Publication2025
Tomato Disease Detection using Deep Learning Architecture
The record
- Type
- Publication
- Date
- 1 January 2025
- Level
- National
- Journal
- Icoicc 2025 3rd International Conference on Intelligent and Cloud Computing
- Published
- 1 January 2025
- DOI
- 10.1109/icoicc64033.2025.11052069
- Scopus ID
- 105012102181
- Authors
- 6
- 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
2.3 Double the agricultural productivity and incomes of small-scale food producers
Deep learning system for detecting tomato diseases allows farmers to optimize intervention timing and enhance agricultural productivity directly.
- 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
AI-driven image classification methodology demonstrates innovation in precision agriculture 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-2.1 Agriculture and the rural economy
Automated disease detection in tomato crops strengthens rural agricultural productivity and farmer decision-making.
- 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. “Tomato Disease Detection using Deep Learning Architecture”. Kortex.