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A Feature Memory Rearrangement Network for Visual Inspection of Textured Surface Defects Toward Edge Intelligent Manufacturing

  • Published:2022 Issue: Volume: Page:1-20
  • ISSN:1545-5955
  • Container-title:IEEE Transactions on Automation Science and Engineering
  • language:
  • Short-container-title:IEEE Trans. Automat. Sci. Eng.

Author:

Yao Haiming1,Yu Wenyong1ORCID,Wang Xue2ORCID

Affiliation:

1. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China

2. Department of Precision Instrument, State Key Laboratory of Precision Measurement Technology and Instruments, Tsinghua University, Beijing, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Control and Systems Engineering

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1. Few-shot unseen defect segmentation for polycrystalline silicon panels with an interpretable dual subspace attention variational learning framework;Advanced Engineering Informatics;2024-10

2. An efficient targeted design for real-time defect detection of surface defects;Optics and Lasers in Engineering;2024-07

3. An Optimized Deep Learning for Efficient Defect Inspection in Smart Industry with Fog Computing;2024 Second International Conference on Data Science and Information System (ICDSIS);2024-05-17

4. Template-based Feature Aggregation Network for industrial anomaly detection;Engineering Applications of Artificial Intelligence;2024-05

5. Image edge detection using pseudo-Boolean polynomials;Sixteenth International Conference on Machine Vision (ICMV 2023);2024-04-03
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