Dario Zanca

Exploring Misclassifications of Robust Neural Networks to Enhance Adversarial Attacks

2021 · arXiv (Cornell University)

Progress in making neural networks more robust against adversarial attacks is mostly marginal, despite the great efforts of the research community. Moreover, the robustness evaluation is often imprecise, making it difficult to identify promising approaches. …

FovEx: Human-inspired explanations for vision transformers and convolutional neural networks

2024 · Publication Server of Goethe University Frankfurt am Main (Goethe University Frankfurt)

Explainability in artificial intelligence (XAI) remains a crucial aspect for fostering trust and understanding in machine learning models. Current visual explanation techniques, such as gradient-based or class-activation-based methods, often exhibit a strong dependence on specific …