Publication2026
Improving Accuracy in Emotion-Action Integrated AI Models: A Hybrid Neural-Symbolic Approach
The record
- Type
- Publication
- Date
- 1 January 2026
- Level
- National
- Journal
- 2026 International Conference on Recent Advances in Electrical Electronics Ubiquitous Communication and Computational Intelligence Raeeucci 2026
- Published
- 1 January 2026
- DOI
- 10.1109/raeeucci67649.2026.11504609
- Scopus ID
- 105040841149
- Authors
- 3
- 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
3 Ensure healthy lives and promote well-being for all at all ages
Cross-attention dual-stream emotion-action recognition uses EfficientNet-B4 networks with spatial attention mapping scenes and persons to predict emotions and suggest actions from images.
- 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.
- 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
9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending
Hybrid neural-symbolic emotion recognition architecture combines deep learning with rule-based reasoning enabling interpretable AI for emotion classification on EMOTIC dataset.
- 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.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-3.2 Digital technology and artificial intelligence
Emotion-action AI model integrating dual-stream neural networks with symbolic reasoning demonstrates explainable artificial intelligence for emotion understanding and action mapping.
- 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. “Improving Accuracy in Emotion-Action Integrated AI Models: A Hybrid Neural-Symbolic Approach”. Kortex.