Support vector (SV) machines are useful tools to classify populations characterized by abrupt decreases in density functions. At least for one class of Gaussian data model the SV ...
Neural networks and other sophisticated machine learning algorithms frequently miss simple solutions that can be discovered by a more constrained learning methods. Transition from ...
Abstract. An application of the recently proposed generalized relevance learning vector quantization (GRLVQ) to the analysis and modeling of time series data is presented. We use G...
This paper presents a biologically motivated model for low and mid-level vision tasks and its interpretation in computer vision terms. Initially we briefly present the biologically...
Abstract. This paper presents a method for estimating the orientation of planar text surfaces using the edge-direction distribution (EDD) extracted from the image as input to a neu...