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InfoResearchPeer-reviewed
A Multigranularity Embedding Guided Open-Set Recognition for Fine-Grained Specific Emitter Identification
- Published
- Record updated
Summary
Researchers propose MGEGOR, a prototype-based open-set specific emitter identification framework inspired by generalized zero-shot learning. It combines contrastive representation learning, prototype-based embedding and multiscale feature extraction with attention alignment to jointly model known and unknown emitters. The method reports significant accuracy gains over state-of-the-art baselines on the LoRa_RFFI dataset and measured datasets.