Kim Steenstrup Pedersen

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Søren HaubergCognitive Systems, DTU Compute, Technical University of DenmarkVerified email at dtu.dk
Christian IgelDepartment of Computer Science, University of CopenhagenVerified email at diku.dk
Mads NielsenProfessor of Computer Science, University of CopenhagenVerified email at diku.edu
Anders Bjorholm DahlProfessor, Image Analysis, Technical University of DenmarkVerified email at dtu.dk
Henrik Aanaes3ShapeVerified email at 3shape.com
François LauzeAssociate Professor, Mathematical Image Analysis, University of CopenhagenVerified email at di.ku.dk
Kristoffer Stensbo-SmidtPostdoc, Department of Applied Mathematics and Computer Science, Technical University of DenmarkVerified email at dtu.dk
Ann B. LeeDepartment of Statistics & Data Science and the Machine Learning Department, Carnegie MellonVerified email at cmu.edu
Jan KremerZendeskVerified email at zendesk.com
Søren I. OlsenAssociate Emeritus, Universty of CopenhagenVerified email at diku.dk
David MumfordProfessor Emeritus, Harvard and Brown UniversitiesVerified email at brown.edu
Fabian GiesekeDepartment of Information Systems, University of MünsterVerified email at uni-muenster.de
Marco LoogRadboud UniversityVerified email at ru.nl
Erik Schou DreierSenior scientist, Foss AnalyticalVerified email at foss.dk
David GustavssonSenior Researcher, FOI, Linköping, SwedenVerified email at foi.se
Ole-Christian Galbo EngstrømPh.D. Student, University of Copenhagen Department of Computer Science and FOSS Analytical A/SVerified email at foss.dk
Stefan SommerProfessor at University of CopenhagenVerified email at di.ku.dk
Bo MarkussenProfessor of Statistics, University of CopenhagenVerified email at math.ku.dk
Anders Boesen Lindbo LarsenTechnical University of DenmarkVerified email at dtu.dk
Kenny ErlebenProfessor, Department of Computer Science, University of CopenhagenVerified email at di.ku.dk

Kim Steenstrup Pedersen

Department of computer science, University of Copenhagen

Verified email at diku.dk - Homepage

Computer vision computer vision for natural history and cultural heritage image analysis machine learning pattern recognitio


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The nonlinear statistics of high-contrast patches in natural images AB Lee, KS Pedersen, D Mumford International Journal of Computer Vision 54, 83-103, 2003	365	2003
Interesting interest points–a survey of interest point performance on a unique data set H Aanæs, AL Dahl, KS Pedersen International Journal of Computer Vision 97 (1), 18--35, 2012	256*	2012
Active learning with support vector machines J Kremer, K Steenstrup Pedersen, C Igel Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 4 (4 …, 2014	181	2014
Big universe, big data: machine learning and image analysis for astronomy J Kremer, K Stensbo-Smidt, F Gieseke, KS Pedersen, C Igel IEEE Intelligent Systems 32 (2), 16-22, 2017	141	2017
Unscented Kalman filtering on Riemannian manifolds S Hauberg, F Lauze, KS Pedersen Journal of mathematical imaging and vision 46, 103-120, 2013	136	2013
Pre-harvest weed mapping of Cirsium arvense in wheat and barley with off-the-shelf UAVs J Rasmussen, J Nielsen, JC Streibig, JE Jensen, KS Pedersen, SI Olsen Precision Agriculture 20, 983-999, 2019	77	2019
Finding the best feature detector-descriptor combination AL Dahl, H Aanæs, KS Pedersen 2011 international conference on 3d imaging, modeling, processing …, 2011	60	2011
Gaussian-like spatial priors for articulated tracking S Hauberg, S Sommer, KS Pedersen Computer Vision–ECCV 2010: 11th European Conference on Computer Vision …, 2010	41	2010
Toward a full probability model of edges in natural images KS Pedersen, AB Lee Computer Vision—ECCV 2002: 7th European Conference on Computer Vision …, 2002	31	2002
The complex statistics of high-contrast patches in natural images AB Lee, KS Pedersen, D Mumford WWW Proceedings of Second International IEEE Workshop on Statistical and …, 2001	28	2001
Predicting articulated human motion from spatial processes S Hauberg, KS Pedersen International Journal of Computer Vision 94, 317-334, 2011	26	2011
Jet-based local image descriptors ABL Larsen, S Darkner, AL Dahl, KS Pedersen Computer Vision–ECCV 2012: 12th European Conference on Computer Vision …, 2012	25	2012
Unscented kalman filtering for articulated human tracking ABL Larsen, S Hauberg, KS Pedersen Image Analysis: 17th Scandinavian Conference, SCIA 2011, Ystad, Sweden, May …, 2011	25	2011
Natural metrics and least-committed priors for articulated tracking S Hauberg, S Sommer, KS Pedersen Image and Vision Computing 30 (6-7), 453-461, 2012	24	2012
Nearest neighbor density ratio estimation for large-scale applications in astronomy J Kremer, F Gieseke, KS Pedersen, C Igel Astronomy and Computing 12, 67-72, 2015	21	2015
Properties of brownian image models in scale-space KS Pedersen International Conference on Scale-Space Theories in Computer Vision, 281-296, 2003	21	2003
The hausdorff dimension and scale-space normalization of natural images KS Pedersen, M Nielsen Journal of Visual communication and image representation 11 (2), 266-277, 2000	20	2000
Shape index descriptors applied to texture-based galaxy analysis KS Pedersen, K Stensbo-Smidt, A Zirm, C Igel Proceedings of the IEEE International Conference on Computer Vision, 2440-2447, 2013	18	2013
Sacrificing information for the greater good: how to select photometric bands for optimal accuracy K Stensbo-Smidt, F Gieseke, C Igel, A Zirm, K Steenstrup Pedersen Monthly Notices of the Royal Astronomical Society 464 (3), 2577-2596, 2017	17	2017
Deep learning for detection of railway signs and signals G Karagiannis, S Olsen, K Pedersen Advances in Computer Vision: Proceedings of the 2019 Computer Vision …, 2020	16	2020

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