Abstract. We introduce a non-linear shape prior for the deformable model framework that we learn from a set of shape samples using recent manifold learning techniques. We model a c...
For many types of machine learning algorithms, one can compute the statistically optimal" way to select training data. In this paper, we review how optimal data selection tec...
David A. Cohn, Zoubin Ghahramani, Michael I. Jorda...
This paper presents a new information acquisition problem motivated by business applications where customer data has to be acquired with a specific modeling objective in mind. In ...
Abstract. Triple graph transformation has become an important approach for model transformations. Triple graphs consist of a source, a target and a connection graph. The correspond...
— We present a method for learning activity-based ground models based on a multiple particle filter approach to motion tracking in video acquired from a moving aerial platform. ...
Andrew Lookingbill, David Lieb, David Stavens, Seb...