Recently, manifold learning has been widely exploited in pattern recognition, data analysis, and machine learning. This paper presents a novel framework, called Riemannian manifold...
A novel neural network model is described that implements context-dependent learning of complex sequences. The model utilises leaky integrate-and-fire neurons to extract timing inf...
OpenMP is an architecture-independent language for programming in the shared memory model. OpenMP is designed to be simple and in terms of programming abstractions. Unfortunately,...
Tiling is a well known loop transformation used to reduce communication overhead in distributed memory machines. Although a lot of theoretical research has been done concerning th...
Georgios I. Goumas, Nikolaos Drosinos, Maria Athan...
Texture analysis has been used extensively in the computer-assisted interpretation of digital imagery. A popular texture feature extraction approach is the grey level co-occurrenc...