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Near-Exact Recovery for Tomographic Inverse Problems via Deep Learning

Near-Exact Recovery for Tomographic Inverse Problems via Deep Learning

14 June 2022
Martin Genzel
Ingo Gühring
Jan Macdonald
M. März
ArXivPDFHTML

Papers citing "Near-Exact Recovery for Tomographic Inverse Problems via Deep Learning"

4 / 4 papers shown
Title
Non-Asymptotic Uncertainty Quantification in High-Dimensional Learning
Non-Asymptotic Uncertainty Quantification in High-Dimensional Learning
Frederik Hoppe
C. M. Verdun
Hannah Laus
Felix Krahmer
Holger Rauhut
UQCV
29
1
0
18 Jul 2024
Limited-Angle Tomography Reconstruction via Deep End-To-End Learning on
  Synthetic Data
Limited-Angle Tomography Reconstruction via Deep End-To-End Learning on Synthetic Data
Thomas Germer
Jan Robine
S. Konietzny
Stefan Harmeling
Tobias Uelwer
MedIm
23
5
0
13 Sep 2023
Let's Enhance: A Deep Learning Approach to Extreme Deblurring of Text
  Images
Let's Enhance: A Deep Learning Approach to Extreme Deblurring of Text Images
Theophil Trippe
Martin Genzel
Jan Macdonald
M. März
34
1
0
18 Nov 2022
On the Convergence Rate of Projected Gradient Descent for a
  Back-Projection based Objective
On the Convergence Rate of Projected Gradient Descent for a Back-Projection based Objective
Tom Tirer
Raja Giryes
27
13
0
03 May 2020
1