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,...
Abstract. Selective attention shift can help neural networks learn invariance. We describe a method that can produce a network with invariance to changes in visual input caused by ...
—Current visual analytics systems provide users with the means to explore trends in their data. Linked views and interactive displays provide insight into correlations among peop...
Ross Maciejewski, Ryan Hafen, Stephen Rudolph, Ste...
Existing temporal pattern mining assumes that events do not have any duration. However, events in many real world applications have durations, and the relationships among these ev...
A sensor network data gathering and visualization infrastructure is demonstrated, comprising of Global Sensor Networks (GSN) middleware and Microsoft SensorMap. Users are invited t...
Sebastian Michel, Ali Salehi, Liqian Luo, Nicholas...