A neural net with multiple output nodes is capable of distinguishing among a set of related input classes even in the absence of training. It can do so with an accuracy that is ma...
This paper investigates a new learning formulation called dynamic group sparsity. It is a natural extension of the standard sparsity concept in compressive sensing, and is motivat...
In this paper, an approach based on the combination of discrete Hidden Markov Models (HMMs) in the ROC space is proposed to improve the performance of off-line signature verificat...
We address the problem of shape based classification. We interpret the shape of an object as a probability distribution governing the location of the points of the object. An imag...
Nowadays various digital television services are available. However, the user of these services experiences longer delays than the traditional analog TV while switching from chann...