1 citations · 1 across the 3 of their papers we have counts for
9 papers
Benchmarking Probabilistic Deep Learning Methods for License Plate Recognition
Franziska Schirrmacher, Benedikt Lorch, Anatol Maier +1
Learning-based algorithms for automated license plate recognition implicitly assume that the training and test data are well aligned. However, this may not be the case under extrem…
Deep learning architectural designs for super-resolution of noisy images
Angel Villar-Corrales, Franziska Schirrmacher, Christian Riess
Recent advances in deep learning have led to significant improvements in single image super-resolution (SR) research. However, due to the amplification of noise during the upsampli…
Multi-modal Deep Guided Filtering for Comprehensible Medical Image Processing
Bernhard Stimpel, Christopher Syben, Franziska Schirrmacher +3
Deep learning-based image processing is capable of creating highly appealing results. However, it is still widely considered as a "blackbox" transformation. In medical imaging, thi…
Merging-ISP: Multi-Exposure High Dynamic Range Image Signal Processing
Prashant Chaudhari, Franziska Schirrmacher, Andreas Maier +2
High dynamic range (HDR) imaging combines multiple images with different exposure times into a single high-quality image. The image signal processing pipeline (ISP) is a core compo…
Magnetic Resonance Fingerprinting Reconstruction Using Recurrent Neural Networks
Elisabeth Hoppe, Florian Thamm, Gregor Körzdörfer +6
Magnetic Resonance Fingerprinting (MRF) is an imaging technique acquiring unique time signals for different tissues. Although the acquisition is highly accelerated, the reconstruct…
RinQ Fingerprinting: Recurrence-informed Quantile Networks for Magnetic Resonance Fingerprinting
Elisabeth Hoppe, Florian Thamm, Gregor Körzdörfer +6
Recently, Magnetic Resonance Fingerprinting (MRF) was proposed as a quantitative imaging technique for the simultaneous acquisition of tissue parameters such as relaxation times $T…