Erich Kobler

Dipl.-Ing., BSc

20152019
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  • 2 Similar Profiles
Image reconstruction Engineering & Materials Science
Early Stopping Mathematics
Image quality Engineering & Materials Science
Image denoising Engineering & Materials Science
Gradient Flow Mathematics
Image Restoration Mathematics
Deconvolution Engineering & Materials Science
optimal control Physics & Astronomy

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Research Output 2015 2019

  • 5 Conference contribution
  • 4 Article
  • 2 Abstract
  • 1 Master's Thesis

An Optimal Control Approach to Early Stopping Variational Methods for Image Restoration

Effland, A., Kobler, E., Kunisch, K. & Pock, T., 2019, (Submitted) In : Journal of Mathematical Imaging and Vision. 32 p.

Research output: Contribution to journalArticleResearchpeer-review

Early Stopping
Image denoising
Gradient Flow
Image Restoration
optimal control

Joint Reconstruction and Classification of Tumor Cells and Cell Interactions in Melanoma Tissue Sections with Synthesized Training Data

Effland, A., Kobler, E., Brandenburg, A., Klatzer, T., Neuhäuser, L., Hölzel, M., Landsberg, J., Pock, T. & Rumpf, M., 2019, In : International Journal of Computer Assisted Radiology and Surgery.

Research output: Contribution to journalArticleResearchpeer-review

Time Discrete Geodesics in Deep Feature Spaces for Image Morphing

Effland, A., Kobler, E., Pock, T. & Rumpf, M., 2019, Scale Space and Variational Methods in Computer Vision: SSVM 2019. Lellmann, J., Burger, M. & Modersitzki, J. (eds.). Cham: Springer, p. 171-182 (Lecture Notes in Computer Science; vol. 11603).

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Splines
Computer vision
Interpolation
Textures
Semantics

Analysis of the influence of deviations between training and test data in learned image reconstruction

Knoll, F., Hammernik, K., Kobler, E., Pock, T., Sodickson, D. K. & Recht, M. P., 2018.

Research output: Contribution to conferenceAbstractResearchpeer-review

Assessment of the generalization of learned image reconstruction and the potential for transfer learning

Knoll, F., Hammernik, K., Kobler, E., Pock, T., Recht, M. P. & Sodickson, D. K., 2018, In : Magnetic resonance in medicine. 13 p.

Research output: Contribution to journalArticleResearchpeer-review

Activities 2018 2018

  • 4 Invited talk at conference or symposium
  • 1 Talk at conference or symposium

Variational Deep Learning for low-dose Computed Tomography

Erich Kobler (Speaker)
18 Apr 2018

Activity: Talk or presentationTalk at conference or symposiumScience to science

Learning Convex Regularizers for Image Reconstruction

Erich Kobler (Speaker)
21 May 201825 May 2018

Activity: Talk or presentationInvited talk at conference or symposiumScience to science

Variational networks: connecting variational methods and deep learning

Erich Kobler (Speaker)
19 Mar 201823 Mar 2018

Activity: Talk or presentationInvited talk at conference or symposiumScience to science

Learning for Compressed Sensing CT Reconstruction

Erich Kobler (Speaker)
7 Jun 2018

Activity: Talk or presentationInvited talk at conference or symposiumScience to science

Deep regularization for medical image analysis

Erich Kobler (Speaker)
5 Jun 2018

Activity: Talk or presentationInvited talk at conference or symposiumScience to science

Prizes

GCPR 2017 Best Paper Award

Erich Kobler (Recipient), Kerstin Hammernik (Recipient), Thomas Pock (Recipient) & Teresa Klatzer (Recipient), 15 Sep 2017

Prize: Prizes / Medals / Awards

Summa cum Laude Merit Award

Kerstin Hammernik (Recipient), Erich Kobler (Recipient), Thomas Pock (Recipient), Michael P Recht (Recipient), Daniel K Sodickson (Recipient) & Florian Knoll (Recipient), 2018

Prize: Prizes / Medals / Awards