Mod-CL uses intra-instance modulation consistency to form positive pairs from temporal signal segments in a tailored contrastive objective, outperforming baselines on RadioML datasets especially in low-label regimes.
Gaf-mae: A self- supervised automatic modulation classification method based on gramian angular field and masked autoencoder
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.SP 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Modulation Consistency-based Contrastive Learning for Self-Supervised Automatic Modulation Classification
Mod-CL uses intra-instance modulation consistency to form positive pairs from temporal signal segments in a tailored contrastive objective, outperforming baselines on RadioML datasets especially in low-label regimes.