10 papers
Differences in Detection: Explainability Where it Matters
Johannes Theodoridis, Johannes Maucher, Andreas Schilling
We propose Differences in Detection (DnD), an intuitive method to compare two object detection models. Based on the same matching algorithm, it complements the standard metrics of…
Evaluating the Impact of Data Anonymization on Image Retrieval
Marvin Chen, Manuel Eberhardinger, Johannes Maucher
With the growing importance of privacy regulations such as the General Data Protection Regulation, anonymizing visual data is becoming increasingly relevant across institutions. Ho…
Generation of Programmatic Rules for Document Forgery Detection Using Large Language Models
Valentin Schmidberger, Manuel Eberhardinger, Setareh Maghsudi +1
Document forgery poses a growing threat to legal, economic, and governmental processes, requiring increasingly sophisticated verification mechanisms. One approach involves the use…
A Toolbox for Improving Evolutionary Prompt Search
Daniel GrieÃhaber, Maximilian Kimmich, Johannes Maucher +1
Evolutionary prompt optimization has demonstrated effectiveness in refining prompts for LLMs. However, existing approaches lack robust operators and efficient evaluation mechanisms…
ViPro-2: Unsupervised State Estimation via Integrated Dynamics for Guiding Video Prediction
Patrick Takenaka, Johannes Maucher, Marco F. Huber
Predicting future video frames is a challenging task with many downstream applications. Previous work has shown that procedural knowledge enables deep models for complex dynamical…
Anonymization of Documents for Law Enforcement with Machine Learning
Manuel Eberhardinger, Patrick Takenaka, Daniel GrieÃhaber +1
The steadily increasing utilization of data-driven methods and approaches in areas that handle sensitive personal information such as in law enforcement mandates an ever increasing…