Optimizing Hyperspectral Image Classification Through Swin Transformer Integration and CNN Feature Extraction
- DOI
- 10.1007/978-3-031-69986-3_29
- Published
- 2024
- Container
- IFIP Advances in Information and Communication Technology
- Publisher
- Springer Nature Switzerland
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1007/978-3-031-69986-3_29,
title = {Optimizing Hyperspectral Image Classification Through Swin Transformer Integration and CNN Feature Extraction},
author = {Sushil Kumar Janardan and Rekh Ram Janghel},
year = {2024},
journal = {IFIP Advances in Information and Communication Technology},
doi = {10.1007/978-3-031-69986-3_29},
url = {https://doi.org/10.1007/978-3-031-69986-3_29}
}RIS
TY - JOUR TI - Optimizing Hyperspectral Image Classification Through Swin Transformer Integration and CNN Feature Extraction AU - Sushil Kumar Janardan AU - Rekh Ram Janghel PY - 2024 JO - IFIP Advances in Information and Communication Technology DO - 10.1007/978-3-031-69986-3_29 UR - https://doi.org/10.1007/978-3-031-69986-3_29 ER -
APA
Janardan, S. K., & Janghel, R. R. (2024). Optimizing Hyperspectral Image Classification Through Swin Transformer Integration and CNN Feature Extraction. IFIP Advances in Information and Communication Technology. https://doi.org/10.1007/978-3-031-69986-3_29
Source records
- crossref · retrieved 2026-09-25T15:39:45.200Z