As technology expands and evolves, one-dimensional, graphical user interface (GUI) design
becomes increasingly limiting and simplistic. Designers must meet the challenge of …

In this paper, we propose a new method for recognizing hand gestures in a continuous
video stream using a dynamic Bayesian network or DBN model. The proposed method of …

Cyber–physical systems (CPSs) are evolving from individual systems to collectives of
systems that collaborate to achieve highly complex goals, realizing a cyber–physical system …

Limited range and charging infrastructure leads to range anxiety of electric vehicle drivers.
Current range estimation algorithms are deemed unreliable and large safety margins are …

Abstract Bayesian Network classifiers (BNCs) are Bayesian Network (BN) models
specifically tailored for classification tasks. There is a wide range of existing models that vary …

In this paper, we describe a dynamic Bayesian network or DBN based approach to both two-
hand gestures and one-hand gestures. Unlike wired glove-based approaches, the success …

In this paper we present a study to assess the performance of dynamic naive Bayesian
classifiers (DNBCs) versus standard hidden Markov models (HMMs) for gesture recognition …

Many problems such as voice recognition, speech recognition and many other tasks have
been tackled with Hidden Markov Models (HMMs). These problems can also be dealt with …

Naive Bayesian classifiers work well in data sets with independent attributes. However, they
perform poorly when the attributes are dependent or when there are one or more irrelevant …

With the flourish development of computer vision technology, hand gesture recognition plays
a more and more vital role in human-computer interaction for its convenient and nonverbal …