In the last decade, there has been a massive increase in network research across both the social and physical sciences. In Physics and Mathematics, there have been extensive work o...
Predicting latency between nodes on the internet can have a significant impact on the performance of many services that use latency distances among nodes as a decision making input...
Determining Euclidean transformations for the robust registration of noisy unstructured point sets is a key problem of model-based computer vision and numerous industrial applicati...
The aim of this paper is to propose a new Kalman Filter Recurrent Neural Network (KFRNN) topology and a recursive Levenberg-Marquardt (L-M) algorithm of its learning capable to est...
We consider the problem of fitting linearly parameterized models, that arises in many computer vision problems such as road scene analysis. Data extracted from images usually cont...