We present a novel method for learning with Gaussian process regression in a hierarchical Bayesian framework. In a first step, kernel matrices on a fixed set of input points are l...
We propose a new approach for the restoration of polarimetric Stokes images, capable of simultaneously segmenting and restoring the images. In order to easily handle the admissibi...
An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of i...
We present a new approach to estimating mixture models based on a new inference principle we have proposed: the latent maximum entropy principle (LME). LME is different both from ...
Due to variations of lighting conditions, camera hardware settings, and the range of skin coloration among human beings, a pre-defined skin-color model cannot accurately capture t...