AINeutralarXiv – CS AI · 15h ago6/10
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Geometry-Aware Contrastive Learning for Few-Shot Automatic Modulation Recognition
Researchers propose Dynamic-Consistency Contrastive Learning (DyCo-CL), a machine learning framework that improves automatic modulation recognition in wireless signal processing by combining virtual adversarial augmentation with semantic consistency loss. The method achieves a 6.27% accuracy improvement in few-shot learning scenarios on standard benchmarks, addressing key challenges in self-supervised learning for signal classification.