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Open access Sep 2026

Attention-guided deep embedding framework for heterogeneous vehicular clustering and cluster head selection in dynamic VANETs

The paper proposes an attention-guided deep embedding framework that jointly models long-range structural interactions and heterogeneous vehicular influence, rather than restricting learning to immediate neighbours, and provides a robust solution for stable V2V communication.

Ajaybeer Kaur, M. Ali, Parveen Kumar et al. · 0 citations

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