We present a numerical framework for Fluorescence Diffuse Optical Tomography (fDOT) that combines a forward model together with an iterative reconstruction procedure. Using rapid ...
This paper presents a novel paradigm for learning languages that consists of mapping strings to an appropriate high-dimensional feature space and learning a separating hyperplane i...
Nowadays color image processing is an essential issue in computer vision. Variational formulations provide a framework for color image restoration, smoothing and segmentation prob...
Many machine learning algorithms can be formulated as a generalized eigenvalue problem. One major limitation of such formulation is that the generalized eigenvalue problem is comp...
We introduce a novel probabilistic approach for nonparametric nonrigid image registration using generalized elastic nets, a model previously used for topographic maps. The idea of...