Publication2025
Two-Dimensional Multi-Deep CNNs for Accurate and Robust Software Defect Detection: A Performance-Driven Approach
- Industry, Innovation and Infrastructure
- Partnerships for the Goals
- Innovation, Science and Technology
The record
- Type
- Publication
- Date
- 1 January 2025
- Level
- International — held abroad
- Journal
- Esic 2025 5th International Conference on Emerging Systems and Intelligent Computing Proceedings
- Pages
- 734-739
- Published
- 1 January 2025
- DOI
- 10.1109/esic64052.2025.10962737
- Scopus ID
- 105004554262
- Authors
- 4
- Open access
- No
- Citations
- 19
- International co-authorship
- Yes
- Co-author countries
- IN, US
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
Multi-deep CNN with crow search optimization detects software defects in complex systems using Apache Active MQ dataset achieving robust classification.
- 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
17.6 Enhance North-South, South-South and triangular cooperation on science, technology and innovation, and knowledge sharing
Structural signal: co-authorship outside India.
- Rule-derived
- Emitted by a deterministic rule from structural signals rather than judged from the record’s text. The rule carries a version, so rule-derived and judged labels stay separable.
- Produced by
- sdg17-structural-v1, under kortex-publication-v1
Viksit Bharat @2047
vb-3 Innovation, Science and Technology
Derived through the seeded SDG-to-Viksit-Bharat crosswalk from the primary SDG 9 label. Multi-deep CNN with crow search optimization detects software defects in complex systems using Apache Active MQ dataset achieving robust classification.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
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- 1
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Citing this record
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KIIT Deemed to be University. “Two-Dimensional Multi-Deep CNNs for Accurate and Robust Software Defect Detection: A Performance-Driven Approach”. Kortex.