5 papers
Prediction error-driven memory consolidation for continual learning. On the case of adaptive greenhouse models
Guido Schillaci, Luis Miranda, Uwe Schmidt
This work presents an adaptive architecture that performs online learning and faces catastrophic forgetting issues by means of episodic memories and prediction-error driven memory…
Practical sensorless aberration estimation for 3D microscopy with deep learning
Debayan Saha, Uwe Schmidt, Qinrong Zhang +6
Estimation of optical aberrations from volumetric intensity images is a key step in sensorless adaptive optics for 3D microscopy. Recent approaches based on deep learning promise a…
An interpretable automated detection system for FISH-based HER2 oncogene amplification testing in histo-pathological routine images of breast and gastric cancer diagnostics
Sarah Schmell, Falk Zakrzewski, Walter de Back +10
Histo-pathological diagnostics are an inherent part of the everyday work but are particularly laborious and associated with time-consuming manual analysis of image data. In order t…
Star-convex Polyhedra for 3D Object Detection and Segmentation in Microscopy
Martin Weigert, Uwe Schmidt, Robert Haase +2
Accurate detection and segmentation of cell nuclei in volumetric (3D) fluorescence microscopy datasets is an important step in many biomedical research projects. Although many auto…
Cell Detection with Star-convex Polygons
Uwe Schmidt, Martin Weigert, Coleman Broaddus +1
Automatic detection and segmentation of cells and nuclei in microscopy images is important for many biological applications. Recent successful learning-based approaches include per…