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A Closer Look at Reference Learning for Fourier Phase Retrieval
Tobias Uelwer, Nick Rucks, Stefan Harmeling
Reconstructing images from their Fourier magnitude measurements is a problem that often arises in different research areas. This process is also referred to as phase retrieval. In…
Non-Iterative Phase Retrieval With Cascaded Neural Networks
Tobias Uelwer, Tobias Hoffmann, Stefan Harmeling
Fourier phase retrieval is the problem of reconstructing a signal given only the magnitude of its Fourier transformation. Optimization-based approaches, like the well-established G…
Learning to Plan via a Multi-Step Policy Regression Method
Stefan Wagner, Michael Janschek, Tobias Uelwer +1
We propose a new approach to increase inference performance in environments that require a specific sequence of actions in order to be solved. This is for example the case for maze…
Contour Proposal Networks for Biomedical Instance Segmentation
Eric Upschulte, Stefan Harmeling, Katrin Amunts +1
We present a conceptually simple framework for object instance segmentation called Contour Proposal Network (CPN), which detects possibly overlapping objects in an image while simu…
2D histology meets 3D topology: Cytoarchitectonic brain mapping with Graph Neural Networks
Christian Schiffer, Stefan Harmeling, Katrin Amunts +1
Cytoarchitecture describes the spatial organization of neuronal cells in the brain, including their arrangement into layers and columns with respect to cell density, orientation, o…