89 citations · 354 across the 44 of their papers we have counts for
12 papers · 1 filter
Navigating the Synthetic Realm: Harnessing Diffusion-based Models for Laparoscopic Text-to-Image Generation
Simeon Allmendinger, Patrick Hemmer, Moritz Queisner +5
Recent advances in synthetic imaging open up opportunities for obtaining additional data in the field of surgical imaging. This data can provide reliable supplements supporting sur…
Redefining the Laparoscopic Spatial Sense: AI-based Intra- and Postoperative Measurement from Stereoimages
Leopold Müller, Patrick Hemmer, Moritz Queisner +5
A significant challenge in image-guided surgery is the accurate measurement task of relevant structures such as vessel segments, resection margins, or bowel lengths. While this tas…
Towards Effective Human-AI Decision-Making: The Role of Human Learning in Appropriate Reliance on AI Advice
Max Schemmer, Andrea Bartos, Philipp Spitzer +4
The true potential of human-AI collaboration lies in exploiting the complementary capabilities of humans and AI to achieve a joint performance superior to that of the individual AI…
AB2CD: AI for Building Climate Damage Classification and Detection
Maximilian Nitsche, S. Karthik Mukkavilli, Niklas Kühl +1
We explore the implementation of deep learning techniques for precise building damage assessment in the context of natural hazards, utilizing remote sensing data. The xBD dataset,…
The Impact of Imperfect XAI on Human-AI Decision-Making
Katelyn Morrison, Philipp Spitzer, Violet Turri +3
Explainability techniques are rapidly being developed to improve human-AI decision-making across various cooperative work settings. Consequently, previous research has evaluated ho…
Conceptualizing A Multi-Sided Platform For Cloud Computing Resource Trading
Franziska Haller, Max Schemmer, Niklas Kühl +1
Cost-effective and responsible use of cloud computing resources (CCR) is on the business agenda of many companies. Despite this strategic goal, two geopolitical strategy decisions…
On the Perception of Difficulty: Differences between Humans and AI
Philipp Spitzer, Joshua Holstein, Michael Vössing +1
With the increased adoption of artificial intelligence (AI) in industry and society, effective human-AI interaction systems are becoming increasingly important. A central challenge…
Learning to Defer with Limited Expert Predictions
Patrick Hemmer, Lukas Thede, Michael Vössing +2
Recent research suggests that combining AI models with a human expert can exceed the performance of either alone. The combination of their capabilities is often realized by learnin…
Parameter-free shape optimization: various shape updates for engineering applications
Lars Radtke, Georgios Bletsos, Niklas Kühl +4
In the last decade, parameter-free approaches to shape optimization problems have matured to a state where they provide a versatile tool for complex engineering applications. Howev…
An Incremental Singular Value Decomposition Approach for Large-Scale Spatially Parallel & Distributed but Temporally Serial Data -- Applied to Technical Flows
Niklas Kühl, Hendrik Fischer, Michael Hinze +1
The paper presents a strategy to construct an incremental Singular Value Decomposition (SVD) for time-evolving, spatially 3D discrete data sets. A low memory access procedure for r…
Towards Meaningful Anomaly Detection: The Effect of Counterfactual Explanations on the Investigation of Anomalies in Multivariate Time Series
Max Schemmer, Joshua Holstein, Niklas Bauer +2
Detecting rare events is essential in various fields, e.g., in cyber security or maintenance. Often, human experts are supported by anomaly detection systems as continuously monito…
Toward Foundation Models for Earth Monitoring: Generalizable Deep Learning Models for Natural Hazard Segmentation
Johannes Jakubik, Michal Muszynski, Michael Vössing +2
Climate change results in an increased probability of extreme weather events that put societies and businesses at risk on a global scale. Therefore, near real-time mapping of natur…