Publication2021
Glaucoma Detection Using Morphological Filters and GLCM Features
- Good Health and Well-being
- Empowered Indians
The record
- Type
- Publication
- Date
- 1 January 2021
- Level
- National
- Journal
- Smart Innovation Systems and Technologies
- Volume
- 224
- Pages
- 627-635
- Published
- 1 January 2021
- DOI
- 10.1007/978-981-16-1502-3_62
- Scopus ID
- 85112677470
- ISSN
- 21903018
- Authors
- 5
- Open access
- No
- Citations
- 3
- 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
Morphological filter and gray level co-occurrence matrix features with support vector machine achieve 93.7% accuracy in automated glaucoma detection.
- 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
Viksit Bharat @2047
vb-1 Empowered Indians
Derived through the seeded SDG-to-Viksit-Bharat crosswalk from the primary SDG 3 label. Morphological filter and gray level co-occurrence matrix features with support vector machine achieve 93.7% accuracy in automated glaucoma detection.
- 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. “Glaucoma Detection Using Morphological Filters and GLCM Features”. Kortex.