Kim Steenstrup Pedersen

Publication Activity (10 Years)

Years Active: 1999-2023
Publications (10 Years): 13

Top Topics

Tissue Segmentation

Top Venues

Int. J. Comput. Vis.

WIREs Data Mining Knowl. Discov.

Publications

Xiao Hu, François Lauze, Kim Steenstrup Pedersen
Refractive Pose Refinement. Int. J. Comput. Vis. 131 (6) (2023)
Ole-Christian Galbo Engstrøm, Erik Schou Dreier, Birthe Møller Jespersen, Kim Steenstrup Pedersen
Analyzing Near-Infrared Hyperspectral Imaging for Protein Content Regression and Grain Variety Classification Using Bulk References and Varying Grain-to-Background Ratios. CoRR (2023)
Ole-Christian Galbo Engstrøm, Erik Schou Dreier, Birthe Møller Jespersen, Kim Steenstrup Pedersen
Improving Deep Learning on Hyperspectral Images of Grain by Incorporating Domain Knowledge from Chemometrics. ICCV (Workshops) (2023)
Roberta Hunt, Kim Steenstrup Pedersen
Rove-Tree-11: The Not-so-Wild Rover a Hierarchically Structured Image Dataset for Deep Metric Learning Research. ACCV (5) (2022)
Xiao Hu, François Lauze, Kim Steenstrup Pedersen, Jean Mélou
Absolute and Relative Pose Estimation in Refractive Multi View. ICCVW (2021)
Ole-Christian Galbo Engstrøm, Erik Schou Dreier, Kim Steenstrup Pedersen
Predicting Protein Content in Grain Using Hyperspectral Deep Learning. ICCVW (2021)
Georgios Karagiannis, Søren I. Olsen, Kim Steenstrup Pedersen
Deep Learning for Detection of Railway Signs and Signals. CVC (1) (2019)
Wouter M. Kouw, Silas N. Ørting, Jens Petersen, Kim Steenstrup Pedersen, Marleen de Bruijne
A cross-center smoothness prior for variational Bayesian brain tissue segmentation. CoRR (2019)
Wouter M. Kouw, Silas N. Ørting, Jens Petersen, Kim Steenstrup Pedersen, Marleen de Bruijne
A Cross-Center Smoothness Prior for Variational Bayesian Brain Tissue Segmentation. IPMI (2019)
Jan Kremer, Kristoffer Stensbo-Smidt, Fabian Gieseke, Kim Steenstrup Pedersen, Christian Igel
Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy. IEEE Intell. Syst. 32 (2) (2017)
Jan Kremer, Kristoffer Stensbo-Smidt, Fabian Gieseke, Kim Steenstrup Pedersen, Christian Igel
Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy. CoRR (2017)
Kim Steenstrup Pedersen, Rasmus R. Paulsen
Special section on 19th Scandinavian conference on image analysis (SCIA 2015). Pattern Recognit. Lett. 80 (2016)
Jan Kremer, Fabian Gieseke, Kim Steenstrup Pedersen, Christian Igel
Nearest neighbor density ratio estimation for large-scale applications in astronomy. Astron. Comput. 12 (2015)
Jan Kremer, Kim Steenstrup Pedersen, Christian Igel
Active learning with support vector machines. WIREs Data Mining Knowl. Discov. 4 (4) (2014)
Henrik Aanæs, Anders Lindbjerg Dahl, Kim Steenstrup Pedersen
Erratum to: Interesting Interest Points - A Comparative Study of Interest Point Performance on a Unique Data Set. Int. J. Comput. Vis. 108 (3) (2014)
Kristoffer Stensbo-Smidt, Christian Igel, Andrew Zirm, Kim Steenstrup Pedersen
Nearest neighbour regression outperforms model-based prediction of specific star formation rate. IEEE BigData (2013)
Kim Steenstrup Pedersen, Kristoffer Stensbo-Smidt, Andrew Zirm, Christian Igel
Shape Index Descriptors Applied to Texture-Based Galaxy Analysis. ICCV (2013)
Cristina E. Manfredotti, Kim Steenstrup Pedersen, Howard J. Hamilton, Sandra Zilles
Learning Models of Activities Involving Interacting Objects. IDA (2013)
Søren Hauberg, François Lauze, Kim Steenstrup Pedersen
Unscented Kalman Filtering on Riemannian Manifolds. J. Math. Imaging Vis. 46 (1) (2013)
Søren Hauberg, Stefan Sommer, Kim Steenstrup Pedersen
Natural metrics and least-committed priors for articulated tracking. Image Vis. Comput. 30 (6-7) (2012)
Henrik Aanæs, Anders Lindbjerg Dahl, Kim Steenstrup Pedersen
Interesting Interest Points - A Comparative Study of Interest Point Performance on a Unique Data Set. Int. J. Comput. Vis. 97 (1) (2012)
Anders Boesen Lindbo Larsen, Sune Darkner, Anders Lindbjerg Dahl, Kim Steenstrup Pedersen
Jet-Based Local Image Descriptors. ECCV (3) (2012)
Søren Hauberg, Kim Steenstrup Pedersen
Spatial Measures between Human Poses for Classification and Understanding. AMDO (2012)
Anders Boesen Lindbo Larsen, Søren Hauberg, Kim Steenstrup Pedersen
Unscented Kalman Filtering for Articulated Human Tracking. SCIA (2011)
Anders Lindbjerg Dahl, Henrik Aanæs, Kim Steenstrup Pedersen
Finding the Best Feature Detector-Descriptor Combination. 3DIMPVT (2011)
Søren Hauberg, Kim Steenstrup Pedersen
Predicting Articulated Human Motion from Spatial Processes. Int. J. Comput. Vis. 94 (3) (2011)
Søren Hauberg, Kim Steenstrup Pedersen
Data-Driven Importance Distributions for Articulated Tracking. EMMCVPR (2011)
Peter Mysling, Søren Hauberg, Kim Steenstrup Pedersen
An Empirical Study on the Performance of Spectral Manifold Learning Techniques. ICANN (1) (2011)
Søren Hauberg, Stefan Sommer, Kim Steenstrup Pedersen
Gaussian-Like Spatial Priors for Articulated Tracking. ECCV (1) (2010)
Søren Hauberg, Kim Steenstrup Pedersen
Stick It! Articulated Tracking Using Spatial Rigid Object Priors. ACCV (3) (2010)
Morten Engell-Nørregård, Søren Hauberg, Jérôe Lapuyade, Kenny Erleben, Kim Steenstrup Pedersen
Interactive Inverse Kinematics for Human Motion Estimation. VRIPHYS (2009)
David Gustavsson, Kim Steenstrup Pedersen, Mads Nielsen
A SVD based Image Complexity Measure. VISAPP (2) (2009)
Søren Hauberg, Jérôe Lapuyade, Morten Engell-Nørregård, Kenny Erleben, Kim Steenstrup Pedersen
Three Dimensional Monocular Human Motion Analysis in End-Effector Space. EMMCVPR (2009)
David Gustavsson, Kim Steenstrup Pedersen, François Lauze, Mads Nielsen
On the Rate of Structural Change in Scale Spaces. SSVM (2009)
Mads Nielsen, Marleen de Bruijne, Camilla Jørgensen, Søren I. Olsen, Kim Steenstrup Pedersen, Jon Sporring
Special Issue on Tribute Workshop for Peter Johansen. J. Math. Imaging Vis. 31 (2-3) (2008)
Anne Cuzol, Kim Steenstrup Pedersen, Mads Nielsen
Field of Particle Filters for Image Inpainting. J. Math. Imaging Vis. 31 (2-3) (2008)
Bo Markussen, Kim Steenstrup Pedersen, Marco Loog
Second Order Structure of Scale-Space Measurements. J. Math. Imaging Vis. 31 (2-3) (2008)
David Gustavsson, Kim Steenstrup Pedersen, Mads Nielsen
Image Inpainting by Cooling and Heating. SCIA (2007)
Kim Steenstrup Pedersen, Marco Loog, Pieter van Dorst
Salient Point and Scale Detection by Minimum Likelihood. Gaussian Processes in Practice (2007)
Kim Steenstrup Pedersen, Marco Loog, Bo Markussen
Generic Maximum Likely Scale Selection. SSVM (2007)
Bo Markussen, Kim Steenstrup Pedersen, Marco Loog
A Scale Invariant Covariance Structure on Jet Space. DSSCV (2005)
Marco Loog, Kim Steenstrup Pedersen, Bo Markussen
Maximum Likely Scale Estimation. DSSCV (2005)
Sune Høgild Keller, Kim Steenstrup Pedersen, François Lauze
Detecting Interlaced or Progressive Source of Video. MMSP (2005)
Kim Steenstrup Pedersen, Remco Duits, Mads Nielsen
On alpha Kernels, Lévy Processes, and Natural Image Statistics. Scale-Space (2005)
Martin Lillholm, Kim Steenstrup Pedersen
Jet Based Feature Classification. ICPR (2) (2004)
Ann B. Lee, Kim Steenstrup Pedersen, David Mumford
The Nonlinear Statistics of High-Contrast Patches in Natural Images. Int. J. Comput. Vis. 54 (1-3) (2003)
Kim Steenstrup Pedersen
Properties of Brownian Image Models in Scale-Space. Scale-Space (2003)
Kim Steenstrup Pedersen, Ann B. Lee
Toward a Full Probability Model of Edges in Natural Images. ECCV (1) (2002)
Kim Steenstrup Pedersen, Mads Nielsen
Computing Optic Flow by Scale-Space Integration of Normal Flow. Scale-Space (2001)
Kim Steenstrup Pedersen, Mads Nielsen
The Hausdorff Dimension and Scale-Space Normalization of Natural Images. J. Vis. Commun. Image Represent. 11 (2) (2000)
Kim Steenstrup Pedersen, Mads Nielsen
The Hausdorff Dimension and Scale-Space Normalisation of Natural Images. Scale-Space (1999)