In this paper, we introduce a new method, GraphScape, to visualize multivariate networks, i.e., graphs with multivariate data associated with their nodes. GraphScape adopts a land...
Kai Xu 0003, Andrew Cunningham, Seok-Hee Hong, Bru...
Our goal is to define a list of tasks for graph visualization that has enough detail and specificity to be useful to designers who want to improve their system and to evaluators w...
Visualization can largely improve biomedical data analysis. It plays a crucial role in explorative data analysis and may support various data mining tasks. The paper presents Free...
We propose a multi-target tracking algorithm based on the Probability Hypothesis Density (PHD) filter and data association using graph matching. The PHD filter is used to compen...
Emilio Maggio, Elisa Piccardo, Carlo S. Regazzoni,...
We describe MGV, an integrated visualization and exploration system for massive multi-digraph navigation. MGV’s only assumption is that the vertex set of the underlying digraph ...