Learning the invisible: a hybrid deep learning-shearlet framework for limited angle computed tomography
Learning the invisible: a hybrid deep learning-shearlet framework for limited angle computed tomography
The high complexity of various inverse problems poses a significant challenge to model-based reconstruction schemes, which in such situations often reach their limits. At the same time, we witness an exceptional success of data-based methodologies such as deep learning. However, in the context of inverse problems, deep neural networks mostly …