Homologydetection in large data bases is probably the most time consuming operation in molecular genetic computing systems. Moreover, the progresses made all around the world conc...
We propose a novel method for automatically discover-ing key motion patterns happening in a scene by observing the scene for an extended period. Our method does not rely on object ...
Abstract. Self-Organizing Map (SOM) is an unsupervised learning neural network and it is used for preserving the structural relationships in the data without prior knowledge. SOM h...
Abstract. We present a strategy to develop, in a functional setting, correct, e cient and portable Divide-and-Conquer (DC) programs for massively parallel architectures. Starting f...
Subspace learning techniques are widespread in pattern recognition research. They include PCA, ICA, LPP, etc. These techniques are generally linear and unsupervised. The problem o...