Ullrich Köthe

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Indice H	44	32
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Fred A. HamprechtProfessor, Heidelberg UniversityEmail verificata su iwr.uni-heidelberg.de
Lynton ArdizzoneHeidelberg UniversityEmail verificata su iwr.uni-heidelberg.de
Carsten RotherProfessor Uni Heidelberg / GermanyEmail verificata su iwr.uni-heidelberg.de
Christoph-Nikolas StraehleResearch Scientist, Bosch Center for Artificial IntelligenceEmail verificata su de.bosch.com
Anna KreshukGroup Leader, EMBL HeidelbergEmail verificata su embl.de
Thorsten BeierQuantStackEmail verificata su quantstack.net
Stefan T. RadevAssistant Professor, Rensselaer Polytechnic InstituteEmail verificata su rpi.edu
Bjoern AndresTU DresdenEmail verificata su andres.sc
Jakob KruseBürgerwerke eGEmail verificata su iwr.uni-heidelberg.de
Martin SchieggResearch Scientist, Bosch Center for AIEmail verificata su bosch.com
Ralf KlessenHeidelberg UniversityEmail verificata su uni-heidelberg.de
Carsten HauboldPhD Student, University of HeidelbergEmail verificata su iwr.uni-heidelberg.de
Graham KnottSenior Scientist, EPFLEmail verificata su epfl.ch
Lena Maier-HeinProfessor, German Cancer Research CenterEmail verificata su dkfz.de
Stuart BergJanelia Research CampusEmail verificata su janelia.hhmi.org
Bernhard X. KauslerEmail verificata su kausler.net
Paul-Christian BürknerFull Professor of Computational Statistics, TU Dortmund UniversityEmail verificata su tu-dortmund.de
Peer StelldingerProfessor of Theoretical Computer Science, Computer Vision and Machine LearningEmail verificata su haw-hamburg.de
Christoph SommerIST AustriaEmail verificata su ist.ac.at
Bernhard RenardHasso Plattner InstituteEmail verificata su hpi.de

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Ullrich Köthe

Adjunct Professor of Computer Science, University of Heidelberg

Email verificata su iwr.uni-heidelberg.de

Image Analysis Machine Learning Scientific Software


Titolo Ordina per citazioni Ordina per anno Ordina per titolo	Citata da Citata da	Anno
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	2035	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	1421	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	644	2018
Guided image generation with conditional invertible neural networks L Ardizzone, C Lüth, J Kruse, C Rother, U Köthe arXiv preprint arXiv:1907.02392, 2019	380*	2019
On oblique random forests BH Menze, BM Kelm, DN Splitthoff, U Köthe, FA Hamprecht Machine Learning and Knowledge Discovery in Databases: European Conference …, 2011	336	2011
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	274	2012
Edge and junction detection with an improved structure tensor U Köthe Joint Pattern Recognition Symposium, 25-32, 2003	243	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	229	2020
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	180	2017
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	166	2011
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	153	2019
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	144	2009
Disentanglement by nonlinear ICA with general incompressible-flow networks (GIN) P Sorrenson, C Rother, U Köthe International Conference on Learning Representations (ICLR 2020), 2020	140	2020
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	136	2008
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	128	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	119	2012
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	115	2020
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	114	2015
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	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	110	2009

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