We propose the use of latent space models applied to local invariant features for object classification. We investigate whether using latent space models enables to learn patterns...
Florent Monay, Pedro Quelhas, Daniel Gatica-Perez,...
Interactive data visualization is inherently an iterative trial-and-error process searching for an ideal set of parameters for classifying and rendering features of interest in th...
This paper presents an agent-based approach to semantic exploration and knowledge discovery in large information spaces by means of capturing, visualizing and making usable implic...
Jasminko Novak, Michael Wurst, Monika Fleischmann,...
This paper adopts the premise that the ‘semantic gap' is an incompletely surveyed feature in the landscape of visual image retrieval, and proposes a framework within which t...
The comprehensive understanding of today’s software systems is a daunting activity, because of the sheer size and complexity that such systems exhibit. Moreover, software system...