ZERO Lab
Home
News
People
Publications
Contact
Low-level vision
R^2 Net Recurrent and Recursive Network for Sparse View CT Artifacts Removal
We propose a novel neural network architecture to reduce streak artifacts generated in sparse-view 2D Cone Beam Computed To-mography (CBCT) image reconstruction.
Recurrent Squeeze-and-Excitation Net for Single Image Deraining
We propose a novel deep network architecture based on deep convolutional and recurrent neural networksfor single image deraining.
Cite
×