The task of clustering is to identify classes of similar objects among a set of objects. The definition of similarity varies from one clustering model to another. However, in most ...
Abstract. Popular algorithms for feature matching and model extraction fall into two broad categories, generate-and-test and Hough transform variations. However, both methods suer...
Feature-oriented programming organizes programs around features rather than objects, thus better supporting extensible, product-line architectures. Programming languages increasin...
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
This paper presents an unsupervised learning algorithm that can derive the probabilistic dependence structure of parts of an object (a moving human body in our examples) automatic...