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.
U-net: Convo- lutional networks for biomedical image segmentation
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A self-supervised framework using SURE and equivariant constraints produces super-resolved Sentinel-5P images comparable to supervised baselines without HR references and with physically plausible structures validated against EMIT data.
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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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Self-Supervised Super-Resolution for Sentinel-5P Hyperspectral Images
A self-supervised framework using SURE and equivariant constraints produces super-resolved Sentinel-5P images comparable to supervised baselines without HR references and with physically plausible structures validated against EMIT data.