The Support Vector Machine (SVM) is a powerful tool for classification. We generalize SVM to work with data objects that are naturally understood to be lying on curved manifolds, ...
Suman K. Sen, Mark Foskey, James Stephen Marron, M...
This work presents the application of a novel technique on dimensionality reduction to deal with multispectral images. A distance based on mutual information is used to construct ...
A novel frequency-domain technique for image blocking artifact detection and reduction is presented in this paper. The algorithm first detects the regions of the image which presen...
George A. Triantafyllidis, Dimitrios Tzovaras, Mic...
Abstract-- The projection data measured in computed tomography (CT) and, consequently, the slices reconstructed from these data are noisy. We present a new wavelet based structurep...
Anja Borsdorf, Rainer Raupach, Thomas Flohr, Joach...
“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal