In this paper we develop a theory of non-parametric self-calibration. Recently, schemes have been devised for non-parametric laboratory calibration, but not for selfcalibration. W...
Based on the theory of Markov Random Fields, a Bayesian regularization model for diffusion tensor images (DTI) is proposed in this paper. The low-degree parameterization of diffus...
Siming Wei, Jing Hua, Jiajun Bu, Chun Chen, Yizhou...
Abstract. In this paper we study a new approach to classify mathematical theorems according to their computational content. Basically, we are asking the question which theorems can...
This study describes a discourse approach to explanation aware knowledge representation. It presents a reasoning model that adheres to argumentation as found in written discourse,...
This paper presents a Bayesian framework for generating inverse-consistent inter-subject large deformation transformations between two multi-modal image sets of the brain. In this...