yeast rice starch.

Biotechnology and applied biochemistry·2023
Same author

Research on the Construction of Grain Food Multi-Chain Blockchain Based on Zero-Knowledge Proof.

Foods (Basel, Switzerland)·2023
Same journal

Correction: Kang et al. Fluid Flow to Electricity: Capturing Flow-Induced Vibrations with Micro-Electromechanical-System-Based Piezoelectric Energy Harvester. <i>Micromachines</i> 2024, <i>15</i>, 581.

Micromachines·2026
Same journal

Femtosecond Laser Texturing of Wood Coatings with Bio-Based Epoxy and Wax Additives for Enhanced Hydrophobicity.

Micromachines·2026
Same journal

Engineering of Optoelectronic Devices for Renewable Energy Applications.

Micromachines·2026
Same journal

Phase Transformation and Electrochemical Behavior of Hexagonal TiO<sub>2</sub> Nanotubes Under Different Annealing Temperatures and Heating Rates.

Micromachines·2026
Same journal

Process Optimization and Predictive Modeling of Femtosecond Laser Precision Milling for Commercial PMMA Slices.

Micromachines·2026
Same journal

A Hybrid Preprocessing Multi-Objective Surrogate Model for Thermal MEMS Actuators.

Micromachines·2026
See all related articles

Related Experiment Video

Updated: Mar 29, 2026

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography
11:34

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography

Published on: May 15, 2017

11.6K

A Novel PCB Surface Defect Detection Method Based on the GBE-YOLOv8 Model.

Chao Gao1, Xin Zhang1, Mengting Bai1

  • 1School of Computer and Artificial Intelligence, Beijing Technology and Business University, Beijing 102488, China.

Micromachines
|March 28, 2026
PubMed
Summary
This summary is machine-generated.

A new Ghost-BiFPN-Efficient-YOLOv8 (GBE-YOLOv8) model enhances printed circuit board (PCB) defect detection. This AI approach improves accuracy and efficiency for real-time surface inspection in manufacturing.

Keywords:
PCBYOLOv8ndeep learningdefect detection

More Related Videos

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

2.8K

Related Experiment Videos

Last Updated: Mar 29, 2026

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography
11:34

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography

Published on: May 15, 2017

11.6K
Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

2.8K

Area of Science:

  • Computer Vision
  • Artificial Intelligence
  • Manufacturing Technology

Background:

  • Surface defect detection is crucial for printed circuit board (PCB) quality and safety.
  • Real-time detection of tiny PCB defects is challenging due to complex layouts.

Purpose of the Study:

  • To develop a novel and efficient model for PCB surface defect detection.
  • To improve the accuracy and computational efficiency of existing object detection models for PCB inspection.

Main Methods:

  • Proposed a Ghost-BiFPN-Efficient-YOLOv8 (GBE-YOLOv8) model based on YOLOv8n.
  • Incorporated lightweight Ghost Conv, G-C2f, BiFPN-Concat, and Efficient Head modules.
  • Analyzed model interpretability using class activation heatmaps.

Main Results:

  • Achieved high performance with mAP@0.5 of 98.9% and mAP@0.5:0.95 of 61.4%.
  • Demonstrated reduced computational complexity (2.6 M parameters, 7.5 GFLOPs) and high speed (252 FPS).
  • Outperformed baseline and state-of-the-art object detection algorithms.

Conclusions:

  • The GBE-YOLOv8 model offers a significant advancement in PCB surface defect detection.
  • The proposed optimizations effectively balance detection accuracy and computational efficiency.
  • Provides a reliable technical solution for high-precision, real-time PCB inspection in industrial settings.