Publication2024
Neuromorphic computing for machine learning: An overview
- Good Health and Well-being
- Industry, Innovation and Infrastructure
- Empowered Indians
The record
- Type
- Publication
- Date
- 1 January 2024
- Level
- National
- Journal
- Primer to Neuromorphic Computing
- Pages
- 1-20
- Published
- 1 January 2024
- DOI
- 10.1016/b978-0-443-21480-6.00013-4
- Scopus ID
- 105001753009
- Authors
- 4
- Open access
- No
- Citations
- 4
- 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
Neuromorphic computing system using spiking neural networks to predict cardiovascular disease survival rates with high diagnostic accuracy.
- 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
9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending
Novel computational architecture advancing research capacity in neural network and machine learning technology.
- 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
Viksit Bharat @2047
vb-1 Empowered Indians
Derived through the seeded SDG-to-Viksit-Bharat crosswalk from the primary SDG 3 label. Neuromorphic computing system using spiking neural networks to predict cardiovascular disease survival rates with high diagnostic accuracy.
- 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. “Neuromorphic computing for machine learning: An overview”. Kortex.