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

Modeling of Diode Forward Characteristics01:19

Modeling of Diode Forward Characteristics

1.5K
Understanding the behavior of diodes when forward-biased is a fundamental aspect of electronic circuit design and analysis. This analysis primarily utilizes two models: the exponential diode model and the constant-voltage-drop model. The exponential model comes into play when the source voltage exceeds 0.5 volts, pushing the diode current to rise exponentially above the saturation current. This relationship is graphically depicted in the current-voltage (I-V) curve, illustrating the diode's...
1.5K
Methods of Medium Optimization01:28

Methods of Medium Optimization

70
Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...
70

You might also read

Related Articles

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

Sort by
Same author

Research on filter life and performance prediction integrating attention mechanism and optimization algorithms.

The Review of scientific instruments·2026
Same author

A large language model for multimodal identification of crop diseases and pests.

Scientific reports·2025
Same author

Two-Stream Retentive Long Short-Term Memory Network for Dense Action Anticipation.

Computational intelligence and neuroscience·2022
Same author

Discontinuous Track Recognition System Based on PolyLaneNet for Darwin-op2 Robot.

Computational intelligence and neuroscience·2022
Same author

Bionic Electronic Nose Based on MOS Sensors Array and Machine Learning Algorithms Used for Wine Properties Detection.

Sensors (Basel, Switzerland)·2018

Related Experiment Video

Updated: May 2, 2026

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

42.8K

An Optimization Method for PCB Surface Defect Detection Model Based on Measurement of Defect Characteristics and

Huixiang Liu1, Xin Zhao1, Qiong Liu1,2

  • 1School of Automation, Beijing Information Science and Technology University, Beijing 100192, China.

Sensors (Basel, Switzerland)
|November 27, 2024
PubMed
Summary
This summary is machine-generated.

A new YOLOv8_DSM algorithm enhances Printed Circuit Board (PCB) defect detection by improving feature extraction and fusion. This advanced method significantly boosts accuracy and efficiency in identifying diverse PCB surface flaws.

Keywords:
PCBYOLOv8defect detectionexplainabilitytarget characteristics

More Related Videos

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

470
Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
08:27

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

982

Related Experiment Videos

Last Updated: May 2, 2026

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

42.8K
Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

470
Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
08:27

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

982

Area of Science:

  • Computer Vision
  • Artificial Intelligence
  • Manufacturing Technology

Background:

  • Printed Circuit Boards (PCBs) are critical electronic components.
  • Detecting diverse, complex PCB surface defects is challenging due to low resolution and background similarity.
  • Existing methods struggle with the intricate nature of PCB surface anomalies.

Purpose of the Study:

  • To develop an optimized algorithm for accurate and efficient PCB surface defect detection.
  • To address the challenges posed by defect complexity, low feature resolution, and background resemblance.
  • To enhance the performance of deep learning models for automated PCB quality inspection.

Main Methods:

  • Proposed YOLOv8_DSM algorithm incorporating CSPLayer_2DCNv3 with deformable convolution for adaptive feature extraction.
  • Introduced Shallow-layer Low-semantic Feature Fusion Module (SLFFM) with bi-level routing attention (BRA) for enhanced feature fusion and defect-background discrimination.
  • Utilized feature map separation-based SPDConv for downsampling and MPDIoU as the bounding box loss function.

Main Results:

  • YOLOv8_DSM achieved a mean Average Precision (mAP) of 63.4% (0.5:0.9 IoU), a 5.14% improvement over the baseline YOLOv8.
  • The model demonstrated a high processing speed of 144.6 Frames Per Second (FPS).
  • The algorithm was successfully deployed in a practical PCB quality inspection system.

Conclusions:

  • The YOLOv8_DSM algorithm offers a significant advancement in PCB surface defect detection.
  • The integration of deformable convolution, shallow-layer feature fusion, and attention mechanisms effectively tackles detection challenges.
  • The model's high accuracy and speed make it suitable for real-world industrial PCB quality control applications.