BadSNN injects backdoors into spiking neural networks by adversarially tuning LIF neuron hyperparameters and optimizing triggers, achieving higher attack success than prior data-poisoning methods while remaining robust to common defenses.
Converting static image datasets to spiking neuromorphic datasets using saccades.Frontiers in neuroscience, 9:437, 2015
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MAST with spiking neural networks achieves 93.14% mean accuracy detecting AI-generated videos from 10 unseen generators by exploiting smoother pixel residuals and compact semantic trajectories.
citing papers explorer
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BadSNN: Backdoor Attacks on Spiking Neural Networks via Adversarial Spiking Neuron
BadSNN injects backdoors into spiking neural networks by adversarially tuning LIF neuron hyperparameters and optimizing triggers, achieving higher attack success than prior data-poisoning methods while remaining robust to common defenses.
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Detecting AI-Generated Videos with Spiking Neural Networks
MAST with spiking neural networks achieves 93.14% mean accuracy detecting AI-generated videos from 10 unseen generators by exploiting smoother pixel residuals and compact semantic trajectories.