321 citations · 420 across the 20 of their papers we have counts for
3 papers · 1 filter
Attack logics, not outputs: Towards efficient robustification of deep neural networks by falsifying concept-based properties
Raik Dankworth, Gesina Schwalbe
Deep neural networks (NNs) for computer vision are vulnerable to adversarial attacks, i.e., miniscule malicious changes to inputs may induce unintuitive outputs. One key approach t…
On Background Bias of Post-Hoc Concept Embeddings in Computer Vision DNNs
Gesina Schwalbe, Georgii Mikriukov, Edgar Heinert +5
The thriving research field of concept-based explainable artificial intelligence (C-XAI) investigates how human-interpretable semantic concepts embed in the latent spaces of deep n…
Benchmarking Vision Foundation Models for Input Monitoring in Autonomous Driving
Mert Keser, Halil Ibrahim Orhan, Niki Amini-Naieni +3
Deep neural networks (DNNs) remain challenged by distribution shifts in complex open-world domains like automated driving (AD): Robustness against yet unknown novel objects (semant…