Classification of steel samples by laser-induced breakdown spectroscopy and random forest
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Decision trees, random forests, and relevance vector machines (RVMs) have achieved good effects under supervised learning for flat steel surface defect classification.
“In addition to the above classifiers, some other classifiers have also achieved good effects under supervised learning for the task of flat steel surface defect classification, such as decision trees, random forests, and relevance vector machines (RVMs).”
From Automated Visual Defect Classification for Flat Steel Surface: A Survey (2020) · cites this paper as [125]
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Automated Visual Defect Classification for Flat Steel Surface: A Survey
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- Authors
- Zhang, T., Xia, D., Tang, H., Yang, X., & Li, H.
- Affiliations
- Northwest University (CN)
- Shaanxi University of Technology (CN)
- Xi'an Shiyou University (CN)
- Corresponding author
- Li, Hua
- Venue
- Chemometrics and Intelligent Laboratory Systems
- Publisher
- Elsevier BV
- Published
- 2016-10
- Volume
- 157
- Pages
- 196-201
- ISSN
- 0169-7439 (ISSN-L)
- OpenAlex
- W2466636344
- Cited by
- 60
- References
- 31
- Citations by year
- 2026: 1 · 2025: 6 · 2024: 5 · 2023: 4 · 2022: 4 · 2021: 4 · 2020: 5 · 2019: 7 · 2018: 12 · 2017: 11 · 2013: 1
- FWCI
- 8.63
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Chemometrics and Intelligent Laboratory Systems (publishedVersion)
- Funders
- National Major Scientific Instruments and Equipment Development Projects of China (2011YQ030113)
- National Natural Science Foundation of China (21175106, 21375105)
- Research Fund for the Doctoral Program of Higher Education of China (20126101110019)
- Topics
- Physical Sciences › Engineering › Mechanics of Materials › Laser-induced spectroscopy and plasma
- Physical Sciences › Chemistry › Analytical Chemistry › Spectroscopy and Chemometric Analyses
- Physical Sciences › Chemistry › Spectroscopy › Spectroscopy and Laser Applications
- Keywords
- laser-induced breakdown spectroscopy, random forest, steel composition, real-time classification
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