Multi-class Classification Methods of Enhanced LS-TWSVM for Strip Steel Surface Defects
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The most popular algorithms applied to flat steel surface defect classification are PCA and LPP.
“Of these methods, the most popular algorithms applied to flat steel surface defect classification are PCA and LPP [112, 113].”
From Automated Visual Defect Classification for Flat Steel Surface: A Survey (2020) · cites this paper as [113]
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Automated Visual Defect Classification for Flat Steel Surface: A Survey
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- Authors
- Chu, M.-X., Wang, A.-N., Gong, R.-F., & Sha, M.
- Affiliations
- Northeastern University (CN)
- Venue
- Journal of Iron and Steel Research International
- Published
- 2014-02
- Volume
- 21
- Issue
- 2
- Pages
- 174-180
- ISSN
- 2210-3988 (ISSN-L)
- 1006-706X
- OpenAlex
- W1963937997
- Cited by
- 21
- References
- 14
- Citations by year
- 2025: 2 · 2024: 2 · 2021: 2 · 2020: 1 · 2019: 2 · 2018: 3 · 2017: 4 · 2016: 4 · 2015: 1
- FWCI
- 5.64
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Iron and Steel Research International (publishedVersion)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Industrial Vision Systems and Defect Detection
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning and ELM
- Physical Sciences › Computer Science › Information Systems › Data Mining and Machine Learning Applications
- Keywords
- multi-class classification, least squares twin support vector machine, binary trees, weight parameter, class imbalance, large-scale data
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