Principal component analysis (PCA) is often applied for analyzing data in the most diverse
areas. This work reports, in an accessible and integrated manner, several theoretical and …

The capacity to recognize faces under varied poses is a fundamental human ability that
presents a unique challenge for computer vision systems. Compared to frontal face …

This study attempts to identify the essential conditioning factors of landslides to increase the
predictive ability of landslide susceptibility models and explore the effects of different grid …

Fractional calculus is an abstract idea exploring interpretations of differentiation having non-
integer order. For a very long time, it was considered as a topic of mere theoretical interest …

Making recognition more reliable under uncontrolled lighting conditions is one of the most
important challenges for practical face recognition systems. We tackle this by combining the …

Government agencies are investing a considerable amount of resources into improving
security systems as result of recent terrorist events that dangerously exposed flaws and …

The traditional image representations are not suited to conventional classification methods,
such as the linear discriminant analysis (LDA), because of the under sample problem (USP) …

Fog computing is a recently proposed computing paradigm that extends Cloud computing
and services to the edge of the network. The new features offered by fog computing (eg …

In some recent studies, a view emerged that stochastic dynamics governing the switching of
cells from one differentiation state to another could be characterized by a peak in gene …

One of the major challenges encountered by current face recognition techniques lies in the
difficulties of handling varying poses, ie, recognition of faces in arbitrary in-depth rotations …