Synthetic data augmentation for surface defect detection and classification using deep learning
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Steel surface defects have inter-class similarity and intra-class diversity.
“First, there is an inter-class similarity and intra-class diversity of defects on the steel surface [2].”
From Steel Surface Defect Recognition: A Survey (2022) · cites this paper as [2]
The citation lists haven’t been fetched yet
References 52 · Cited by 302
- Authors
- Jain, S., Seth, G., Paruthi, A., Soni, U., & Kumar, G.
- Affiliations
- Netaji Subhas University of Technology (IN)
- Delhi Technological University (IN)
- Corresponding author
- Soni, Umang
- Venue
- Journal of Intelligent Manufacturing
- Published
- 2020-11-18
- Volume
- 33
- Issue
- 4
- Pages
- 1007-1020
- ISSN
- 0956-5515 (ISSN-L)
- 1572-8145
- OpenAlex
- W3100487172
- Cited by
- 302
- References
- 52
- Citations by year
- 2026: 50 · 2025: 87 · 2024: 78 · 2023: 48 · 2022: 30 · 2021: 9
- FWCI
- 13.87
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Intelligent Manufacturing (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Industrial Vision Systems and Defect Detection
- Physical Sciences › Engineering › Civil and Structural Engineering › Infrastructure Maintenance and Monitoring
- Physical Sciences › Engineering › Mechanical Engineering › Non-Destructive Testing Techniques
- Keywords
- synthetic data augmentation, surface defect detection, surface defect classification, generative adversarial networks, convolutional neural networks, hot-rolled strip, manufacturing inspection, disentangled representations, limited labeled data
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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