The elementary theories of Shannon information and Kolmogorov complexity are cmpared, the extent to which they have a common purpose, and where they are fundamentally different. T...
In this paper, we first introduce a 3D morphing method for landmark-based volume deformation, using various scattered data interpolation schemes. Qualitative and speed comparisons...
Many machine learning algorithms require the summation of Gaussian kernel
functions, an expensive operation if implemented straightforwardly. Several methods
have been proposed t...
Vlad I. Morariu1, Balaji V. Srinivasan, Vikas C. R...
Shape analysis requires invariance under translation, scale and rotation. Translation and scale invariance can be realized by normalizing shape vectors with respect to their mean ...
?This paper presents a computational paradigm called Data-Driven Markov Chain Monte Carlo (DDMCMC) for image segmentation in the Bayesian statistical framework. The paper contribut...