Publication2023
Medical Image Processing Using CNN
- Good Health and Well-being
- Industry, Innovation and Infrastructure
- Empowered Indians
The record
- Type
- Publication
- Date
- 1 January 2023
- Level
- National
- Journal
- 2023 IEEE 3rd International Conference on Applied Electromagnetics Signal Processing and Communication Aespc 2023
- Published
- 1 January 2023
- DOI
- 10.1109/aespc59761.2023.10390095
- Scopus ID
- 85184848779
- Authors
- 5
- Open access
- No
- Citations
- 2
- 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
3.4 Reduce premature mortality from non-communicable diseases and promote mental health and well-being
Convolutional neural network model achieves 98.13% accuracy for automated malaria parasite detection from blood samples, improving diagnostic speed and healthcare delivery.
- 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
Deep learning research on medical image processing with CNN demonstrates advanced computational and artificial intelligence methodologies.
- 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. Convolutional neural network model achieves 98.13% accuracy for automated malaria parasite detection from blood samples, improving diagnostic speed and healthcare delivery.
- 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. “Medical Image Processing Using CNN”. Kortex.