Publication2025
A Review on Use of Deep Learning and Hyperspectral Data Integration for Early Stage Crop Disease Detection
- Zero Hunger
- Industry, Innovation and Infrastructure
- Thriving and Sustainable Economy
The record
- Type
- Publication
- Date
- 1 January 2025
- Level
- National
- Journal
- 2025 3rd International Conference on Communication Security and Artificial Intelligence Iccsai 2025
- Pages
- 1758-1765
- Published
- 1 January 2025
- DOI
- 10.1109/iccsai64074.2025.11063960
- Scopus ID
- 105012096549
- Authors
- 3
- Open access
- No
- Citations
- 1
- 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 End hunger, achieve food security and improved nutrition and promote sustainable agriculture
Review of deep learning and hyperspectral imaging for crop disease detection enables early identification of plant infections before visible symptoms appear, supporting timely intervention to minimize crop loss and enhance agricultural productivity.
- 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
Integration of CNN, Vision Transformer, and multispectral imaging demonstrates innovation in deep learning methodology and computer vision research for precision agriculture applications.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-2 Thriving and Sustainable Economy
Derived through the seeded SDG-to-Viksit-Bharat crosswalk from the primary SDG 2 label. Review of deep learning and hyperspectral imaging for crop disease detection enables early identification of plant infections before visible symptoms appear, supporting timely intervention to minimize crop loss and enhance agricultural productivity.
- 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. “A Review on Use of Deep Learning and Hyperspectral Data Integration for Early Stage Crop Disease Detection”. Kortex.