Supervised learning aims to train a classifier under the assumption that training and test
data are from the same distribution. To ease the above assumption, researchers have …

Pattern recognition, image processing and computer vision are closely linked areas which
have seen enormous progress in the last fifty years. Their applications in our daily life …

Image denoising—removal of additive white Gaussian noise from an image—is one of the
oldest and most studied problems in image processing. Extensive work over several …

The authors consider the problem of robustly estimating optical flow from a pair of images
using a new framework based on robust estimation which addresses violations of the …

This paper addresses three major issues associated with conventional partitional clustering,
namely, sensitivity to initialization, difficulty in determining the number of clusters, and …

We study a bootstrap method which is based on the method of sieves. A linear process is
approximated by a sequence of autoregressive processes of order p= p (n), where p (n)→∞ …

Using a sample of 76 banks from the Gulf Cooperation Council region, we use accounting-
as well as market-based measures of financial stability to examine whether Islamic banks …

This paper describes a method to estimate parametric motion models. Motivations for the
use of such models are, on one hand, their efficiency, which has been demonstrated in …

The incorporation of sex and gender (S/G) related factors is commonly acknowledged as a
necessary step to advance towards more personalized diagnoses and treatments for …

The basic limitations of the standard appearance-based matching methods using
eigenimages are nonrobust estimation of coefficients and inability to cope with problems …