Dominik Drees

17 papers Journal 12Unranked 4
YearRankTypeTitle / Venue / Authors
2025 J jnl
Activation Functions in Non-Negative Neural Networks.
IEEE Access
Marlon Becker, Dominik Drees, Frank Brückerhoff-Plückelmann, Carsten Schuck, Wolfram H. P. Pernice, Benjamin Risse
2025 J jnl
Palace: A Library for Interactive GPU-Accelerated Large Tensor Processing and Visualization.
CoRR
Dominik Drees, Benjamin Risse
2024 — conf
S-ROPE: Spectral Frame Representation of Periodic Events.
ECCV Workshops (24)
Luis Garcia Rodriguez, Jonas Konrad, Dominik Drees, Benjamin Risse
2022 — conf
A Bhattacharyya Coefficient-Based Framework for Noise Model-Aware Random Walker Image Segmentation.
GCPR
Dominik Drees, Florian Eilers, Ang Bian, Xiaoyi Jiang
2022 J jnl
A Bhattacharyya Coefficient-Based Framework for Noise Model-Aware Random Walker Image Segmentation.
CoRR
Dominik Drees, Florian Eilers, Ang Bian, Xiaoyi Jiang
2022 — —
Efficient Out-of-Core methods for biomedical volume processing and analysis.
Dominik Drees
2022 J jnl
Hierarchical Random Walker Segmentation for Large Volumetric Biomedical Images.
IEEE Trans. Image Process.
Dominik Drees, Florian Eilers, Xiaoyi Jiang
2022 J jnl
Voreen - An Open-source Framework for Interactive Visualization and Processing of Large Volume Data.
CoRR
Dominik Drees, Simon Leistikow, Xiaoyi Jiang, Lars Linsen
2021 J jnl
A Streaming Volumetric Image Generation Framework for Development and Evaluation of Out-of-Core Methods.
CoRR
Dominik Drees, Xiaoyi Jiang
2021 J jnl
Hierarchical Random Walker Segmentation for Large Volumetric Biomedical Data.
CoRR
Dominik Drees, Xiaoyi Jiang
2021 J jnl
Scalable Robust Graph and Feature Extraction for Arbitrary Vessel Networks in Large Volumetric Datasets.
CoRR
Dominik Drees, Aaron Scherzinger, René Hägerling, Friedemann Kiefer, Xiaoyi Jiang
2021 J jnl
Scalable robust graph and feature extraction for arbitrary vessel networks in large volumetric datasets.
BMC Bioinform.
Dominik Drees, Aaron Scherzinger, René Hägerling, Friedemann Kiefer, Xiaoyi Jiang
2019 J jnl
GERoMe-a Method for Evaluating Stability of Graph Extraction Algorithms Without Ground Truth.
IEEE Access
Dominik Drees, Aaron Scherzinger, Xiaoyi Jiang
2018 J jnl
Barista - a Graphical Tool for Designing and Training Deep Neural Networks.
CoRR
Sören Klemm, Aaron Scherzinger, Dominik Drees, Xiaoyi Jiang
2017 — conf
GERoMe - A Novel Graph Extraction Robustness Measure.
GbRPR
Dominik Drees, Aaron Scherzinger, Xiaoyi Jiang
2017 J jnl
Interactive Exploration of Cosmological Dark-Matter Simulation Data.
IEEE Computer Graphics and Applications
Aaron Scherzinger, Tobias J. Brix, Dominik Drees, Andreas Völker, Kiril Radkov, Niko Santalidis, Alexander Fieguth, Klaus H. Hinrichs
2015 — conf
Visualize the universe: Interactive exploration of cosmological dark matter simulation data.
SciVis
Aaron Scherzinger, Tobias J. Brix, Dominik Drees, Andreas Völker, Kiril Radkov, Niko Santalidis, Alexander Fieguth, Klaus H. Hinrichs