Steffen Wolf
Steffen Wolf
MRC Laboratory of Molecular Biology, Cambridge
Verified email at - Homepage
Cited by
Cited by
An objective comparison of cell-tracking algorithms
V Ulman, M Maška, KEG Magnusson, O Ronneberger, C Haubold, ...
Nature methods 14 (12), 1141-1152, 2017
The Mutex Watershed: Efficient, Parameter-Free Image Partitioning
S Wolf, C Pape, A Bailoni, N Rahaman, A Kreshuk, U Kothe, ...
Proceedings of the European Conference on Computer Vision (ECCV), 546-562, 2018
Learned Watershed: End-to-End Learning of Seeded Segmentation
S Wolf, L Schott, U Köthe, F Hamprecht
International Conference on Computer Vision: ICCV 2017, 2017
The mutex watershed and its objective: Efficient, parameter-free graph partitioning
S Wolf, A Bailoni, C Pape, N Rahaman, A Kreshuk, U Köthe, ...
IEEE transactions on pattern analysis and machine intelligence 43 (10), 3724 …, 2020
A generalized framework for agglomerative clustering of signed graphs applied to instance segmentation
A Bailoni, C Pape, S Wolf, T Beier, A Kreshuk, FA Hamprecht
arXiv preprint arXiv:1906.11713, 2019
A generalized successive shortest paths solver for tracking dividing targets
C Haubold, J Aleš, S Wolf, FA Hamprecht
European Conference on Computer Vision, 566-582, 2016
The semantic mutex watershed for efficient bottom-up semantic instance segmentation
S Wolf, Y Li, C Pape, A Bailoni, A Kreshuk, FA Hamprecht
European Conference on computer vision, 208-224, 2020
Tracking objects with higher order interactions via delayed column generation
S Wang, S Wolf, C Fowlkes, J Yarkony
Artificial Intelligence and Statistics, 1132-1140, 2017
Microscopy‐based assay for semi‐quantitative detection of SARS‐CoV‐2 specific antibodies in human sera: A semi‐quantitative, high throughput, microscopy‐based assay expands …
C Pape, R Remme, A Wolny, S Olberg, S Wolf, L Cerrone, M Cortese, ...
BioEssays 43 (3), 2000257, 2021
LemoNADe: Learned motif and neuronal assembly detection in calcium imaging videos
E Kirschbaum, M Haußmann, S Wolf, H Sonntag, J Schneider, S Elzoheiry, ...
arXiv preprint arXiv:1806.09963, 2018
Learning the arrow of time for problems in reinforcement learning
N Rahaman, S Wolf, A Goyal, R Remme, Y Bengio
Instance separation emerges from inpainting
S Wolf, FA Hamprecht, J Funke
arXiv preprint arXiv:2003.00891, 2020
Microscopy-based assay for semi-quantitative detection of SARS-CoV-2 specific antibodies in human sera
C Pape, R Remme, A Wolny, S Olberg, S Wolf, L Cerrone, M Cortese, ...
bioRxiv, 2020
Proof-reading guidance in cell tracking by sampling from tracking-by-assignment models
M Schiegg, B Heuer, C Haubold, S Wolf, U Koethe, FA Hamprecht
2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), 394-398, 2015
Inpainting Networks Learn to Separate Cells in Microscopy Images.
S Wolf, FA Hamprecht, J Funke, H Janelia, VA Ashburn
BMVC, 2020
Current approaches to fate mapping and lineage tracing using image data
S Wolf, Y Wan, K McDole
Development 148 (18), dev198994, 2021
Proposal-free volumetric instance segmentation from latent single-instance masks
A Bailoni, C Pape, S Wolf, A Kreshuk, FA Hamprecht
DAGM German Conference on Pattern Recognition, 331-344, 2020
Learning the Arrow of Time
N Rahaman, S Wolf, A Goyal, R Remme, Y Bengio
arXiv preprint arXiv:1907.01285, 2019
Tracking objects with higher order interactions using delayed column generation
S Wolf, FA Hamprecht, J Yarkony
arXiv preprint arXiv:1512.02413, 2015
Temporal control of the integrated stress response by a stochastic molecular switch
P Klein, SM Kallenberger, H Roth, K Roth, TBN Ly-Hartig, V Magg, J Alěs, ...
bioRxiv, 2022
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