Search Results - "Raab, René"

Exploring misclassifications of robust neural networks to enhance adversarial attacks by Schwinn, Leo, Raab, René, Nguyen, An, Zanca, Dario, Eskofier, Bjoern

“…Progress in making neural networks more robust against adversarial attacks is mostly marginal, despite the great efforts of the research community. Moreover,…”
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Automated long-term monitoring of stereotypical movement in polar bears under human care using machine learning by Zuerl, Matthias, Stoll, Philip, Brehm, Ingrid, Sueskind, Jonas, Raab, René, Petermann, Jan, Zanca, Dario, Simon, Ralph, von Fersen, Lorenzo, Eskofier, Bjoern

“…The welfare of animals under human care is often assessed by observing behaviours indicative of stress or discomfort, such as stereotypical behaviour (SB),…”
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Automated Video-Based Analysis Framework for Behavior Monitoring of Individual Animals in Zoos Using Deep Learning-A Study on Polar Bears by Zuerl, Matthias, Stoll, Philip, Brehm, Ingrid, Raab, René, Zanca, Dario, Kabri, Samira, Happold, Johanna, Nille, Heiko, Prechtel, Katharina, Wuensch, Sophie, Krause, Marie, Seegerer, Stefan, von Fersen, Lorenzo, Eskofier, Bjoern

“…The monitoring of animals under human care is a crucial tool for biologists and zookeepers to keep track of the animals' physical and psychological health…”
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Federated electronic health records for the European Health Data Space by Raab, René, Küderle, Arne, Zakreuskaya, Anastasiya, Stern, Ariel D, Klucken, Jochen, Kaissis, Georgios, Rueckert, Daniel, Boll, Susanne, Eils, Roland, Wagener, Harald, Eskofier, Bjoern M

“…The European Commission's draft for the European Health Data Space (EHDS) aims to empower citizens to access their personal health data and share it with…”
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Aligning Federated Learning with Existing Trust Structures in Health Care Systems by Abdullahi, Imrana Yari, Raab, René, Küderle, Arne, Eskofier, Björn

“…Patient-centered health care information systems (PHSs) on peer-to-peer (P2P) networks (e.g., decentralized personal health records) enable storing data…”
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CLIP: Cheap Lipschitz Training of Neural Networks by Bungert, Leon, Raab, René, Roith, Tim, Schwinn, Leo, Tenbrinck, Daniel

“…International Conference on Scale Space and Variational Methods in Computer Vision, 307-319, 2021 Despite the large success of deep neural networks (DNN) in…”
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Towards Rapid and Robust Adversarial Training with One-Step Attacks by Schwinn, Leo, Raab, René, Eskofier, Björn

“…Adversarial training is the most successful empirical method for increasing the robustness of neural networks against adversarial attacks. However, the most…”
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Exploring Misclassifications of Robust Neural Networks to Enhance Adversarial Attacks by Schwinn, Leo, Raab, René, Nguyen, An, Zanca, Dario, Eskofier, Bjoern

“…Progress in making neural networks more robust against adversarial attacks is mostly marginal, despite the great efforts of the research community. Moreover,…”
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Recombinant Reporter Phage rTUN1:: nLuc Enables Rapid Detection and Real-Time Antibiotic Susceptibility Testing of Klebsiella pneumoniae K64 Strains by Braun, Peter, Raab, Rene, Bugert, Joachim J, Braun, Simone

“…The emergence of multi-drug-resistant ( ) strains constitutes an enormous threat to global health as multi-drug resistance-associated treatment failure causes…”
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Improving Robustness against Real-World and Worst-Case Distribution Shifts through Decision Region Quantification by Schwinn, Leo, Bungert, Leon, Nguyen, An, Raab, René, Pulsmeyer, Falk, Precup, Doina, Eskofier, Björn, Zanca, Dario

“…The reliability of neural networks is essential for their use in safety-critical applications. Existing approaches generally aim at improving the robustness of…”
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Identifying Untrustworthy Predictions in Neural Networks by Geometric Gradient Analysis by Schwinn, Leo, Nguyen, An, Raab, René, Bungert, Leon, Tenbrinck, Daniel, Zanca, Dario, Burger, Martin, Eskofier, Bjoern

“…The susceptibility of deep neural networks to untrustworthy predictions, including out-of-distribution (OOD) data and adversarial examples, still prevent their…”
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Dynamically Sampled Nonlocal Gradients for Stronger Adversarial Attacks by Schwinn, Leo, Nguyen, An, Raab, René, Zanca, Dario, Eskofier, Bjoern, Tenbrinck, Daniel, Burger, Martin

“…The vulnerability of deep neural networks to small and even imperceptible perturbations has become a central topic in deep learning research. Although several…”
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Dynamically Sampled Nonlocal Gradients for Stronger Adversarial Attacks by Schwinn, Leo, Nguyen, An, Raab, Rene, Zanca, Dario, Eskofier, Bjoern M., Tenbrinck, Daniel, Burger, Martin

“…The vulnerability of deep neural networks to small and even imperceptible perturbations has become a central topic in deep learning research. Although several…”
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