Cardiac segmentation is in great demand for clinical practice. Due to th...
We propose a method to infer a dense depth map from a single image, its
...
We present a method to segment MRI scans of the human brain into ischemi...
We present a method to infer a dense depth map from a color image and
as...
Generative adversarial networks (GAN) is a framework for generating fake...
Regularization is essential for avoiding over-fitting to training data i...
We propose a first-order stochastic optimization algorithm incorporating...
We present an adaptive regularization algorithm that can be effectively
...
Regularization in the optimization of deep neural networks is often crit...
Supervised learning methods to infer (hypothesize) depth of a scene from...
We present a stochastic first-order optimization algorithm, named BCSC, ...
We present an adaptive regularization scheme for optimizing composite en...
We present a variational multi-label segmentation algorithm based on a r...
We propose an adaptive regularization scheme in a variational framework ...
We formulate a general energy and method for segmentation that is design...
In this paper, we propose a method for tracking structures (e.g., ventri...