Publication2020
Detection and Classification of Crop Diseases from Its Leaves Using Image Processing
The record
- Type
- Publication
- Date
- 1 January 2020
- Level
- National
- Journal
- Smart Innovation Systems and Technologies
- Volume
- 159
- Pages
- 215-228
- Published
- 1 January 2020
- DOI
- 10.1007/978-981-13-9282-5_20
- Scopus ID
- 85075748508
- ISSN
- 21903018
- Authors
- 3
- 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
2.2 End all forms of malnutrition, including stunting and wasting in children under five
Image processing and machine learning detect rice crop diseases with k-means clustering achieving 80.6% accuracy with management feedback to farmers.
- 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
9.2 Promote inclusive and sustainable industrialization and raise industry’s share of employment and GDP
Agricultural technology incorporating computer vision and data mining for crop yield optimization and disease prevention.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-2.1 Agriculture and the rural economy
Agricultural productivity improvement through AI-enabled crop disease detection and farmer advisory systems.
- 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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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. “Detection and Classification of Crop Diseases from Its Leaves Using Image Processing”. Kortex.