Publication2020
Comparison of deep CNN and ResNet for Handwritten Devanagari Character Recognition
The record
- Type
- Publication
- Date
- 5 September 2020
- Level
- National
- Journal
- 2020 IEEE International Conference for Convergence in Engineering Icce 2020 Proceedings
- Pages
- 235-238
- Published
- 5 September 2020
- DOI
- 10.1109/icce50343.2020.9290637
- Scopus ID
- 85099318722
- Authors
- 3
- Open access
- No
- Citations
- 10
- 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
4 Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all
Deep CNN and ResNet performance comparison for Devanagari handwritten character recognition achieves 99% accuracy supporting regional language optical character recognition capability
- 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 Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation
Deep learning model development for script recognition represents artificial intelligence research innovation in natural language processing and pattern recognition
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-1.1 Education and lifelong learning
Devanagari character recognition capability supports education technology and accessibility for regional language learners and educational content digitalization
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
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- 1
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Citing this record
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KIIT Deemed to be University. “Comparison of deep CNN and ResNet for Handwritten Devanagari Character Recognition”. Kortex.