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Related Experiment Video

Updated: Jan 12, 2026

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
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A Real-Time Defect Detector With Content-Guided Feature Extraction and Detail Enhancement.

Yuefei Huang1, Tingting Fang1, Ming Ye1

  • 1College of Artificial Intelligence, Southwest University, Chongqing, China.

Annals of the New York Academy of Sciences
|November 3, 2025
PubMed
Summary

This study introduces CGRNet, an efficient real-time detector for industrial surface defect detection. CGRNet enhances small defect identification and achieves high accuracy, addressing complex backgrounds and missed defects.

Keywords:
content‐guided feature extractiondual residual attentionindustrial surface anomaly detectionreal‐time defect detector

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Area of Science:

  • Materials Science
  • Computer Vision
  • Artificial Intelligence

Background:

  • Industrial surface defect detection is challenged by complex backgrounds and small, easily missed defects.
  • Existing methods often struggle with accuracy and real-time processing.

Purpose of the Study:

  • To develop an efficient and accurate real-time detector for industrial surface defects.
  • To improve the detection of small defects and handle complex backgrounds.

Main Methods:

  • Introduced CGRNet, a content-guided feature extraction network with adaptive high-frequency filtering.
  • Employed a detail enhancement module with a double residual attention mechanism for multi-scale feature interaction.
  • Utilized SIoU loss function and Lion optimizer for faster convergence and improved localization.

Main Results:

  • CGRNet achieved 93.6% mAP on the PVEL_AD dataset, outperforming existing methods.
  • The model demonstrated real-time performance at 81.9 frames per second on the NEU-DET dataset.
  • Significant improvements in detecting small defects and handling complex backgrounds were observed.

Conclusions:

  • CGRNet offers an effective solution for real-time industrial surface defect detection.
  • The proposed methods enhance accuracy and processing speed, meeting practical application demands.