1 citations · 1 across the 5 of their papers we have counts for
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KLOS finds Consensus: A Meta-Algorithm for Evaluating Inter-Annotator Agreement in Complex Vision Tasks
David Tschirschwitz, Volker Rodehorst
Progress in object detection benchmarks is stagnating. It is limited not by architectures but by the inability to distinguish model improvements from label noise. To restore trust…
CISOL: An Open and Extensible Dataset for Table Structure Recognition in the Construction Industry
David Tschirschwitz, Volker Rodehorst
Reproducibility and replicability are critical pillars of empirical research, particularly in machine learning, where they depend not only on the availability of models, but also o…
Efficient and Discriminative Image Feature Extraction for Universal Image Retrieval
Morris Florek, David Tschirschwitz, Björn Barz +1
Current image retrieval systems often face domain specificity and generalization issues. This study aims to overcome these limitations by developing a computationally efficient tra…
Label Convergence: Defining an Upper Performance Bound in Object Recognition through Contradictory Annotations
David Tschirschwitz, Volker Rodehorst
Annotation errors are a challenge not only during training of machine learning models, but also during their evaluation. Label variations and inaccuracies in datasets often manifes…
Drawing the Same Bounding Box Twice? Coping Noisy Annotations in Object Detection with Repeated Labels
David Tschirschwitz, Christian Benz, Morris Florek +3
The reliability of supervised machine learning systems depends on the accuracy and availability of ground truth labels. However, the process of human annotation, being prone to err…