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Johannes Leuschner
Johannes Leuschner
Verified email at uni-bremen.de - Homepage
Title
Cited by
Cited by
Year
Computed tomography reconstruction using deep image prior and learned reconstruction methods
DO Baguer, J Leuschner, M Schmidt
Inverse Problems 36 (9), 094004, 2020
602020
The lodopab-ct dataset: A benchmark dataset for low-dose ct reconstruction methods
J Leuschner, M Schmidt, DO Baguer, P Maaß
arXiv preprint arXiv:1910.01113, 2019
322019
Supervised non-negative matrix factorization methods for MALDI imaging applications
J Leuschner, M Schmidt, P Fernsel, D Lachmund, T Boskamp, P Maass
Bioinformatics 35 (11), 1940-1947, 2019
322019
LoDoPaB-CT, a benchmark dataset for low-dose computed tomography reconstruction
J Leuschner, M Schmidt, DO Baguer, P Maass
Scientific Data 8 (1), 1-12, 2021
152021
Quantitative comparison of deep learning-based image reconstruction methods for low-dose and sparse-angle CT applications
J Leuschner, M Schmidt, PS Ganguly, V Andriiashen, SB Coban, ...
Journal of Imaging 7 (3), 44, 2021
102021
Conditional normalizing flows for low-dose computed tomography image reconstruction
A Denker, M Schmidt, J Leuschner, P Maass, J Behrmann
arXiv preprint arXiv:2006.06270, 2020
82020
Deep inversion validation library
J Leuschner, M Schmidt, D Erzmann
Software available from https://github. com/jleuschn/dival, 2019
52019
Conditional Invertible Neural Networks for Medical Imaging
A Denker, M Schmidt, J Leuschner, P Maass
Journal of Imaging 7 (11), 243, 2021
22021
Is Deep Image Prior in Need of a Good Education?
R Barbano, J Leuschner, M Schmidt, A Denker, A Hauptmann, P Maaß, ...
arXiv preprint arXiv:2111.11926, 2021
12021
Blind source separation in polyphonic music recordings using deep neural networks trained via policy gradients
S Schulze, J Leuschner, EJ King
Signals 2 (4), 637-661, 2021
12021
The LoDoPaB-CT Dataset
J Leuschner, M Schmidt, DO Baguer, P Maaß
arXiv preprint arXiv:1910.01113, 2019
12019
A Probabilistic Deep Image Prior for Computational Tomography
J Antorán, R Barbano, J Leuschner, JM Hernández-Lobato, B Jin
arXiv preprint arXiv:2203.00479, 2022
2022
The Deep Capsule Prior–advantages through complexity?
M Schmidt, A Denker, J Leuschner
PAMM 21 (1), e202100166, 2021
2021
Training a Deep Neural Network via Policy Gradients for Blind Source Separation in Polyphonic Music Recordings
S Schulze, J Leuschner, EJ King
arXiv e-prints, arXiv: 2107.04235, 2021
2021
A Benchmark for Deep Learning Reconstruction Methods for Low-Dose Computed Tomography
M Schmidt, J Leuschner, DO Baguer, P Maaß
2020
Regression Models for Ultrasonic Testing of Carbon Fiber Reinforced Polymers
C Brandt, M Hamann, J Leuschner
Universität Bremen, Zentrum für Technomathematik, Fachbereich 3-Mathematik …, 2019
2019
Zentrum für Technomathematik
C Brandt, M Hamann, J Leuschner
International Workshop on Magnetic Particle Imaging (IWMPI) Book of …, 2017
2017
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Articles 1–17