In this paper, a State-Based Dynamic Transportation Network (SBDTN) model is presented, which can be used to describe the spatiotemporal aspect of temporally variable transportatio...
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
In the demonstration, we will present the concepts and an implementation of an inductive database ? as proposed by Imielinski and Mannila ? in the relational model. The goal is to...
Quantifying the motion and deformation of large numbers of cells through image sequences obtained with fluorescence microscopy is a recurrent task in many biological studies. Aut...
Oleh Dzyubachyk, Wiro J. Niessen, Erik H. W. Meije...
In this paper, we propose a novel method for rapid feature space Maximum Likelihood Linear Regression (FMLLR) speaker adaptation based on bilinear models. When the amount of adapt...