We develop an efficient learning framework to construct signal dictionaries for sparse representation by selecting the dictionary columns from multiple candidate bases. By sparse,...
In this work we address the problem of boundary detection by combining ideas and approaches from biological and computational vision. Initially, we propose a simple and efficient ...
Iasonas Kokkinos, Rachid Deriche, Olivier D. Fauge...
We propose a reduced algebraic cost based on pairwise epipolar constraints for the iterative refinement of a multiple view 3D reconstruction. The aim is to accelerate the intermedi...
Background: Identification of gene and protein names in biomedical text is a challenging task as the corresponding nomenclature has evolved over time. This has led to multiple syn...
Daniel Hanisch, Katrin Fundel, Heinz-Theodor Mevis...
The paper proposes a new method to perform foreground detection by means of background modeling using the tensor concept. Sometimes, statistical modelling directly on image values...