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 | 1703 | 2019 |
Ilastik: Interactive learning and segmentation toolkit C Sommer, C Straehle, U Köthe, FA Hamprecht International Symposium on Biomedical Imaging (ISBI 2011), 230-233, 2011 | 1380 | 2011 |
Analyzing inverse problems with invertible neural networks L Ardizzone, J Kruse, S Wirkert, D Rahner, EW Pellegrini, RS Klessen, ... International Conference on Learning Representations (ICLR 2019), 2018 | 554 | 2018 |
On oblique random forests BH Menze, BM Kelm, DN Splitthoff, U Köthe, FA Hamprecht Machine Learning and Knowledge Discovery in Databases: European Conference …, 2011 | 322 | 2011 |
Guided image generation with conditional invertible neural networks L Ardizzone, C Lüth, J Kruse, C Rother, U Köthe arXiv preprint arXiv:1907.02392, 2019 | 319* | 2019 |
Learning to count with regression forest and structured labels L Fiaschi, U Köthe, R Nair, FA Hamprecht Proceedings of the 21st international conference on pattern recognition …, 2012 | 270 | 2012 |
Edge and junction detection with an improved structure tensor U Köthe Joint Pattern Recognition Symposium, 25-32, 2003 | 239 | 2003 |
BayesFlow: Learning complex stochastic models with invertible neural networks ST Radev, UK Mertens, A Voss, L Ardizzone, U Köthe IEEE Transactions on Neural Networks and Learning Systems 33 (4), 1452-1466, 2020 | 170 | 2020 |
Automated detection and segmentation of synaptic contacts in nearly isotropic serial electron microscopy images A Kreshuk, CN Straehle, C Sommer, U Köthe, M Cantoni, G Knott, ... PloS one 6 (10), e24899, 2011 | 164 | 2011 |
Multicut brings automated neurite segmentation closer to human performance T Beier, C Pape, N Rahaman, T Prange, S Berg, DD Bock, A Cardona, ... Nature Methods 14 (2), 101-102, 2017 | 162 | 2017 |
Theoretical and experimental error analysis of continuous-wave time-of-flight range cameras M Frank, M Plaue, H Rapp, U Köthe, B Jähne, FA Hamprecht Optical Engineering 48 (1), 013602-013602-16, 2009 | 141 | 2009 |
Segmentation of SBFSEM volume data of neural tissue by hierarchical classification B Andres, U Köthe, M Helmstaedter, W Denk, FA Hamprecht Pattern Recognition: 30th DAGM Symposium Munich, Germany, June 10-13, 2008 …, 2008 | 133 | 2008 |
Can virtual contrast enhancement in brain MRI replace gadolinium?: a feasibility study J Kleesiek, JN Morshuis, F Isensee, K Deike-Hofmann, D Paech, ... Investigative radiology 54 (10), 653-660, 2019 | 131 | 2019 |
Disentanglement by nonlinear ICA with general incompressible-flow networks (GIN) P Sorrenson, C Rother, U Köthe International Conference on Learning Representations (ICLR 2020), 2020 | 128 | 2020 |
Probabilistic image segmentation with closedness constraints B Andres, JH Kappes, T Beier, U Köthe, FA Hamprecht 2011 International Conference on Computer Vision, 2611-2618, 2011 | 121 | 2011 |
Globally optimal closed-surface segmentation for connectomics B Andres, T Kroeger, KL Briggman, W Denk, N Korogod, G Knott, U Köthe, ... Computer Vision–ECCV 2012: 12th European Conference on Computer Vision …, 2012 | 116 | 2012 |
Graphical model for joint segmentation and tracking of multiple dividing cells M Schiegg, P Hanslovsky, C Haubold, U Köthe, L Hufnagel, ... Bioinformatics 31 (6), 948-956, 2015 | 113 | 2015 |
Toward digital staining using imaging mass spectrometry and random forests M Hanselmann, U Köthe, M Kirchner, BY Renard, ER Amstalden, ... Journal of proteome research 8 (7), 3558-3567, 2009 | 107 | 2009 |
DALSA: Domain adaptation for supervised learning from sparsely annotated MR images M Goetz, C Weber, F Binczyk, J Polanska, R Tarnawski, ... IEEE transactions on medical imaging 35 (1), 184-196, 2015 | 102 | 2015 |
Invertible networks or partons to detector and back again M Bellagente, A Butter, G Kasieczka, T Plehn, A Rousselot, ... SciPost Physics 9 (5), 074, 2020 | 98 | 2020 |