World's Best Scientists 2026 revealed!
Stefan Harmeling

Stefan Harmeling

D-Index & Metrics

Computer Science

D-Index
38
Citations
12866
World Ranking
9963
National Ranking
498

Overview

Stefan Harmeling is affiliated with TU Dortmund University in Germany and has an extensive publication record primarily focused on computer science and its intersection with medical imaging and related technologies. Their work spans several subfields, including artificial intelligence, computer vision and pattern recognition, and radiology, nuclear medicine, and imaging.

Their research topics cover a variety of specialized areas such as reinforcement learning in robotics, advanced MRI techniques and applications, atomic and subatomic physics research, social media and politics, advanced X-ray imaging techniques, cell image analysis techniques, and advanced image processing techniques.

Notable recent publications include:

  • Contour proposal networks for biomedical instance segmentation, 2022, Medical Image Analysis
  • Convolutional neural networks for cytoarchitectonic brain mapping at large scale, 2021, NeuroImage
  • Comparison of cardiac volumetry using real-time MRI during free-breathing with standard cine MRI during breath-hold in children, 2022, Pediatric Radiology
  • Spirometry-based reconstruction of real-time cardiac MRI: Motion control and quantification of heart-lung interactions, 2021, Magnetic Resonance in Medicine
  • Limited-angle tomography reconstruction via deep end-to-end learning on synthetic data, 2023, Applied Mathematics for Modern Challenges

Frequent collaboration partners of Harmeling include Tobias Uelwer, Jan Robine, Stefan Sylvius Wagner, Maike Behrendt, and Marc Höftmann. The collaborative research with these coauthors has contributed to numerous publications over various years.

Harmeling's work has been published predominantly in the venue arXiv (Cornell University), with 23 publications, alongside contributions to Lecture Notes in Computer Science, Medical Image Analysis, Pediatric Radiology, and Applied Mathematics for Modern Challenges.

Their focus on advanced computational techniques applied to biomedical imaging and complex physical systems illustrates a multifaceted approach to research within computer science, intersecting with medical and physical sciences.

Best Publications

  • Learning to detect unseen object classes by between-class attribute transfer

    Christoph H Lampert;Hannes Nickisch;Stefan Harmeling

  • Attribute-Based Classification for Zero-Shot Visual Object Categorization

    Christoph H. Lampert;Hannes Nickisch;Stefan Harmeling

  • Image denoising: Can plain neural networks compete with BM3D?

    Harold C. Burger;Christian J. Schuler;Stefan Harmeling

  • How to Explain Individual Classification Decisions

    David Baehrens;Timon Schroeter;Stefan Harmeling;Motoaki Kawanabe

  • Learning to Deblur

    Christian J. Schuler;Michael Hirsch;Stefan Harmeling;Bernhard Scholkopf

  • Recording and playback of camera shake: benchmarking blind deconvolution with a real-world database

    Rolf Köhler;Michael Hirsch;Betty Mohler;Bernhard Schölkopf

  • Painfree and accurate Bayesian estimation of psychometric functions for (potentially) overdispersed data

    Heiko H. Schütt;Heiko H. Schütt;Stefan Harmeling;Jakob H. Macke;Jakob H. Macke;Felix A. Wichmann

  • Fast removal of non-uniform camera shake

    Michael Hirsch;Christian J. Schuler;Stefan Harmeling;Bernhard Scholkopf

  • A Machine Learning Approach for Non-blind Image Deconvolution

    Christian J. Schuler;Harold Christopher Burger;Stefan Harmeling;Bernhard Scholkopf

  • Efficient filter flow for space-variant multiframe blind deconvolution

    Michael Hirsch;Suvrit Sra;Bernhard Scholkopf;Stefan Harmeling

  • Results of the GREAT08 Challenge: an image analysis competition for cosmological lensing

    Sarah Bridle;Sreekumar T. Balan;Matthias Bethge;Marc Gentile

  • How to Explain Individual Classification Decisions

    David Baehrens;Timon Schroeter;Stefan Harmeling;Motoaki Kawanabe

  • Kernel-based nonlinear blind source separation

    Stefan Harmeling;Andreas Ziehe;Motoaki Kawanabe;Klaus-Robert Müller

  • Image analysis for cosmology: results from the GREAT10 Galaxy Challenge

    T. D. Kitching;S. T. Balan;S. Bridle;N. Cantale

  • Detection and attribution of large spatiotemporal extreme events in Earth observation data

    Jakob Zscheischler;Miguel D. Mahecha;Stefan Harmeling;Markus Reichstein

  • Mask-Specific Inpainting with Deep Neural Networks

    Rolf Köhler;Christian J. Schuler;Bernhard Schölkopf;Stefan Harmeling

  • Space-Variant Single-Image Blind Deconvolution for Removing Camera Shake

    Stefan Harmeling;Hirsch Michael;Bernhard Schölkopf

  • From outliers to prototypes: Ordering data

    Stefan Harmeling;Guido Dornhege;David Tax;Frank Meinecke

  • Non-stationary correction of optical aberrations

    Christian J. Schuler;Michael Hirsch;Stefan Harmeling;Bernhard Scholkopf

  • Blind separation of post-nonlinear mixtures using linearizing transformations and temporal decorrelation

    Andreas Ziehe;Motoaki Kawanabe;Stefan Harmeling;Klaus-Robert Müller

Frequent Co-Authors

Bernhard Schölkopf
Bernhard Schölkopf Max Planck Institute for Intelligent Systems
Katrin Amunts
Katrin Amunts Forschungszentrum Jülich
Klaus-Robert Müller
Klaus-Robert Müller Technical University of Berlin
Jakob Zscheischler
Jakob Zscheischler Helmholtz Centre for Environmental Research
Richard Massey
Richard Massey Durham University
Catherine Heymans
Catherine Heymans University of Edinburgh
Gary Bernstein
Gary Bernstein University of Pennsylvania
Rachel Mandelbaum
Rachel Mandelbaum Carnegie Mellon University
Konrad Kuijken
Konrad Kuijken Leiden University

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