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Detektion, Quantifikation und Mitigation von Robustheitsanfälligkeiten in Tiefen Neuronalen Netzen.

. University of Erlangen-Nuremberg, Germany, (2023)

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CLIP: Cheap Lipschitz Training of Neural Networks., , , , and . SSVM, volume 12679 of Lecture Notes in Computer Science, page 307-319. Springer, (2021)Detektion, Quantifikation und Mitigation von Robustheitsanfälligkeiten in Tiefen Neuronalen Netzen.. University of Erlangen-Nuremberg, Germany, (2023)Artificial intelligence trend analysis on healthcare podcasts using topic modeling and sentiment analysis: a data-driven approach., , , , and . Evol. Intell., 17 (4): 2145-2166 (August 2024)System Design for a Data-Driven and Explainable Customer Sentiment Monitor Using IoT and Enterprise Data., , , , , , , , , and 1 other author(s). IEEE Access, (2021)Exploring misclassifications of robust neural networks to enhance adversarial attacks., , , , and . Appl. Intell., 53 (17): 19843-19859 (September 2023)Just a Matter of Scale? Reevaluating Scale Equivariance in Convolutional Neural Networks., , , , , , and . IJCNN, page 1-8. IEEE, (2023)Dynamically Sampled Nonlocal Gradients for Stronger Adversarial Attacks., , , , , , and . IJCNN, page 1-8. IEEE, (2021)A Unified Approach Towards Active Learning and Out-of-Distribution Detection., , , and . CoRR, (2024)Caption-Driven Explorations: Aligning Image and Text Embeddings through Human-Inspired Foveated Vision., , , , , , and . CoRR, (2024)Contrastive Language-Image Pretrained Models are Zero-Shot Human Scanpath Predictors., , , , , , and . CoRR, (2023)