Publication2021
Dimensionality reduction and evaluation in hyperspectral images using LSTM models
The record
- Type
- Publication
- Date
- 5 August 2021
- Level
- National
- Journal
- 2nd International Conference on Range Technology Icort 2021
- Published
- 5 August 2021
- DOI
- 10.1109/icort52730.2021.9582080
- Scopus ID
- 85118988194
- 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
9 Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation
Long Short Term Memory networks for hyperspectral imaging classification enable deep learning analysis of earth observation remote sensing data.
- 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
Viksit Bharat @2047
vb-3.1 Research and development
LSTM-based dimensionality reduction advances remote sensing research capacity for earth surface characterization through deep learning methodology.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
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- 1
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Citing this record
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KIIT Deemed to be University. “Dimensionality reduction and evaluation in hyperspectral images using LSTM models”. Kortex.