Publication2022
Rice Yield Estimation Using Deep Learning
- Zero Hunger
- Industry, Innovation and Infrastructure
- Thriving and Sustainable Economy
The record
- Type
- Publication
- Date
- 1 January 2022
- Level
- National
- Journal
- Communications in Computer and Information Science
- Volume
- 1737 CCIS
- Pages
- 379-388
- Published
- 1 January 2022
- DOI
- 10.1007/978-3-031-23233-6_28
- Scopus ID
- 85146682365
- ISSN
- 18650929
- Authors
- 3
- Open access
- No
- Citations
- 67
- 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
LSTM deep learning model predicts rice yield supporting food security and sustainable agricultural resource 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
9 Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation
Long short-term memory neural network achieves 0.989 recall rate for crop yield forecasting using regional agricultural data.
- 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. LSTM deep learning model predicts rice yield supporting food security and sustainable agricultural resource management.
- 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. “Rice Yield Estimation Using Deep Learning”. Kortex.
