Developers of new imageanalysis algorithmstypically require an interactive environment in which the imagedata can be passed through various operators, some of which may involve fe...
M. Stella Atkins, Torre Zuk, B. Johnston, T. Arden
This paper proposes the use of uncertainty reduction in machine learning methods such as co-training and bilingual bootstrapping, which are referred to, in a general term, as ‘c...
In this paper, the problem of non-regular static state feedback linearization of a ne nonlinear systems is considered. First of all, a new canonical form for non-regular feedback ...
Many scientific applications generate massive volumes of data through observations or computer simulations, bringing up the need for effective indexing methods for efficient stora...
The task of balancing dynamically generated work load occurs in a wide range of parallel and distributed applications. Diffusion based schemes, which belong to the class of neares...