#spiking neural networks
16 papers · 1 filter
Temporal Poisoning: Clean-Label Backdoors via Event Redistribution in SNNs
Roberto Riaño, Gorka Abad, Stjepan Picek +1
The paper introduces a clean‑label backdoor attack for spiking neural networks that subtly reshapes the timing of events in target‑class training streams, achieving near‑perfect at…
Driving up Inference Energy on SNNs: Per-Sample and Universal Sponge Attacks
Spyridon Raptis, Haralampos-G. Stratigopoulos
The paper demonstrates that spiking neural networks, which are energy‑efficient on neuromorphic hardware, can be targeted by adversarial "sponge" attacks that increase spike activi…
Sequence-SOD: Bio-inspired Sequence-aware Spiking ObjectDetection for Event Cameras
Katharina Bendig, René Schuster, Didier Stricker
The paper presents Sequence-SOD, a spiking neural network object detector for event cameras that processes continuous sequences of events while preserving membrane potentials, lead…
The Sparsity Ceiling: Where Spiking Networks Can and Cannot Trade Activity for Energy
Zeyu Wang
The paper studies how much spiking neural networks can lower their firing activity without losing performance, showing that the achievable sparsity depends on the task and architec…
Scalable Training of Continuous-Time Spiking Neural Networks with Differentiable Spike-Time Discretization
Yusuke Sakemi, Tomoya Takeuchi, Takeo Hosomi +1
The paper proposes a memory‑efficient training method for continuous‑time spiking neural networks by discretizing spike times into differentiable weighted events, enabling deep SNN…
RainDancer: RGB-Event Video Deraining with Rain-Oriented Spiking Dynamics
Kui Jiang, Runzhe Li, Zhaocheng Yu +3
RainDancer is a video deraining framework that jointly processes RGB frames and event-camera data, first decomposing rain and background within each modality and then fusing them u…