Neural network ensemble is a learning paradigm where many neural networks are jointly used to solve a problem. In this paper, the relationship between the ensemble and its compone...
We propose a content-based information retrieval (CBIR) method that models known relationships between multimedia objects as a hierarchical tree-structure incorporating additional ...
Users tend to use the Internet for “resource-hungry” applications (which involve content such as video, audio on-demand and distributed data) and at the same time, more and mo...
George Pallis, Konstantinos Stamos, Athena Vakali,...
The paper deals with the concept of relevance learning in learning vector quantization and classification. Recent machine learning approaches with the ability of metric adaptation...
Thomas Villmann, Frank-Michael Schleif, Barbara Ha...
We present a hybrid and parallel system based on artificial neural networks for a face invariant classifier and general pattern recognition problems. A set of face features is ext...
Peter V. Bazanov, Tae-Kyun Kim, Seok-Cheol Kee, Sa...