2 citations · 3 across the 6 of their papers we have counts for
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cs.CV2024
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…
cs.CV2024
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…
cs.CV2024★ 2 cited
ENSTRECT: A Stage-based Approach to 2.5D Structural Damage Detection
Christian Benz, Volker Rodehorst
To effectively assess structural damage, it is essential to localize the instances of damage in the physical world of a civil structure. ENSTRECT is a stage-based approach designed…