Publication2026
IndiSegNet: Real-time semantic segmentation for unstructured road scenes in intelligent transportation systems
- Industry, Innovation and Infrastructure
- Sustainable Cities and Communities
- Partnerships for the Goals
- Thriving and Sustainable Economy
The record
- Type
- Publication
- Date
- 1 March 2026
- Level
- International — held abroad
- Journal
- Intelligent Systems with Applications
- Volume
- 29
- Published
- 1 March 2026
- DOI
- 10.1016/j.iswa.2026.200629
- Scopus ID
- 105028524216
- ISSN
- 26673053
- Authors
- 5
- Open access
- Yes
- Citations
- 2
- International co-authorship
- Yes
- Co-author countries
- GB, 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
11.2 Provide access to safe, affordable, accessible and sustainable transport systems for all
Deep learning architecture for real-time semantic segmentation in unstructured Indian traffic conditions enabling autonomous vehicle deployment in developing regions.
- 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
9 Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation
Transportation technology innovation addressing infrastructure challenges in emerging markets.
- Moderate confidence
- The alignment is plausible and defensible but rests on an assumption a reasonable reviewer could decline. Published, and surfaced in the review queue for a human to confirm or override.
- 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-2 Thriving and Sustainable Economy
Derived through the seeded SDG-to-Viksit-Bharat crosswalk from the primary SDG 11 label. Deep learning architecture for real-time semantic segmentation in unstructured Indian traffic conditions enabling autonomous vehicle deployment in developing regions.
- 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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Provenance
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- Source rows resolved into this record
- 1
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Citing this record
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KIIT Deemed to be University. “IndiSegNet: Real-time semantic segmentation for unstructured road scenes in intelligent transportation systems”. Kortex.