Search Results for author: Martin Nocker

Found 2 papers, 1 papers with code

On the Effect of Adversarial Training Against Invariance-based Adversarial Examples

no code implementations16 Feb 2023 Roland Rauter, Martin Nocker, Florian Merkle, Pascal Schöttle

Another type of adversarial examples are invariance-based adversarial examples, where the images are semantically modified such that the predicted class of the model does not change, but the class that is determined by humans does.

HE-MAN -- Homomorphically Encrypted MAchine learning with oNnx models

1 code implementation16 Feb 2023 Martin Nocker, David Drexel, Michael Rader, Alessio Montuoro, Pascal Schöttle

Fully homomorphic encryption (FHE) is a promising technique to enable individuals using ML services without giving up privacy and protecting the ML model of service providers at the same time.

Face Recognition Privacy Preserving

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