70 citations · 130 across the 41 of their papers we have counts for
11 papers · 1 filter
Confident Teacher, Confident Student? A Novel User Study Design for Investigating the Didactic Potential of Explanations and their Impact on Uncertainty
Teodor Chiaburu, Frank Haußer, Felix Bießmann
Evaluating the quality of explanations in Explainable Artificial Intelligence (XAI) is to this day a challenging problem, with ongoing debate in the research community. While some…
The Influence of Faulty Labels in Data Sets on Human Pose Estimation
Arnold Schwarz, Levente Hernadi, Felix Bießmann +1
In this study we provide empirical evidence demonstrating that the quality of training data impacts model performance in Human Pose Estimation (HPE). Inaccurate labels in widely us…
Generating Synthetic Satellite Imagery for Rare Objects: An Empirical Comparison of Models and Metrics
Tuong Vy Nguyen, Johannes Hoster, Alexander Glaser +2
Generative deep learning architectures can produce realistic, high-resolution fake imagery -- with potentially drastic societal implications. A key question in this context is: How…
Data-driven Modeling of Combined Sewer Systems for Urban Sustainability: An Empirical Evaluation
Vipin Singh, Tianheng Ling, Teodor Chiaburu +1
Climate change poses complex challenges, with extreme weather events becoming increasingly frequent and difficult to model. Examples include the dynamics of Combined Sewer Systems…
TinyChirp: Bird Song Recognition Using TinyML Models on Low-power Wireless Acoustic Sensors
Zhaolan Huang, Adrien Tousnakhoff, Polina Kozyr +5
Monitoring biodiversity at scale is challenging. Detecting and identifying species in fine grained taxonomies requires highly accurate machine learning (ML) methods. Training such…
Automated Computational Energy Minimization of ML Algorithms using Constrained Bayesian Optimization
Pallavi Mitra, Felix Biessmann
Bayesian optimization (BO) is an efficient framework for optimization of black-box objectives when function evaluations are costly and gradient information is not easily accessible…
Multisensor Data Fusion for Automatized Insect Monitoring (KInsecta)
Martin Tschaikner, Danja Brandt, Henning Schmidt +7
Insect populations are declining globally, making systematic monitoring essential for conservation. Most classical methods involve death traps and counter insect conservation. This…
CoProNN: Concept-based Prototypical Nearest Neighbors for Explaining Vision Models
Teodor Chiaburu, Frank Haußer, Felix Bießmann
Mounting evidence in explainability for artificial intelligence (XAI) research suggests that good explanations should be tailored to individual tasks and should relate to concepts…
Generating Synthetic Satellite Imagery With Deep-Learning Text-to-Image Models -- Technical Challenges and Implications for Monitoring and Verification
Tuong Vy Nguyen, Alexander Glaser, Felix Biessmann
Novel deep-learning (DL) architectures have reached a level where they can generate digital media, including photorealistic images, that are difficult to distinguish from real data…
Using Game Engines and Machine Learning to Create Synthetic Satellite Imagery for a Tabletop Verification Exercise
Johannes Hoster, Sara Al-Sayed, Felix Biessmann +4
Satellite imagery is regarded as a great opportunity for citizen-based monitoring of activities of interest. Relevant imagery may however not be available at sufficiently high reso…
Interpretable Time Series Models for Wastewater Modeling in Combined Sewer Overflows
Teodor Chiaburu, Felix Biessmann
Climate change poses increasingly complex challenges to our society. Extreme weather events such as floods, wild fires or droughts are becoming more frequent, spontaneous and diffi…