A common trait of background subtraction algorithms is that they have learning rates, thresholds, and initial values that are hand-tuned for a scenario in order to produce the des...
A new framework of compressive sensing (CS), namely statistical compressive sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical dist...
EM algorithm is a very popular iteration-based method to estimate the parameters of Gaussian Mixture Model from a large observation set. However, in most cases, EM algorithm is no...
In this paper, a spatially constrained mixture model for the segmentation of MR brain images is presented. The novelty of this work is a new, edge preserving, smoothness prior whic...
Giorgos Sfikas, Christophoros Nikou, Nikolas P. ...
With smart-phones becoming increasingly commonplace, there has been a subsequent surge in applications that continuously track the location of users. However, serious privacy conc...