Abstract— Designing effective behavioral controllers for mobile robots can be difficult and tedious; this process can be circumvented by using unsupervised learning techniques w...
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
In this work, we explore the use of a learning-based framework for retrieval of relevant mammogram images from a database, for purposes of aiding diagnoses. A fundamental issue is...
Issam El-Naqa, Yongyi Yang, Miles N. Wernick, Niko...
Abstract. This work describes an evolutionary approach to texture segmentation, a long-standing and important problem in computer vision. The difficulty of the problem can be relat...
The assessment of the reliability of clusters discovered in bio-molecular data is a central issue in several bioinformatics problems. Several methods based on the concept of stabil...