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
Christoph HoferPostDoc, University of SalzburgVerified email at cosy.sbg.ac.at
Peter Meerwald-StadlerUniversity of SalzburgVerified email at pmeerw.net
Stephen R. AylwardSenior Director of Strategic Initiatives, North Carolina, KitwareVerified email at kitware.com
Stefan HuberSalzburg University of Applied SciencesVerified email at sthu.org
Martin StynerAssociate Professor of Computer Science and Psychiatry, University of North Carolina at Chapel HillVerified email at unc.edu
Yi HongShanghai Jiao Tong UniversityVerified email at sjtu.edu.cn
Mandar DixitScientist, MicrosoftVerified email at microsoft.com
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
François-Xavier VialardProfessor, Université Gustave EiffelVerified email at u-pem.fr
Nikhil RasiwasiaAmazon, Snapdeal, Yahoo, UCSD, Google, Microsoft.Verified email at amazon.com
Sebastian HegenbartUniversity of Applied Sciences VorarlbergVerified email at fhv.at
Florian GrafUniversity of SalzburgVerified email at sbg.ac.at
Matthew McCormickKitware, IncVerified email at kitware.com
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 sbg.ac.at - Homepage

Computer Vision Machine Learning 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	439	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	306	2015
BlenSor: Blender sensor simulation toolbox M Gschwandtner, R Kwitt, A Uhl, W Pree International Symposium on Visual Computing, 199-208, 2011	246	2011
Deep learning with topological signatures C Hofer, R Kwitt, M Niethammer, A Uhl Advances in neural information processing systems 30, 2017	181	2017
Fast predictive image registration X Yang, R Kwitt, M Niethammer Deep Learning and Data Labeling for Medical Applications, 48-57, 2016	116	2016
Lightweight probabilistic texture retrieval R Kwitt, A Uhl IEEE Transactions on Image Processing 19 (1), 241-253, 2009	116	2009
Aga: Attribute-guided augmentation M Dixit, R Kwitt, M Niethammer, N Vasconcelos Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017	110	2017
Scene recognition on the semantic manifold R Kwitt, N Vasconcelos, N Rasiwasia European Conference on Computer Vision (ECCV 2012), 359-372, 2012	109	2012
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	89	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	85	2011
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	76	2015
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	69	2010
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	65	2018
Metric learning for image registration M Niethammer, R Kwitt, FX Vialard Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019	62	2019
Connectivity-optimized representation learning via persistent homology C Hofer, R Kwitt, M Niethammer, M Dixit International conference on machine learning, 2751-2760, 2019	50	2019
Infrared camera calibration for dense depth map construction M Gschwandtner, R Kwitt, A Uhl, W Pree 2011 IEEE Intelligent Vehicles Symposium (IV), 857-862, 2011	45	2011
Low-rank atlas image analyses in the presence of pathologies X Liu, M Niethammer, R Kwitt, N Singh, M McCormick, S Aylward IEEE transactions on medical imaging 34 (12), 2583-2591, 2015	43	2015
Computer-assisted pit-pattern classification in different wavelet domains for supporting dignity assessment of colonic polyps M Häfner, R Kwitt, A Uhl, F Wrba, A Gangl, A Vécsei Pattern Recognition 42 (6), 1180-1191, 2009	43	2009
Localizing target structures in ultrasound video–a phantom study R Kwitt, N Vasconcelos, S Razzaque, S Aylward Medical image analysis 17 (7), 712-722, 2013	41	2013
Feature extraction from multi-directional multi-resolution image transformations for the classification of zoom-endoscopy images M Häfner, R Kwitt, A Uhl, A Gangl, F Wrba, A Vécsei Pattern Analysis and Applications 12 (4), 407-413, 2009	41	2009

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