Defect Classification Recognition on Strip Steel Surface Using Second-Order Cone Programming-Relevance Vector Machine Algorithm
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FT can reflect local outstanding feature information and is widely used in the extraction of features of steel surface images.
“FT can reflect the local outstanding feature information, which is widely used in the extraction of features of steel surface images [96, 97].”
From Automated Visual Defect Classification for Flat Steel Surface: A Survey (2020) · cites this paper as [96]
The Fourier transform is invariant to translation, expansion and rotation.
“Invariance to translation, expansion and rotation.”
From Automated Visual Defect Classification for Flat Steel Surface: A Survey (2020) · cites this paper as [96]
The Fourier transform lacks a localized signal analysis function.
“Lack of localized signal analysis function.”
From Automated Visual Defect Classification for Flat Steel Surface: A Survey (2020) · cites this paper as [96]
Wavelet transform has difficulty choosing a wavelet basis.
“Difficulty in choosing wavelet basis.”
From Automated Visual Defect Classification for Flat Steel Surface: A Survey (2020) · cites this paper as [96]
Cited by
Sorted by citations
Automated Visual Defect Classification for Flat Steel Surface: A Survey
Luo, Q., Fang, X., Su, J., Zhou, J., Zhou, B., Yang, C., Liu, L., Gui, W., & Tian, L. (2020) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2020.3030167 · Cited by 148 · see citing works
“FT can reflect the local outstanding feature information, which is widely used in the extraction of features of steel surface images [96], [97].”
BackgroundDefect Image Sample Generation With Diffusion Prior for Steel Surface Defect Recognition
Tai, Y., Yang, K., Peng, T., Huang, Z., & Zhang, Z. (2024) · IEEE Transactions on Automation Science and Engineering · doi:10.1109/tase.2024.3482362 · Cited by 37 · see citing works
“Among existing methods for defect recognition in industrial manufacturing [3], [4], [5], deep learning techniques are increasingly prevalent [6], [7], [8].”
Steel Surface Defect Classification Based on Discriminant Manifold Regularized Local Descriptor
Zhao, J., Peng, Y., & Yan, Y. (2018) · IEEE Access · doi:10.1109/access.2018.2881962 · Cited by 26 · see citing works
“[10] employed the multi-kernel function RVM which is solved by SOCP algorithm to improve the performance of defect classification recognition on steel strip surface.”
MethodAdaptive-MAML: Few-shot metal surface defects diagnosis based on model-agnostic meta-learning
Pang, S., Zhang, L., Yuan, Y., Zhao, W., Wang, S., & Wang, S. (2023) · Measurement · doi:10.1016/j.measurement.2023.113612 · Cited by 22 · see citing works
Defect Detection and Classification of Strip Steel Based on Improved VIT Model
Xing, L., Li, T., Fan, H., & Zhu, H. (2022) · IFIP advances in information and communication technology · doi:10.1007/978-3-031-03948-5_26 · Cited by 7 · see citing works
Compact and Efficient Feature Representation for Defect in hot rolled strip steel:A postion paper
Su, J., Luo, Q., & Yang, C. (2022) · Asian Control Conference (ASCC) · doi:10.23919/ascc56756.2022.9828012
- Authors
- Dongyan, C., Kewen, X., Aslam, N., & Jingzhong, H.
- Affiliations
- School of Electronics and Information Engineering, Hebei University of Technology, Tianjin, 300401, China
- Hebei University of Technology (CN)
- ORCID
- Aslam, Nelofar
- Venue
- Journal of Computational and Theoretical Nanoscience
- Publisher
- American Scientific Publishers
- Published
- 2016-09-01
- Volume
- 13
- Issue
- 9
- Pages
- 6141-6148
- ISSN
- 1546-1955 (ISSN-L)
- OpenAlex
- W2581023882
- Cited by
- 6
- References
- 0
- Citations by year
- 2024: 1 · 2023: 1 · 2022: 2 · 2020: 1 · 2018: 1
- FWCI
- 0.45
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Computational and Theoretical Nanoscience (publishedVersion)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Industrial Vision Systems and Defect Detection
- Physical Sciences › Engineering › Mechanical Engineering › Non-Destructive Testing Techniques
- Physical Sciences › Engineering › Civil and Structural Engineering › Infrastructure Maintenance and Monitoring
- Keywords
- defect classification, second-order cone programming, relevance vector machine, steel quality inspection
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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