Christoph-Nikolas Straehle
Christoph-Nikolas Straehle
Research Scientist, Bosch Center for Artificial Intelligence
Verified email at de.bosch.com
Title
Cited by
Cited by
Year
Ilastik: Interactive learning and segmentation toolkit
C Sommer, C Straehle, U Koethe, FA Hamprecht
2011 IEEE international symposium on biomedical imaging: From nano to macro …, 2011
10112011
Ilastik: interactive machine learning for (bio) image analysis
S Berg, D Kutra, T Kroeger, CN Straehle, BX Kausler, C Haubold, ...
Nature Methods 16 (12), 1226-1232, 2019
3072019
Automated detection and segmentation of synaptic contacts in nearly isotropic serial electron microscopy images
A Kreshuk, CN Straehle, C Sommer, U Koethe, M Cantoni, G Knott, ...
PloS one 6 (10), e24899, 2011
1422011
Globally consistent multi-label assignment on the ray space of 4d light fields
S Wanner, C Straehle, B Goldluecke
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013
1042013
Correlative in vivo 2 photon and focused ion beam scanning electron microscopy of cortical neurons
B Maco, A Holtmaat, M Cantoni, A Kreshuk, CN Straehle, FA Hamprecht, ...
PloS one 8 (2), e57405, 2013
762013
Carving: scalable interactive segmentation of neural volume electron microscopy images
CN Straehle, U Köthe, G Knott, FA Hamprecht
International Conference on Medical Image Computing and Computer-Assisted …, 2011
462011
Automated segmentation of synapses in 3D EM data
A Kreshuk, CN Straehle, C Sommer, U Koethe, G Knott, FA Hamprecht
2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro …, 2011
342011
Conditional flow variational autoencoders for structured sequence prediction
A Bhattacharyya, M Hanselmann, M Fritz, B Schiele, CN Straehle
arXiv preprint arXiv:1908.09008, 2019
312019
Seeded watershed cut uncertainty estimators for guided interactive segmentation
CN Straehle, U Koethe, G Knott, K Briggman, W Denk, FA Hamprecht
2012 IEEE Conference on Computer Vision and Pattern Recognition, 765-772, 2012
282012
Biomedical imaging: from Nano to Macro
C Sommer, C Straehle, U Kothe, FA Hamprecht
2011 IEEE International Symposium on 230, 233, 2011
112011
K-smallest spanning tree segmentations
C Straehle, S Peter, U Köthe, FA Hamprecht
German Conference on Pattern Recognition, 375-384, 2013
92013
Including multi-feature interactions and redundancy for feature ranking in mixed datasets
AK Shekar, T Bocklisch, PI Sánchez, CN Straehle, E Müller
Joint European conference on machine learning and knowledge discovery in …, 2017
82017
Multiple instance learning with response-optimized random forests
C Straehle, M Kandemir, U Koethe, FA Hamprecht
2014 22nd International Conference on Pattern Recognition, 3768-3773, 2014
82014
Weakly supervised learning of image partitioning using decision trees with structured split criteria
C Straehle, U Koethe, FA Hamprecht
Proceedings of the IEEE International Conference on Computer Vision, 1849-1856, 2013
62013
Haar wavelet based block autoregressive flows for trajectories
A Bhattacharyya, CN Straehle, M Fritz, B Schiele
DAGM German Conference on Pattern Recognition, 275-288, 2020
42020
Learning game-theoretic models of multiagent trajectories using implicit layers
P Geiger, CN Straehle
arXiv preprint arXiv:2008.07303, 2020
32020
Non-cooperative multi-agent systems with exploring agents
J Etesami, CN Straehle
arXiv preprint arXiv:2005.12360, 2020
22020
Method and device for controlling a robot
CN Straehle, SJ Etesami
US Patent App. 17/156,156, 2021
2021
Training and data synthesis and probability inference using nonlinear conditional normalizing flow model
A Bhattacharyya, CN Straehle
US Patent App. 16/922,748, 2021
2021
Machine learnable system with conditional normalizing flow
A Bhattacharyya, CN Straehle
US Patent App. 16/919,955, 2021
2021
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