18 citations · 33 across the 8 of their papers we have counts for
9 papers
Annotating Ambiguous Images: General Annotation Strategy for High-Quality Data with Real-World Biomedical Validation
Lars Schmarje, Vasco Grossmann, Claudius Zelenka +2
In the field of image classification, existing methods often struggle with biased or ambiguous data, a prevalent issue in real-world scenarios. Current strategies, including semi-s…
Label Smarter, Not Harder: CleverLabel for Faster Annotation of Ambiguous Image Classification with Higher Quality
Lars Schmarje, Vasco Grossmann, Tim Michels +4
High-quality data is crucial for the success of machine learning, but labeling large datasets is often a time-consuming and costly process. While semi-supervised learning can help…
GADformer: A Transparent Transformer Model for Group Anomaly Detection on Trajectories
Andreas Lohrer, Darpan Malik, Claudius Zelenka +1
Group Anomaly Detection (GAD) identifies unusual pattern in groups where individual members might not be anomalous. This task is of major importance across multiple disciplines, in…
Automated Classification of Nanoparticles with Various Ultrastructures and Sizes
Claudius Zelenka, Marius Kamp, Kolja Strohm +4
Accurately measuring the size, morphology, and structure of nanoparticles is very important, because they are strongly dependent on their properties for many applications. In this…
Is one annotation enough? A data-centric image classification benchmark for noisy and ambiguous label estimation
Lars Schmarje, Vasco Grossmann, Claudius Zelenka +8
High-quality data is necessary for modern machine learning. However, the acquisition of such data is difficult due to noisy and ambiguous annotations of humans. The aggregation of…
Learning Stixel-based Instance Segmentation
Monty Santarossa, Lukas Schneider, Claudius Zelenka +3
Stixels have been successfully applied to a wide range of vision tasks in autonomous driving, recently including instance segmentation. However, due to their sparse occurrence in t…
A data-centric approach for improving ambiguous labels with combined semi-supervised classification and clustering
Lars Schmarje, Monty Santarossa, Simon-Martin Schröder +5
Consistently high data quality is essential for the development of novel loss functions and architectures in the field of deep learning. The existence of such data and labels is us…
2D and 3D Segmentation of uncertain local collagen fiber orientations in SHG microscopy
Lars Schmarje, Claudius Zelenka, Ulf Geisen +2
Collagen fiber orientations in bones, visible with Second Harmonic Generation (SHG) microscopy, represent the inner structure and its alteration due to influences like cancer. Whil…
Restoration of Images with Wavefront Aberrations
Claudius Zelenka, Reinhard Koch
This contribution deals with image restoration in optical systems with coherent illumination, which is an important topic in astronomy, coherent microscopy and radar imaging. Such…