We propose a new methodology for fusing temporally changing multisensor raster and vector data by developing a spatially and temporally varying uncertainty model of acquired and t...
We investigate techniques for analysis and retrieval of object trajectories in a two or three dimensional space. Such kind of data usually contain a great amount of noise, that ma...
Michail Vlachos, Dimitrios Gunopulos, George Kolli...
De-noising of SPECT and PET images is a challenging task due to the inherent low signal-to-noise ratio of acquired data. Wavelet based multiscale denoising methods typically apply ...
Yinpeng Jin, Elsa D. Angelini, Peter D. Esser, And...
Background: Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples ar...
— Missing feature theory (MFT) has demonstrated great potential for improving the noise robustness in speech recognition. MFT was mostly applied in the log-spectral domain since ...