Publication2025
Industrial Surface Defect Detection Using Machine Leaning Approach
The record
- Type
- Publication
- Date
- 1 January 2025
- Level
- National
- Journal
- 2025 7th International Conference on Information Systems and Computer Networks Iscon 2025
- Published
- 1 January 2025
- DOI
- 10.1109/iscon65210.2025.11341674
- Scopus ID
- 105033342757
- Authors
- 6
- Open access
- No
- Citations
- 0
- International co-authorship
- No
- Co-author countries
- IN
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending
Computer vision with DINO V2 feature extraction and SVM classifier achieves 0.827 F1-score for industrial surface defect detection, advancing manufacturing quality control.
- High confidence
- The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
12 Ensure sustainable consumption and production patterns
Automated defect detection reduces production waste and improves resource efficiency in manufacturing processes.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-2.2 Industry and manufacturing
Industrial quality control innovation supports manufacturing efficiency and responsible production.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
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- 1
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Citing this record
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KIIT Deemed to be University. “Industrial Surface Defect Detection Using Machine Leaning Approach”. Kortex.