Publication2022
Advances in Hyperspectral Image Classification Based on Convolutional Neural Networks: A Review
The record
- Type
- Publication
- Date
- 1 January 2022
- Level
- National
- Journal
- CMES Computer Modeling in Engineering and Sciences
- Volume
- 133
- Issue
- 2
- Pages
- 219-250
- Published
- 1 January 2022
- DOI
- 10.32604/cmes.2022.020601
- Scopus ID
- 85135832453
- ISSN
- 15261492
- Authors
- 3
- Open access
- Yes
- Citations
- 59
- 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
9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending
Systematic review of CNN architectures (1D, 2D, 3D, feature fusion) for hyperspectral image classification demonstrates research innovation in deep learning and remote sensing methodology.
- 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-3.2 Digital technology and artificial intelligence
Deep learning and AI methodology review for remote sensing image analysis advances digital technology and artificial intelligence research and development capabilities.
- 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. “Advances in Hyperspectral Image Classification Based on Convolutional Neural Networks: A Review”. Kortex.