We propose low-rank representation (LRR) to segment data drawn from a union of multiple linear (or affine) subspaces. Given a set of data vectors, LRR seeks the lowestrank represe...
The e-KNOWNET is a Lifelong Learning project, which aims to develop an innovative and viable mechanism to facilitate the flow of new scientific knowledge produced in the research ...
G. Anyfandi, V. Laopodis, V. Koulaidis, Nicolas Ap...
In this paper we present a dynamic texture based motion segmentation approach to address the challenging problem of heart localization and segmentation in 4D Spatio-temporal cardi...
Junzhou Huang, Xiaolei Huang, Dimitris N. Metaxas,...
Abstract. We demonstrate that selective attention can improve learning. Considerably fewer samples are needed to learn a source separation problem when the inputs are pre-segmented...
We present a new variational level-set-based segmentation
formulation that uses both shape and intensity prior information
learned from a training set. By applying Bayes’
rule...