Publication2022
ILCAN: A New Vision Attention-Based Late Blight Disease Localization and Classification
The record
- Type
- Publication
- Date
- 1 February 2022
- Level
- International — held abroad
- Journal
- Arabian Journal for Science and Engineering
- Volume
- 47
- Issue
- 2
- Pages
- 2305-2314
- Published
- 1 February 2022
- DOI
- 10.1007/s13369-021-06201-6
- Scopus ID
- 85115625165
- ISSN
- 2193567X
- Authors
- 3
- Open access
- No
- Citations
- 6
- International co-authorship
- Yes
- Co-author countries
- FR, IN, SA
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 End hunger, achieve food security and improved nutrition and promote sustainable agriculture
Vision attention-based deep learning model ILCAN achieves 98.99% accuracy in early detection and localization of late blight crop disease in PlantVillage dataset.
- 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
Convolutional neural network research with visual attention mechanisms advances AI and deep learning research capacity for agricultural applications.
- 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
17.6 Enhance North-South, South-South and triangular cooperation on science, technology and innovation, and knowledge sharing
Structural signal: co-authorship outside India.
- Rule-derived
- Emitted by a deterministic rule from structural signals rather than judged from the record’s text. The rule carries a version, so rule-derived and judged labels stay separable.
- Produced by
- sdg17-structural-v1, under kortex-publication-v1
Viksit Bharat @2047
vb-2.1 Agriculture and the rural economy
AI-enabled crop disease detection prevents yield losses and supports food security in agriculture.
- 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.
Evidence
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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. “ILCAN: A New Vision Attention-Based Late Blight Disease Localization and Classification”. Kortex.