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 Experiment Video

Updated: Sep 12, 2025

Longitudinal Micro-Computed Tomography Image Analysis for User-Defined Region of Interest in Critical-Sized Bone Defects
08:39

Longitudinal Micro-Computed Tomography Image Analysis for User-Defined Region of Interest in Critical-Sized Bone Defects

Published on: June 24, 2025

173

PEYOLO a perception efficient network for multiscale surface defects detection.

Xun Li1,2,3, Yuzhen Zhao4, Xiangke Jiao1

  • 1Xi'an Key Laboratory of Advanced Photo-Electronics Materials and Energy Conversion Device, School of Electronic Information, Xijing University, Xi'an, 710123, People's Republic of China.

Scientific Reports
|August 6, 2025
PubMed
Summary

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Fog-Adaptive-YOLO: A lightweight model for insulator defect detection.

PloS one·2026
Same author

GS-YOLO: A lightweight high-accuracy model for small target detection in drone aerial images.

PloS one·2026
Same author

Downregulation of NOX2 Expression Alleviates Severe Acute Pancreatitis by Restoring Autophagy and Inhibiting mtDNA-mediated Activation of the cGAS-STING Signalling Pathway.

Inflammation·2026
Same author

SCB-YOLO: a lightweight adaptive attention-enhanced network for student behavior detection in complex classroom settings.

Scientific reports·2026
Same author

Nicotinamide Mononucleotide Enhances Boar Sperm Quality via Maintaining Mitochondrial Function During Liquid Storage.

Animals : an open access journal from MDPI·2025
Same author

GURLKNet gated unified reparameterized large kernel network for insulator defect detection.

Scientific reports·2025

This study introduces PEYOLO, an efficient network for detecting small steel surface defects. PEYOLO improves accuracy and speed in complex production environments for real-time quality control.

Area of Science:

  • Materials Science
  • Computer Vision
  • Artificial Intelligence

Background:

  • Steel defect detection is vital for quality control in manufacturing.
  • Detecting small-scale defects in complex industrial settings presents significant challenges.
  • Existing methods struggle with multi-scale defects and efficiency.

Purpose of the Study:

  • To develop a perception-efficient network for fast and accurate detection of multi-scale steel surface defects.
  • To enhance feature fusion and global feature capture for improved defect identification.
  • To provide a solution suitable for real-time steel defect detection applications.

Main Methods:

  • Introduced Defect Capture Path Aggregation Network for multi-scale feature learning.
  • Designed Perception-Efficient Head (PEHead) to reduce missed detections by mitigating aliasing.
Keywords:
Deep learningIndustrial detectionLightweight networkMulti-scale feature extractionSurface defect detectionYOLOv8

More Related Videos

Multiscale Structures Aggregated by Imprinted Nanofibers for Functional Surfaces
06:14

Multiscale Structures Aggregated by Imprinted Nanofibers for Functional Surfaces

Published on: September 11, 2018

6.7K
Picometer-Precision Atomic Position Tracking through Electron Microscopy
15:04

Picometer-Precision Atomic Position Tracking through Electron Microscopy

Published on: July 3, 2021

7.7K

Related Experiment Videos

Last Updated: Sep 12, 2025

Longitudinal Micro-Computed Tomography Image Analysis for User-Defined Region of Interest in Critical-Sized Bone Defects
08:39

Longitudinal Micro-Computed Tomography Image Analysis for User-Defined Region of Interest in Critical-Sized Bone Defects

Published on: June 24, 2025

173
Multiscale Structures Aggregated by Imprinted Nanofibers for Functional Surfaces
06:14

Multiscale Structures Aggregated by Imprinted Nanofibers for Functional Surfaces

Published on: September 11, 2018

6.7K
Picometer-Precision Atomic Position Tracking through Electron Microscopy
15:04

Picometer-Precision Atomic Position Tracking through Electron Microscopy

Published on: July 3, 2021

7.7K
  • Proposed Receptive Field Extension Module (RFEM) to enhance global feature capture and handle aspect ratio variations.
  • Integrated these modules into the YOLO framework, creating PEYOLO.

    • Main Results:

    • PEYOLO achieved mAP50 improvements of 3.5% (NEU-DET), 9.1% (GC10-DET), and 3.3% (Severstal) over YOLOv8n.
    • The method maintained high inference speed, comparable to real-time requirements.
    • Demonstrated significant performance gains on public steel defect datasets.

    Conclusions:

    • PEYOLO effectively addresses the challenge of detecting small-scale, multi-scale steel surface defects.
    • The proposed network offers a balance of high accuracy and fast inference speeds.
    • PEYOLO is a viable solution for real-time steel defect detection in industrial quality control.