Modeling moving and deforming objects requires capturing as much information as possible during a very short time. When using off-the-shelf hardware, this often hinders the resolu...
Abstract. Clustering high dimensional data with sparse features is challenging because pairwise distances between data items are not informative in high dimensional space. To addre...
The emerging theory of compressed sensing (CS) provides a universal signal detection approach for sparse signals at sub-Nyquist sampling rates. A small number of random projection...
Simple binary patterns have been successfully used for extracting feature representations for visual object classification. In this paper, we present a method to learn a set of d...
In the Ad-Hoc InfoWare project, we develop a delay tolerant event notification service for sparse Mobile Ad-Hoc Networks for emergency and rescue operations. In most event notific...
Anna K. Lekova, Katrine Stemland Skjelsvik, Thomas...