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Driving up Inference Energy on SNNs: Per-Sample and Universal Sponge Attacks
Spyridon Raptis, Haralampos-G. Stratigopoulos
Spiking Neural Networks (SNNs) communicate through sparse binary spike events rather than dense activations, enabling energy-efficient inference on neuromorphic hardware and motiva…
A Heterogeneous Neural Network Accelerator for End-to-End Multitask RF Signal Recognition
Zhifan Song, Haralampos-G. Stratigopoulos, Hassan Aboushady
This paper presents a heterogeneous neural network accelerator for multi-task RF signal recognition, supporting automatic modulation recognition (AMR), hardware-Trojan covert chann…
Edge-Efficient Transformer for End-to-End RF Spectrum Monitoring
Zhifan Song, Haralampos-G. Stratigopoulos, Hassan Aboushady
We present E-SpecFormer (Edge Spectrum monitoring Transformer) for end-to-end automatic modulation and covert channel (CC) recognition. We introduce LiTAN (Linear Tanh Attention Ne…