Daniel Siegismund

According to our database, Daniel Siegismund authored at least 6 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Revisiting Deep Archetypal Analysis for Phenotype Discovery in High Content Imaging.

Mario Wieser, Daniel Siegismund, Stephan Steigele

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2025

2024

PCIM: Learning Pixel Attributions via Pixel-wise Channel Isolation Mixing in High Content Imaging.

Daniel Siegismund, Mario Wieser, Stephan Heyse, Stephan Steigele

CoRR, 2024

2023

Learning Channel Importance for High Content Imaging with Interpretable Deep Input Channel Mixing.

Daniel Siegismund, Mario Wieser, Stephan Heyse, Stephan Steigele

Proceedings of the Pattern Recognition - 45th DAGM German Conference, 2023

2022

Vision Transformers Show Improved Robustness in High-Content Image Analysis.

Mario Wieser, Daniel Siegismund, Stephan Heyse, Stephan Steigele

Proceedings of the 9th Swiss Conference on Data Science, 2022

Self-Supervised Representation Learning for High-Content Screening.

Daniel Siegismund, Mario Wieser, Stephan Heyse, Stephan Steigele

Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022

2020

Uncertainty with deep learning: a practical view on out of distribution detection.

Daniel Siegismund, Stephan Heyse, Stephan Steigele

Proceedings of the 7th Swiss Conference on Data Science, 2020