Roland Kwitt

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Marc NiethammerProfessor of Computer Science, UNC Chapel HillVerified email at cs.unc.edu
Xiao YangBytedance Inc.Verified email at cs.unc.edu
Nuno VasconcelosProfessor of Electrical and Computer Engineering, University of California San DiegoVerified email at ece.ucsd.edu
Stephen R. AylwardSenior Director of Strategic Initiatives, North Carolina, KitwareVerified email at kitware.com
Peter Meerwald-StadlerUniversity of SalzburgVerified email at pmeerw.net
Stefan HuberSalzburg University of Applied SciencesVerified email at sthu.org
Florian GrafUniversity of SalzburgVerified email at sbg.ac.at
Mandar DixitScientist, MicrosoftVerified email at microsoft.com
Yi HongShanghai Jiao Tong UniversityVerified email at sjtu.edu.cn
Martin StynerAssociate Professor of Computer Science and Psychiatry, University of North Carolina at Chapel HillVerified email at unc.edu
Michael GschwandtnerVerified email at ait.ac.at
Nikhil SinghUniversity of North Carolina, Chapel Hill, University of UtahVerified email at cs.utah.edu
Ulrich BauerTechnical University of MunichVerified email at tum.de
Jan ReininghausInstitute of Science and Technology AustriaVerified email at ist.ac.at
Sebastian HegenbartUniversity of Applied Sciences VorarlbergVerified email at fhv.at
Nikhil RasiwasiaAmazon, Snapdeal, Yahoo, UCSD, Google, Microsoft.Verified email at amazon.com
Matthew McCormickKitware, IncVerified email at kitware.com
François-Xavier VialardProfessor, Université Gustave EiffelVerified email at u-pem.fr
Xu HanPhD student of Computer Science, UNC Chapel HillVerified email at cs.unc.edu
Sharif RazzaqueMedtronicVerified email at medtronic.com

Roland Kwitt

Professor, Department of Artificial Intelligence and Human Interfaces, University of Salzburg

Verified email at plus.ac.at - Homepage

Machine Learning Computer Vision Medical Imaging


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Quicksilver: Fast predictive image registration–a deep learning approach X Yang, R Kwitt, M Styner, M Niethammer NeuroImage 158, 378-396, 2017	586	2017
A stable multi-scale kernel for topological machine learning J Reininghaus, S Huber, U Bauer, R Kwitt Proceedings of the IEEE conference on computer vision and pattern …, 2015	371	2015
BlenSor: Blender sensor simulation toolbox M Gschwandtner, R Kwitt, A Uhl, W Pree Advances in Visual Computing: 7th International Symposium, ISVC 2011, Las …, 2011	322	2011
Deep learning with topological signatures C Hofer, R Kwitt, M Niethammer, A Uhl Advances in neural information processing systems 30, 2017	252	2017
Fast predictive image registration X Yang, R Kwitt, M Niethammer Deep Learning and Data Labeling for Medical Applications: First …, 2016	150	2016
Aga: Attribute-guided augmentation M Dixit, R Kwitt, M Niethammer, N Vasconcelos Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017	133	2017
Lightweight probabilistic texture retrieval R Kwitt, A Uhl IEEE Transactions on Image Processing 19 (1), 241-253, 2009	119	2009
Scene recognition on the semantic manifold R Kwitt, N Vasconcelos, N Rasiwasia European Conference on Computer Vision (ECCV 2012), 359-372, 2012	112	2012
Feature space transfer for data augmentation B Liu, X Wang, M Dixit, R Kwitt, N Vasconcelos Proceedings of the IEEE conference on computer vision and pattern …, 2018	104	2018
Statistical topological data analysis-a kernel perspective R Kwitt, S Huber, M Niethammer, W Lin, U Bauer Advances in neural information processing systems 28, 2015	95	2015
Image similarity measurement by Kullback-Leibler divergences between complex wavelet subband statistics for texture retrieval R Kwitt, A Uhl 2008 15th IEEE International Conference on Image Processing, 933-936, 2008	94	2008
Efficient texture image retrieval using copulas in a Bayesian framework R Kwitt, P Meerwald, A Uhl IEEE transactions on image processing 20 (7), 2063-2077, 2011	89	2011
Metric learning for image registration M Niethammer, R Kwitt, FX Vialard Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019	84	2019
Dissecting Supervised Contrastive Learning F Graf, C Hofer, M Niethammer, R Kwitt International Conference on Machine Learning, 3821-3830, 2021	77	2021
Lightweight detection of additive watermarking in the DWT-domain R Kwitt, P Meerwald, A Uhl IEEE transactions on image processing 20 (2), 474-484, 2010	74	2010
Graph filtration learning C Hofer, F Graf, B Rieck, M Niethammer, R Kwitt International Conference on Machine Learning, 4314-4323, 2020	71	2020
Connectivity-optimized representation learning via persistent homology C Hofer, R Kwitt, M Niethammer, M Dixit International conference on machine learning, 2751-2760, 2019	69	2019
One-shot learning of scene locations via feature trajectory transfer R Kwitt, S Hegenbart, M Niethammer Proceedings of The IEEE conference on computer vision and pattern …, 2016	59	2016
Learning representations of persistence barcodes. CD Hofer, R Kwitt, M Niethammer J. Mach. Learn. Res. 20 (126), 1-45, 2019	58	2019
Stochastic block models with multiple continuous attributes N Stanley, T Bonacci, R Kwitt, M Niethammer, PJ Mucha Applied Network Science 4 (1), 1-22, 2019	57	2019

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