This paper focuses on data fusion, which is fundamental to one of the most important
modules in any autonomous system: perception. Over the past decade, there has been a …

Speech recognition and speaker recognition by machine are crucial ingredients for many
important applications such as natural and flexible human-machine interfaces. Most …

Most biometric systems that are presently in use, typically use a single biometric trait to
establish identity (ie, they are unibiometric systems). With the proliferation of biometric …

Gaussian Mixture Models (GMMs) and Radial Basis Function (RBF) networks are two of the
promising neural models for pattern classification. In this laboratory exercise, your task is to …

In recent years, the field of Universal Access has made significant progress in consolidating
theoretical approaches, scientific methods and technologies, as well as in exploring new …

Multibiometric systems, which consolidate information from multiple biometric sources, are
gaining popularity because they are able to overcome limitations such as non-universality …

Face-voice matching is a task to find correspondence between faces and voices. Many
researches in cognitive science have confirmed human ability in the face-voice matching …

This paper explores the fusion of audio and visual evidences through a multi-level hybrid
fusion architecture based on dynamic Bayesian network (DBN), which combines model level …

It has been demonstrated that multibiometrics can produce higher accuracy than single
biometrics. This is mainly because the use of multiple biometric traits of the subject enables …

Establishing identity is becoming critical in our vastly interconnected society. Questions such
as “Is she really who she claims to be?,”“Is this person authorized to use this facility?,” or “Is …