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by IQAC KIITKIIT Deemed to be University — Internal Quality Assurance Cell

Publication2024

Detection And Classification Of Diseases In Rice Crops From Its Leaves By Using Machine Learning Algorithm

The record

Type
Publication
Date
1 January 2024
Level
International — held abroad
Journal
Proceedings 2024 Oits International Conference on Information Technology Ocit 2024
Pages
476-481
Published
1 January 2024
DOI
10.1109/ocit65031.2024.00089
Scopus ID
105004803353
Authors
6
Open access
No
Citations
2
International co-authorship
Yes
Co-author countries
IE, IN, US, VN

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

  1. 2 End hunger, achieve food security and improved nutrition and promote sustainable agriculture

    GoalPrimaryHigh confidenceJudged

    Convolutional neural network for rice crop disease detection and classification from leaf images, directly addressing agricultural pest and disease management.

    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

  2. 9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending

    TargetSecondaryModerate confidenceJudged

    Machine learning methodology applied to agricultural disease diagnosis systems.

    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

  3. 17.6 Enhance North-South, South-South and triangular cooperation on science, technology and innovation, and knowledge sharing

    TargetSecondaryHigh confidenceRule-derivedrule sdg17-structural-v1

    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

  1. vb-2.1 Agriculture and the rural economy

    Sub-themePrimaryHigh confidenceJudged

    Agricultural productivity improved through AI-based disease detection for food security.

    Produced by
    claude-haiku-4-5-20251001, under kortex-publication-v1

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KIIT Deemed to be University. “Detection And Classification Of Diseases In Rice Crops From Its Leaves By Using Machine Learning Algorithm”. Kortex.

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