We describe a novel method whereby a particle filter is used to create a potential field for robot control without prior clustering. We show an application of this technique to ...
This paper addresses the supervised learning in which the class membership of training data are subject to uncertainty. This problem is tackled in the framework of the Dempster-Sha...
In this paper, we investigate the use of the watershed transformation for integrating spatial and spectral information in the process of endmember extraction for spectral unmixing...
Real life datasets often suffer from the problem of class imbalance, which thwarts supervised learning process. In such data sets examples of positive (minority) class are signific...
Many large-scale distributed systems have been built with great complexity to run Internet services. Due to the heterogeneity and dynamics of complex systems, it is very difficult ...