49 citations · 59 across the 6 of their papers we have counts for
3 papers · 1 filter
Assessing Systematic Weaknesses of DNNs using Counterfactuals
Sujan Sai Gannamaneni, Michael Mock, Maram Akila
With the advancement of DNNs into safety-critical applications, testing approaches for such models have gained more attention. A current direction is the search for and identificat…
Using ScrutinAI for Visual Inspection of DNN Performance in a Medical Use Case
Rebekka Görge, Elena Haedecke, Michael Mock
Our Visual Analytics (VA) tool ScrutinAI supports human analysts to investigate interactively model performanceand data sets. Model performance depends on labeling quality to a lar…
Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety
Sebastian Houben, Stephanie Abrecht, Maram Akila +38
The use of deep neural networks (DNNs) in safety-critical applications like mobile health and autonomous driving is challenging due to numerous model-inherent shortcomings. These s…