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Found 9 papers, 3 papers with code
Benchmarking Probabilistic Deep Learning Methods for License Plate Recognition
Such an uncertainty measure allows to detect false predictions, indicating an analyst when not to trust the result of the automated license plate recognition.
Deep learning architectural designs for super-resolution of noisy images
Recent advances in deep learning have led to significant improvements in single image super-resolution (SR) research.
Multi-modal Deep Guided Filtering for Comprehensible Medical Image Processing
In medical imaging, this lack of comprehensibility of the results is a sensitive issue.
Merging-ISP: Multi-Exposure High Dynamic Range Image Signal Processing
As such, it is end-to-end trainable, circumvents the use of hand-crafted and potentially complex algorithms, and mitigates error propagation.
Magnetic Resonance Fingerprinting Reconstruction Using Recurrent Neural Networks
Magnetic Resonance Fingerprinting (MRF) is an imaging technique acquiring unique time signals for different tissues.
RinQ Fingerprinting: Recurrence-informed Quantile Networks for Magnetic Resonance Fingerprinting
Although the acquisition is highly accelerated, the state-of-the-art reconstruction suffers from long computation times: Template matching methods are used to find the most similar signal to the measured one by comparing it to pre-simulated signals of possible parameter combinations in a discretized dictionary.
Adaptive Quantile Sparse Image (AQuaSI) Prior for Inverse Imaging Problems
Inverse problems play a central role for many classical computer vision and image processing tasks.
Temporal and volumetric denoising via quantile sparse image prior
For the purpose of denoising, we propose a variational framework based on the QuaSI prior and a Huber data fidelity model that can handle 3-D and 3-D+t data.
QuaSI: Quantile Sparse Image Prior for Spatio-Temporal Denoising of Retinal OCT Data
Optical coherence tomography (OCT) enables high-resolution and non-invasive 3D imaging of the human retina but is inherently impaired by speckle noise.
