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math.NA2024
Error Estimates for Data-driven Weakly Convex Frame-based Image Regularization
Andrea Ebner, Matthias Schwab, Markus Haltmeier
Inverse problems are fundamental in fields like medical imaging, geophysics, and computerized tomography, aiming to recover unknown quantities from observed data. However, these pr…
cs.CV2024
A lightweight residual network for unsupervised deformable image registration
Ahsan Raza Siyal, Astrid Ellen Grams, Markus Haltmeier
Accurate volumetric image registration is highly relevant for clinical routines and computer-aided medical diagnosis. Recently, researchers have begun to use transformers in learni…
cs.CV2024
Deep Gaussian mixture model for unsupervised image segmentation
Matthias Schwab, Agnes Mayr, Markus Haltmeier
The recent emergence of deep learning has led to a great deal of work on designing supervised deep semantic segmentation algorithms. As in many tasks sufficient pixel-level labels…