In this paper we address the problem of how to learn a structural prototype that can be used to represent the variations present in a set of trees. The prototype serves as a patte...
Self-organizing models develop realistic cortical structures when given approximations of the visual environment as input, and are an effective way to model the development of fac...
T h e ease of learning concepts f r o m examples in empirical machine learning depends on the attributes used for describing the training d a t a . We show t h a t decision-tree b...
Feature selection and weighting are central problems in pattern recognition and instance-based learning. In this work, we discuss the challenges of constructing and weighting feat...
Kreshna Gopal, Tod D. Romo, James C. Sacchettini, ...
A visual word lexicon can be constructed by clustering primitive visual features, and a visual object can be described by a set of visual words. Such a "bag-of-words" re...