CAIC-Net: Robust Radio Modulation Classification via Unified Dynamic Cross-Attention and Cross-Signal-to-Noise Ratio Contrastive Learning.
- DOI
- 10.3390/s26030756
- Published
- 2026 Jan 23
- Container
- Sensors (Basel, Switzerland)
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3390/s26030756,
title = {CAIC-Net: Robust Radio Modulation Classification via Unified Dynamic Cross-Attention and Cross-Signal-to-Noise Ratio Contrastive Learning.},
author = {Wu T and Zhu Q and Mao R and Hu C and Wei S},
year = {2026},
journal = {Sensors (Basel, Switzerland)},
doi = {10.3390/s26030756},
url = {https://doi.org/10.3390/s26030756}
}RIS
TY - JOUR TI - CAIC-Net: Robust Radio Modulation Classification via Unified Dynamic Cross-Attention and Cross-Signal-to-Noise Ratio Contrastive Learning. AU - Wu T AU - Zhu Q AU - Mao R AU - Hu C AU - Wei S PY - 2026 JO - Sensors (Basel, Switzerland) DO - 10.3390/s26030756 UR - https://doi.org/10.3390/s26030756 ER -
APA
T, W., Q, Z., R, M., C, H., & S, W. (2026). CAIC-Net: Robust Radio Modulation Classification via Unified Dynamic Cross-Attention and Cross-Signal-to-Noise Ratio Contrastive Learning.. Sensors (Basel, Switzerland). https://doi.org/10.3390/s26030756
Source records
- pubmed · retrieved 2026-09-25T07:17:33.527Z