Maximilian Schmidt

140

105

20182019202020212022202320241 5 29 67 97 139 53

Public access

5 articles

0 articles

available

not available

Based on funding mandates

Peter MaassProfessor Mathematics, University of BremenVerified email at math.uni-bremen.de
Daniel Otero BaguerPostDoc, University of BremenVerified email at uni-bremen.de
Jens BehrmannApple AI/ML ResearchVerified email at apple.com
Kees Joost BatenburgProfessor of Imaging and VisualizationVerified email at liacs.leidenuniv.nl
Maureen van EijnattenTeam Lead / Program Scientist, Dept. of Crop Data Science, KeyGene N.V.Verified email at keygene.com
Sophia Bethany CobanPost-doctoral Researcher at the University of ManchesterVerified email at manchester.ac.uk
Poulami Somanya GangulySchool of Mathematical Sciences, Queen Mary University of LondonVerified email at qmul.ac.uk
Christian EtmannSenior Research Scientist, Deep RenderVerified email at deeprender.ai

Maximilian Schmidt

Verified email at uni-bremen.de - Homepage


Title Sort by citations Sort by year Sort by 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	159	2020
LoDoPaB-CT, a benchmark dataset for low-dose computed tomography reconstruction J Leuschner, M Schmidt, DO Baguer, P Maass Scientific Data 8 (1), 109, 2021	70	2021
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	53	2019
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	47	2019
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	44	2021
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	17	2020
Deep relevance regularization: Interpretable and robust tumor typing of imaging mass spectrometry data C Etmann, M Schmidt, J Behrmann, T Boskamp, L Hauberg-Lotte, A Peter, ... arXiv preprint arXiv:1912.05459, 2019	2	2019
Around the clock‐capsule networks and image transformations M Schmidt PAMM 20 (1), e202000179, 2021		2021

The system can't perform the operation now. Try again later.

Articles 1–8

Citations per year