This paper investigates the role of existing "probabilistic" schemes to reason about various everyday situations on the basis of data from multiple heterogeneous physical...
Abstract— Highly heterogeneous robotic systems are becoming increasingly common, as are robotic systems integrated with smart environments. In such distributed systems, there are...
— Humans can control MIMO (Multiple-Input Multiple-Output) objects appropriately using knowledge of the MIMO object, which can be referred to as human MIMO control knowledge. An ...
In this work an improved scheme for eliminating impulsive noise of varying strengths from corrupted images is proposed. A neural network is employed to classify the corrupted and n...
—Approaches based on conditional independence tests are among the most popular methods for learning graphical models from data. Due to the predominance of Bayesian networks in th...