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.
Test lineární separability
Text document classification based on mixture models
Finite mixture modelling of class-conditional distributions is a standard method in a statistical pattern recognition. This paper, using bag-of-words vector document representation, explores the use of the mixture of multinomial distributions as a model for class-conditional distribution for multiclass text document classification task. Experimental comparison of the proposed model and the standard Bernoulli and multinomial models as well as the model based on mixture of multivariate Bernoulli distributions...
The 2nd Conference on Digitization
The concept of indirectness in artificial intelligence
The current approaches in pattern recognition
The employment of Prolog for a syntax analysis in syntactic pattern recognition applications
The finite automata approaches in stringology
We present an overview of four approaches of the finite automata use in stringology: deterministic finite automaton, deterministic simulation of nondeterministic finite automaton, finite automaton as a model of computation, and compositions of finite automata solutions. We also show how the finite automata can process strings build over more complex alphabet than just single symbols (degenerate symbols, strings, variables).
The present and future of signal processing
The quantitative evaluation of image quality and definition of an image
The relation of two patterns with comparable languages patterns
The structural description of self-embedding nature of waveform peaks
Theory of classification : a survey of some recent advances
The last few years have witnessed important new developments in the theory and practice of pattern classification. We intend to survey some of the main new ideas that have led to these recent results.