Seminář: Intelligent Image retrieval using numerical linear algebra and applications

Rapid development of information technologies provides users a simple and easy access to a very large amount of data, for instance texts, images and voice. Unfortunately, wide popular techniques, which are based on keyword matching are not very efficient for real text databases because of polysemy (words having multiple meanings), synonymy (multiple words having the same meaning) and omnipresent typing errors. Moreover, real digital images contain reflex and noise, measured data are always with weighted by the measurements errors and a human conversation in traffic is not simple because of a background noise of the car engine. Recently, the methods of numerical linear algebra, especially Singular Value Decomposition (SVD), are successfully used for instance for the face recognition and reconstruction, biometrics identification via the iris recognition, as a tool for the gene expression data analysis in biology, for the macroeconomic data analysis in economics, for the information extraction from HTML product catalogues and for the analysis of geochemical data.