Self-learning facial emotional feature selection based on rough set theory.
Semi-topological classification of line patterns in the plane
Several comments on pattern recognition system based on the use of attributed grammars
Shape-from-Shading, viscosity solutions and edges.
Signature verification: A comprehensive study of the hidden signature method
Many handwritten signature verification algorithms have been developed in order to distinguish between genuine signatures and forgeries. An important group of these methods is based on dynamic time warping (DTW). Traditional use of DTW for signature verification consists in forming a misalignment score between the verified signature and a set of template signatures. The right selection of template signatures has a big impact on that verification. In this article, we describe our proposition for...
Simple use of pattern recognition in experiment analysis
Some methods of constructing kernels in statistical learning
This paper is a collection of numerous methods and results concerning a design of kernel functions. It gives a short overview of methods of building kernels in metric spaces, especially and . However we also present a new theory. Introducing kernels was motivated by searching for non-linear patterns by using linear functions in a feature space created using a non-linear feature map.
Some variants of Hausdorff distance for word matching
Spectral fuzzy classification system: a supervised approach.
The goal of this paper is to present all algorithm for pattern recognition, leveraging on an existing fuzzy clustering algorithm developed by Del Amo et al. [3, 5], and modifying it to its supervised version, in order to apply the algorithm to different pattern recognition applications in Remote Sensing. The main goal is to recognize the object and stop the search depending on the precision of the application. The referred algorithm was the core of a classification system based on Fuzzy Sets Theory...
Statistical approach to pattern recognition: Theory and practical solution by means of PREDITAS system
Strategies for seeing.
Strict maximum separability of two finite sets: an algorithmic approach
The paper presents a recursive algorithm for the investigation of a strict,linear separation in the Euclidean space. In the case when sets are linearly separable, it allows us to determine the coefficients of the hyperplanes. An example of using this algorithm as well as its drawbacks are shown. Then the algorithm of determining an optimal separation (in the sense of maximizing the distance between the two sets) is presented.
Summaries of certain spatial patterns retrieved from multidate remote-sensing data.