Surface Defect Classification for Hot-Rolled Steel Strips by Selectively Dominant Local Binary Patterns
- Submitting institution
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University of Hertfordshire
- Unit of assessment
- 12 - Engineering
- Output identifier
- 19719389
- Type
- D - Journal article
- DOI
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10.1109/ACCESS.2019.2898215
- Title of journal
- IEEE Access
- Article number
- -
- First page
- 23488
- Volume
- 7
- Issue
- -
- ISSN
- 2169-3536
- Open access status
- Compliant
- Month of publication
- February
- Year of publication
- 2019
- URL
-
-
- Supplementary information
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-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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6
- Research group(s)
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-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- International collaboration between UH and the Central South University, China, Hefei University of Technology, China, the University of Oulu, Finland and the National University of Defence Technology, China. Funding was provided by the National Natural Science Foundation of China (Grants 51704089 and 61701157), the China Postdoctoral Science Foundation (Grant 2017M621996), and by the Fundamental Research Funds of the Central Universities of China (Grant JZ2018YYPY0296). Comprehensive experiments were conducted on an open texture database and an actual defect database demonstrating the important application for this research in automatic optical inspection instruments of steel strip manufacturing in steel industries.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -