In this paper, we tackle a fully unsupervised super-resolution problem, ...
Data augmentation is an effective way to improve the performance of deep...
Devising indicative evaluation metrics for the image generation task rem...
A good image-to-image translation model should learn a mapping between
d...
We propose a generic confidence-based approximation that can be plugged ...
Recent style transfer models have provided promising artistic results.
H...
Answerer in Questioner's Mind (AQM) is an information-theoretic framewor...
We present a hybrid framework that leverages the trade-off between tempo...
Accelerated magnetic resonance (MR) scan acquisition with compressed sen...
An inverse elastic source problem with sparse measurements is of concern...
Can artificial intelligence (AI) learn complicated non-linear physics? H...
Model based iterative reconstruction (MBIR) algorithms for low-dose X-ra...
Purpose: A radial k-space trajectory is one of well-established sampling...
Purpose: Compressed sensing MRI (CS-MRI) from single and parallel coils ...
Recently, compressed sensing (CS) computed tomography (CT) using sparse
...
The latest deep learning approaches perform better than the state-of-the...