This paper discusses the clustering quality and complexities of the hierarchical data clustering algorithm based on gravity theory. The gravitybased clustering algorithm simulates ...
: In many computer vision classification problems, both the error and time characterizes the quality of a decision. We show that such problems can be formalized in the framework of...
Among image restoration literature, there are mainly two kinds of approach. One is based on a process over image wavelet coefficients, as wavelet shrinkage for denoising. The other...
Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for highdimensional sparse data commonly encountered in applications like t...
The problem attempted in this paper is to select a sample from a large set where the sample is required to have a particular average property. The problem can be expressed as an o...